IDEAS home Printed from https://ideas.repec.org/e/c/pha10.html
   My authors  Follow this author

Nikolaus Hautsch

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüß, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Menac, 2024. "Nonstandard errors," LSE Research Online Documents on Economics 123002, London School of Economics and Political Science, LSE Library.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad‐Díaz & Menachem (Meni) Abudy , 2024. "Nonstandard Errors," Journal of Finance, American Finance Association, vol. 79(3), pages 2339-2390, June.
    • Utz Weitzel & Michael Razen & Sebastian Neussüs & Michael Kirchler & Magnus Johannesson & Juergen Huber & Felix Holzmeister & Anna Dreber & Albert J. Menkveld & Javier Gil-Bazo, 2021. "Non-Standard Errors," Working Papers 1303, Barcelona School of Economics.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," IWH Discussion Papers 11/2021, Halle Institute for Economic Research (IWH).
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian T. Brownlees & Javier Gil-Baz, 2021. "Non-standard errors," Economics Working Papers 1807, Department of Economics and Business, Universitat Pompeu Fabra.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Mena, 2021. "Non-Standard Errors," Working Papers 2021:17, Lund University, Department of Economics.
    • Albert J. et al. Menkveld, 2021. "Non-Standard Errors," CESifo Working Paper Series 9453, CESifo.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Post-Print halshs-03500882, HAL.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Edwin Baidoo & Michael Frömmel & et al, 2021. "Non-Standard Errors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1032, Ghent University, Faculty of Economics and Business Administration.
    • Francesco Franzoni & Roxana Mihet & Markus Leippold & Per Ostberg & Olivier Scaillet & Norman Schürhoff & Oksana Bashchenko & Nicola Mano & Michele Pelli, 2022. "Non-Standard Errors," Swiss Finance Institute Research Paper Series 22-09, Swiss Finance Institute.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Cambridge Working Papers in Economics 2182, Faculty of Economics, University of Cambridge.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Hasse, Jean-Baptiste & e.a.,, 2023. "Non-Standard Errors," LIDAM Reprints LFIN 2023002, Université catholique de Louvain, Louvain Finance (LFIN).
    • Moinas, Sophie & Declerck, Fany & Menkveld, Albert J. & Dreber, Anna, 2023. "Non-Standard Errors," TSE Working Papers 23-1451, Toulouse School of Economics (TSE).
    • Albert Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad-Díaz & Tobias Adrian & Yacine Ai, 2024. "Nonstandard Errors," Post-Print hal-04676112, HAL.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," SAFE Working Paper Series 327, Leibniz Institute for Financial Research SAFE.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Dí­az & Menachem Abudy & Tobi, 2021. "Non-Standard Errors," Working Papers 2021-31, Faculty of Economics and Statistics, Universität Innsbruck.
    • Ferrara, Gerardo & Jurkatis, Simon, 2021. "Non-standard errors," Bank of England working papers 955, Bank of England.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03500882, HAL.
    • Ciril Bosch-Rosa & Bernhard Kassner, 2023. "Non-Standard Errors," Rationality and Competition Discussion Paper Series 385, CRC TRR 190 Rationality and Competition.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Janeway Institute Working Papers 2112, Faculty of Economics, University of Cambridge.
    • Wolff, Christian & Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüess, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-Standard Errors," CEPR Discussion Papers 16751, C.E.P.R. Discussion Papers.
    • Albert J. Menkveld & Anna Dreber & Félix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard, 2021. "Non-Standard Errors," Documents de travail du Centre d'Economie de la Sorbonne 21033, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

    Cited by:

    1. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
    2. Dreber, Anna & Johannesson, Magnus, 2023. "A framework for evaluating reproducibility and replicability in economics," Ruhr Economic Papers 1055, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. Fišar, Miloš & Greiner, Ben & Huber, Christoph & Katok, Elena & Ozkes, Ali & Collaboration, Management Science Reproducibility, 2023. "Reproducibility in Management Science," OSF Preprints mydzv, Center for Open Science.
    4. Christoph Huber & Christian König-Kersting & Matteo M. Marini, 2022. "Experimenting with Financial Professionals," Working Papers 2022-07, Faculty of Economics and Statistics, Universität Innsbruck, revised Jun 2024.
    5. Christophe Pérignon & Olivier Akmansoy & Christophe Hurlin & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johanneson & Michael Kirchler & Albert Menkveld & Michael Razen & Utz Weitzel, 2022. "Reproducibility of Empirical Results: Evidence from 1,000 Tests in Finance," Working Papers hal-03810013, HAL.
    6. Soebhag, Amar & Van Vliet, Bart & Verwijmeren, Patrick, 2024. "Non-standard errors in asset pricing: Mind your sorts," Journal of Empirical Finance, Elsevier, vol. 78(C).
    7. Fišar, Miloš & Greiner, Ben & Huber, Christoph & Katok, Elena & Ozkes, Ali & Collaboration, Management Science Reproducibility, 2023. "Reproducibility in Management Science," OSF Preprints mydzv_v1, Center for Open Science.
    8. Breznau, Nate & Rinke, Eike Mark & Wuttke, Alexander & Nguyen, Hung H. V. & Adem, Muna & Adriaans, Jule & Alvarez-Benjumea, Amalia & Andersen, Henrik K. & Auer, Daniel & Azevedo, Flavio & Bahnsen, Oke, 2022. "Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 119(44), pages 1-8.
    9. Stephen A. Gorman & Frank J. Fabozzi, 2023. "Alternative risk premium: specification noise," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 459-473, October.
    10. van Dolder, Dennie & Vandenbroucke, Jurgen, 2024. "Behavioral risk profiling: Measuring loss aversion of individual investors," Journal of Banking & Finance, Elsevier, vol. 168(C).

  2. Rafael Reisenhofer & Xandro Bayer & Nikolaus Hautsch, 2022. "HARNet: A Convolutional Neural Network for Realized Volatility Forecasting," Papers 2205.07719, arXiv.org.

    Cited by:

    1. Alessio Brini & Giacomo Toscano, 2024. "SpotV2Net: Multivariate Intraday Spot Volatility Forecasting via Vol-of-Vol-Informed Graph Attention Networks," Papers 2401.06249, arXiv.org, revised Jan 2025.
    2. Andrew J. Patton & Yasin Simsek, 2023. "Generalized Autoregressive Score Trees and Forests," Papers 2305.18991, arXiv.org.

  3. Nikolaus Hautsch & Christoph Scheuch & Stefan Voigt, 2018. "Building Trust Takes Time: Limits to Arbitrage for Blockchain-Based Assets," Papers 1812.00595, arXiv.org, revised Oct 2023.

    Cited by:

    1. Bruno Biais & Albert Menkveld & Catherine Casamatta & Christophe Bisière & Matthieu Bouvard, 2019. "Equilibrium Bitcoin Pricing," 2019 Meeting Papers 360, Society for Economic Dynamics.
    2. Brauneis, Alexander & Mestel, Roland & Riordan, Ryan & Theissen, Erik, 2022. "Bitcoin unchained: Determinants of cryptocurrency exchange liquidity," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 106-122.
    3. Divakaruni, Anantha & Zimmerman, Peter, 2023. "The Lightning Network: Turning Bitcoin into money," Finance Research Letters, Elsevier, vol. 52(C).
    4. Chen, Meichen & Qin, Cong & Zhang, Xiaoyu, 2022. "Cryptocurrency price discrepancies under uncertainty: Evidence from COVID-19 and lockdown nexus," Journal of International Money and Finance, Elsevier, vol. 124(C).

  4. Hautsch, Nikolaus & Scheuch, Christoph & Voigt, Stefan, 2018. "Limits to arbitrage in markets with stochastic settlement latency," CFS Working Paper Series 616, Center for Financial Studies (CFS).

    Cited by:

    1. Andrea Barbon & Angelo Ranaldo, 2022. "On The Quality Of Cryptocurrency Markets: Centralized Versus Decentralized Exchanges," Swiss Finance Institute Research Paper Series 22-38, Swiss Finance Institute.
    2. Saggese, Pietro & Belmonte, Alessandro & Dimitri, Nicola & Facchini, Angelo & Böhme, Rainer, 2023. "Arbitrageurs in the Bitcoin ecosystem: Evidence from user-level trading patterns in the Mt. Gox exchange platform," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 251-270.
    3. Zimmerman, Peter, 2020. "Blockchain structure and cryptocurrency prices," Bank of England working papers 855, Bank of England.

  5. Hautsch, Nikolaus & Horvath, Akos, 2017. "How effective are trading pauses?," CFS Working Paper Series 571, Center for Financial Studies (CFS).

    Cited by:

    1. Caio Machado, 2023. "Managing Overreaction During a Run," Documentos de Trabajo 574, Instituto de Economia. Pontificia Universidad Católica de Chile..
    2. Ester Félez‐Viñas & Björn Hagströmer, 2021. "Do volatility extensions improve the quality of closing call auctions?," The Financial Review, Eastern Finance Association, vol. 56(3), pages 385-406, August.
    3. Joost Bats & William Greif & Daniel Kapp, 2021. "The rise in the cross-sectoral dispersion of earnings expectations during COVID-19," Working Papers 724, DNB.
    4. Apergis, Nicholas & Lau, Chi Keung & Xu, Bing, 2023. "The impact of COVID-19 on stock market liquidity: Fresh evidence on listed Chinese firms," International Review of Financial Analysis, Elsevier, vol. 90(C).
    5. Lin, Hai & Lo, Ingrid & Qiao, Rui, 2021. "Macroeconomic news announcements and market efficiency: Evidence from the U.S. Treasury market," Journal of Banking & Finance, Elsevier, vol. 133(C).
    6. Zhang, Xiaotao & Li, Xinxian & Hao, Jing & Li, Peigong, 2023. "Price limit change and magnet effect: The role of investor attention," Finance Research Letters, Elsevier, vol. 53(C).
    7. Kyong Shik Eom & Kyung Yoon Kwon & Sung Chae La & Jong-Ho Park, 2022. "Dynamic and Static Volatility Interruptions: Evidence from the Korean Stock Markets," JRFM, MDPI, vol. 15(3), pages 1-19, February.
    8. Hautsch, Nikolaus & Noé, Michael & Zhang, S. Sarah, 2017. "The ambivalent role of high-frequency trading in turbulent market periods," CFS Working Paper Series 580, Center for Financial Studies (CFS).
    9. Wang, Steven Shuye & Xu, Kuan & Zhang, Hao, 2019. "A microstructure study of circuit breakers in the Chinese stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    10. Qi, Qingyu & Uchida, Konari & Liu, Jianlei, 2024. "Do stock swap bidders suspend their stock trading? Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    11. Hao Li & Zhisheng Li, 2022. "The effect of daily price limits on stock liquidity: Evidence from the Chinese stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(5), pages 4885-4917, December.
    12. Marjolein E. Verhulst & Philippe Debie & Stephan Hageboeck & Joost M. E. Pennings & Cornelis Gardebroek & Axel Naumann & Paul van Leeuwen & Andres A. Trujillo-Barrera & Lorenzo Moneta, 2021. "When Two Worlds Collide: Using Particle Physics Tools to Visualize the Limit Order Book," Papers 2109.04812, arXiv.org.
    13. Wong, Kin Ming & Kong, Xiao Wei & Li, Min, 2020. "The magnet effect of circuit breakers and its interactions with price limits," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    14. Sifat, Imtiaz Mohammad & Mohamad, Azhar, 2020. "A survey on the magnet effect of circuit breakers in financial markets," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 138-151.
    15. Kyong S. Eom & Kyung Y. Kwon & Jong‐Ho Park, 2021. "Effectiveness of the conditional random‐end trading mechanism on the Korea Exchange: Normal trade and Option Shock," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1545-1568, October.
    16. Aloosh, Arash & Choi, Hyung-Eun & Ouzan, Samuel, 2023. "The tail wagging the dog: How do meme stocks affect market efficiency?," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 68-78.
    17. Castro, Carlos & Agudelo, Diego A. & Preciado, Sergio, 2020. "Measuring the effectiveness of volatility auctions," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 566-581.
    18. Bats, Joost & Greif, William & Kapp, Daniel, 2022. "The rise in the cross-sectoral dispersion of earnings expectations during COVID-19," Working Paper Series 2664, European Central Bank.
    19. Sánchez Serrano Antonio, 2020. "High-Frequency Trading and Systemic Risk: A Structured Review of Findings and Policies," Review of Economics, De Gruyter, vol. 71(3), pages 169-195, December.
    20. Xinyue He & Teresa Serra, 2022. "Are price limits cooling off agricultural futures markets?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(5), pages 1724-1746, October.

  6. Hautsch, Nikolaus & Noé, Michael & Zhang, S. Sarah, 2017. "The ambivalent role of high-frequency trading in turbulent market periods," CFS Working Paper Series 580, Center for Financial Studies (CFS).

    Cited by:

    1. Bellia, Mario & Christensen, Kim & Kolokolov, Aleksey & Pelizzon, Loriana & Renò, Roberto, 2022. "Do designated market makers provide liquidity during a flash crash?," SAFE Working Paper Series 270, Leibniz Institute for Financial Research SAFE, revised 2022.
    2. Corgnet, Brice & DeSantis, Mark & Siemroth, Christoph, 2023. "Algorithmic Trading, Price Efficiency and Welfare: An Experimental Approach," Economics Discussion Papers 36273, University of Essex, Department of Economics.
    3. Yamada, Masahiro, 2022. "Profitability and liquidity provision of HFTs during large price shocks: Does relative tick size matter?," Finance Research Letters, Elsevier, vol. 46(PA).
    4. Ersan, Oguz & Simsir, Serif Aziz & Simsek, Koray D. & Hasan, Afan, 2021. "The speed of stock price adjustment to corporate announcements: Insights from Turkey," Emerging Markets Review, Elsevier, vol. 47(C).
    5. Park, Seongkyu Gilbert & Ryu, Doojin, 2019. "Speed and trading behavior in an order-driven market," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 145-164.
    6. Banerjee, Anirban & Nawn, Samarpan, 2024. "Proprietary algorithmic traders and liquidity supply during the pandemic," Finance Research Letters, Elsevier, vol. 61(C).
    7. Ekinci, Cumhur & Ersan, Oğuz, 2022. "High-frequency trading and market quality: The case of a “slightly exposed” market," International Review of Financial Analysis, Elsevier, vol. 79(C).

  7. Nikolaus Hautsch & Stefan Voigt, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty," Papers 1709.06296, arXiv.org, revised Jun 2018.

    Cited by:

    1. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
    2. Llorens-Terrazas, Jordi & Brownlees, Christian, 2023. "Projected Dynamic Conditional Correlations," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1761-1776.
    3. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    4. Hongxin Zhao & Yilun Jiang & Yizhou Yang, 2023. "Robust and Sparse Portfolio: Optimization Models and Algorithms," Mathematics, MDPI, vol. 11(24), pages 1-20, December.
    5. Hafner, Christian & Wang, Linqi, 2020. "Dynamic portfolio selection with sector-specific regularization," LIDAM Discussion Papers ISBA 2020032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Martin, Feldkircher & Thomas, Gruber & Florian, Huber, 2019. "International effects of a compression of euro area yield curves," Working Papers in Economics 2019-1, University of Salzburg.
    7. Bian, Zhicun & Liao, Yin & O’Neill, Michael & Shi, Jing & Zhang, Xueyong, 2020. "Large-scale minimum variance portfolio allocation using double regularization," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    8. Kouaissah, Noureddine, 2021. "Using multivariate stochastic dominance to enhance portfolio selection and warn of financial crises," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 480-493.
    9. Hafner, Christian M. & Wang, Linqi, 2024. "Dynamic portfolio selection with sector-specific regularization," Econometrics and Statistics, Elsevier, vol. 32(C), pages 17-33.
    10. Yukari Shirota & Basabi Chakraborty, 2022. "Amplitude-Based Time Series Data Clustering Method," Gakushuin Economic Papers, Gakushuin University, Faculty of Economics, vol. 59(2), pages 127-140.
    11. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    12. Qiao, W. & Bu, D. & Gibberd, A. & Liao, Y. & Wen, T. & Li, E., 2023. "When “time varying” volatility meets “transaction cost” in portfolio selection," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 220-237.
    13. Filippou, Ilias & Maurer, Thomas A. & Pezzo, Luca & Taylor, Mark P., 2024. "Importance of transaction costs for asset allocation in foreign exchange markets," Journal of Financial Economics, Elsevier, vol. 159(C).
    14. Moura, Guilherme V. & Santos, André A.P. & Ruiz, Esther, 2020. "Comparing high-dimensional conditional covariance matrices: Implications for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 118(C).

  8. Andersen, Torben G. & Cebiroglu, Gökhan & Hautsch, Nikolaus, 2017. "Volatility, information feedback and market microstructure noise: A tale of two regimes," CFS Working Paper Series 569, Center for Financial Studies (CFS).

    Cited by:

    1. Clinet, Simon & Potiron, Yoann, 2019. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 289-337.
    2. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.

  9. Gould, Martin D. & Hautsch, Nikolaus & Howison, Sam D. & Porter, Mason A., 2017. "Counterparty credit limits: An effective tool for mitigating counterparty risk?," CFS Working Paper Series 581, Center for Financial Studies (CFS).

    Cited by:

    1. Deimante Teresiene & Beatrice Gudaviciute, 2021. "Counterparty risk management framework: theoretical approach in COVID-19 environment," Technium Social Sciences Journal, Technium Science, vol. 17(1), pages 184-193, March.

  10. Hautsch, Nikolaus & Herrera, Rodrigo, 2015. "Multivariate dynamic intensity peaks-over-threshold models," CFS Working Paper Series 516, Center for Financial Studies (CFS).

    Cited by:

    1. Pushpa Dissanayake & Teresa Flock & Johanna Meier & Philipp Sibbertsen, 2021. "Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave Heights," Mathematics, MDPI, vol. 9(21), pages 1-33, November.
    2. Herrera, Rodrigo & González, Sergio & Clements, Adam, 2018. "Mutual excitation between OECD stock and oil markets: A conditional intensity extreme value approach," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 70-88.
    3. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.
    4. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.

  11. Markus Bibinger & Nikolaus Hautsch & Peter Malec & Markus Reiss, 2014. "Estimating the Spot Covariation of Asset Prices – Statistical Theory and Empirical Evidence," Cambridge Working Papers in Economics 1464, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Gustavo Fruet Dias & Marcelo Fernandes & Cristina Mabel Scherrer, 2019. "Price discovery in a continuous-time setting," University of East Anglia School of Economics Working Paper Series 2019-02, School of Economics, University of East Anglia, Norwich, UK..
    2. Todorov, Viktor & Zhang, Yang, 2023. "Bias reduction in spot volatility estimation from options," Journal of Econometrics, Elsevier, vol. 234(1), pages 53-81.
    3. Torben G. Andersen & Martin Thyrsgaard & Viktor Todorov, 2021. "Recalcitrant betas: Intraday variation in the cross‐sectional dispersion of systematic risk," Quantitative Economics, Econometric Society, vol. 12(2), pages 647-682, May.
    4. Bibinger, Markus & Winkelmann, Lars, 2014. "Common price and volatility jumps in noisy high-frequency data," SFB 649 Discussion Papers 2014-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    6. Hautsch, Nikolaus & Horvath, Akos, 2017. "How effective are trading pauses?," CFS Working Paper Series 571, Center for Financial Studies (CFS).
    7. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
    8. Chae-Deug, Yi, 2024. "Realized normal volatility and maximum outlying jumps in high frequency returns for Korean won–US Dollar," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    9. Kim Christensen & Ulrich Hounyo & Zhi Liu, 2024. "A nonparametric test for diurnal variation in spot correlation processes," Papers 2408.02757, arXiv.org.
    10. Markus Bibinger & Nikolaus Hautsch & Alexander Ristig, 2024. "Jump detection in high-frequency order prices," Papers 2403.00819, arXiv.org.
    11. Markus Bibinger & Christopher J. Neely & Lars Winkelmann, 2017. "Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book," Working Papers 2017-12, Federal Reserve Bank of St. Louis.
    12. Jakob Albers & Mihai Cucuringu & Sam Howison & Alexander Y. Shestopaloff, 2021. "Fragmentation, Price Formation, and Cross-Impact in Bitcoin Markets," Papers 2108.09750, arXiv.org.
    13. Mustafayeva, Konul & Wang, Weining, 2020. "Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data," IRTG 1792 Discussion Papers 2020-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    14. Žikica Lukić & Bojana Milošević, 2024. "A novel two-sample test within the space of symmetric positive definite matrix distributions and its application in finance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(5), pages 797-820, October.
    15. Bibinger, Markus & Madensoy, Mehmet, 2019. "Change-point inference on volatility in noisy Itô semimartingales," Stochastic Processes and their Applications, Elsevier, vol. 129(12), pages 4878-4925.
    16. Jacod, Jean & Mykland, Per A., 2015. "Microstructure noise in the continuous case: Approximate efficiency of the adaptive pre-averaging method," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2910-2936.
    17. Rui Da & Dacheng Xiu, 2021. "When Moving‐Average Models Meet High‐Frequency Data: Uniform Inference on Volatility," Econometrica, Econometric Society, vol. 89(6), pages 2787-2825, November.
    18. Zhang, Congshan & Li, Jia & Bollerslev, Tim, 2022. "Occupation density estimation for noisy high-frequency data," Journal of Econometrics, Elsevier, vol. 227(1), pages 189-211.
    19. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
    20. Dalderop, Jeroen, 2020. "Nonparametric filtering of conditional state-price densities," Journal of Econometrics, Elsevier, vol. 214(2), pages 295-325.
    21. Richard Y. Chen, 2019. "The Fourier Transform Method for Volatility Functional Inference by Asynchronous Observations," Papers 1911.02205, arXiv.org.
    22. Yucheng Sun, 2024. "Testing for jumps with robust spot volatility estimators," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 78(1), pages 79-104, February.
    23. Jir^o Akahori & Nien-Lin Liu & Maria Elvira Mancino & Tommaso Mariotti & Yukie Yasuda, 2023. "Symmetric positive semi-definite Fourier estimator of instantaneous variance-covariance matrix," Papers 2304.04372, arXiv.org.

  12. Hautsch, Nikolaus & Okhrin, Ostap & Ristig, Alexander, 2014. "Efficient iterative maximum likelihood estimation of high-parameterized time series models," SFB 649 Discussion Papers 2014-010, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    2. Mat'uv{s} Maciak & Ostap Okhrin & Michal Pev{s}ta, 2018. "Dynamic and granular loss reserving with copulae," Papers 1801.01792, arXiv.org.

  13. Betz, Frank & Hautsch, Nikolaus & Peltonen, Tuomas A. & Schienle, Melanie, 2014. "Systemic risk spillovers in the European banking and sovereign network," CFS Working Paper Series 467, Center for Financial Studies (CFS).

    Cited by:

    1. Huang, Shoujun & Bossman, Ahmed & Gubareva, Mariya & Teplova, Tamara, 2024. "International transmission of shocks and African forex markets," Energy Economics, Elsevier, vol. 131(C).
    2. Syed Jawad Hussain Shahzad & Thi Hong Van Hoang & Jose Arreola-Hernandez, 2019. "Risk spillovers between large banks and the financial sector: Asymmetric evidence from Europe," Post-Print hal-02129104, HAL.
    3. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Erick Treviño Aguilar, 2020. "The interdependency structure in the Mexican stock exchange: A network approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-31, October.
    5. Yousaf, Imran & Youssef, Manel & Goodell, John W., 2022. "Quantile connectedness between sentiment and financial markets: Evidence from the S&P 500 twitter sentiment index," International Review of Financial Analysis, Elsevier, vol. 83(C).
    6. Chao, Xiangrui & Ran, Qin & Chen, Jia & Li, Tie & Qian, Qian & Ergu, Daji, 2022. "Regulatory technology (Reg-Tech) in financial stability supervision: Taxonomy, key methods, applications and future directions," International Review of Financial Analysis, Elsevier, vol. 80(C).
    7. Borjigin, Sumuya & Gao, Ting & Sun, Yafei & An, Biao, 2020. "For evil news rides fast, while good news baits later?—A network based analysis in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    8. Name 1 Dieter Wang Email 1 & Iman (I.P.P.) van Lelyveld & Julia (J.) Schaumburg, 2018. "Do information contagion and business model similarities explain bank credit risk commonalities?," Tinbergen Institute Discussion Papers 18-100/IV, Tinbergen Institute.
    9. Billah, Mabruk & Karim, Sitara & Naeem, Muhammad Abubakr & Vigne, Samuel A., 2022. "Return and volatility spillovers between energy and BRIC markets: Evidence from quantile connectedness," Research in International Business and Finance, Elsevier, vol. 62(C).
    10. Costola, Michele & Lorusso, Marco, 2021. "Spillovers among Energy Commodities and the Russian Stock Market," MPRA Paper 108990, University Library of Munich, Germany.
    11. Miao He & Yanhong Guo, 2022. "Systemic Risk Contributions of Financial Institutions during the Stock Market Crash in China," Sustainability, MDPI, vol. 14(9), pages 1-14, April.
    12. Foglia, Matteo & Angelini, Eliana, 2020. "The diabolical sovereigns/banks risk loop: A VAR quantile design," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    13. Ali Namaki & Jamshid Ardalankia & Reza Raei & Leila Hedayatifar & Ali Hosseiny & Emmanuel Haven & G. Reza Jafari, 2020. "Analysis of the Global Banking Network by Random Matrix Theory," Papers 2007.14447, arXiv.org.
    14. Arreola Hernandez, Jose & Kang, Sang Hoon & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2020. "Spillovers and diversification potential of bank equity returns from developed and emerging America," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    15. Sheikh, Umaid A. & Asadi, Mehrad & Roubaud, David & Hammoudeh, Shawkat, 2024. "Global uncertainties and Australian financial markets: Quantile time-frequency connectedness," International Review of Financial Analysis, Elsevier, vol. 92(C).
    16. Mokni, Khaled & Al-Shboul, Mohammed & Assaf, Ata, 2021. "Economic policy uncertainty and dynamic spillover among precious metals under market conditions: Does COVID-19 have any effects?," Resources Policy, Elsevier, vol. 74(C).
    17. Moratis, Georgios & Sakellaris, Plutarchos, 2021. "Measuring the systemic importance of banks," Journal of Financial Stability, Elsevier, vol. 54(C).
    18. Foglia, Matteo & Di Tommaso, Caterina & Wang, Gang-Jin & Pacelli, Vincenzo, 2024. "Interconnectedness between stock and credit markets: The role of European G-SIBs in a multilayer perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    19. Huang, Shoujun & Gubareva, Mariya & Teplova, Tamara & Bossman, Ahmed, 2024. "African forex markets: Modeling their predictability and the asymmetric effects of oil and geopolitical risk," Energy Economics, Elsevier, vol. 136(C).
    20. Zhu, Bo & Liu, Jiahao & Lin, Renda & Chevallier, Julien, 2021. "Cross-border systemic risk spillovers in the global oil system: Does the oil trade pattern matter?," Energy Economics, Elsevier, vol. 101(C).
    21. Apostolakis, George N. & Floros, Christos & Giannellis, Nikolaos, 2022. "On bank return and volatility spillovers: Identifying transmitters and receivers during crisis periods," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 156-176.
    22. Khalfaoui, Rabeh & Hammoudeh, Shawkat & Rehman, Mohd Ziaur, 2023. "Spillovers and connectedness among BRICS stock markets, cryptocurrencies, and uncertainty: Evidence from the quantile vector autoregression network," Emerging Markets Review, Elsevier, vol. 54(C).
    23. Brownlees, Christian & Hans, Christina & Nualart, Eulalia, 2021. "Bank credit risk networks: Evidence from the Eurozone," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 585-599.
    24. Foglia, Matteo & Addi, Abdelhamid & Angelini, Eliana, 2022. "The Eurozone banking sector in the time of COVID-19: Measuring volatility connectedness," Global Finance Journal, Elsevier, vol. 51(C).
    25. Christian Gross & Pierre L. Siklos, 2019. "Analyzing credit risk transmission to the non-financial sector in Europe: A network approach," CAMA Working Papers 2019-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    26. Buch, Claudia M. & Koetter, Michael & Ohls, Jana, 2016. "Banks and sovereign risk: A granular view," Journal of Financial Stability, Elsevier, vol. 25(C), pages 1-15.
    27. Deng, Yang & Zhang, Ziqing & Zhu, Li, 2021. "A model-based index for systemic risk contribution measurement in financial networks," Economic Modelling, Elsevier, vol. 95(C), pages 35-48.
    28. Wen, Fenghua & Wang, Kangsheng & Zeng, Aiqing, 2024. "Return spillover across the carbon market and financial markets: A quantile-based approach," Research in International Business and Finance, Elsevier, vol. 69(C).
    29. Clancy, Daragh & Gabriele, Carmine & Žigraiová, Diana, 2022. "Sovereign bond market spillovers from crisis-time developments in Greece," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    30. Härdle, Wolfgang Karl & Wang, Weining & Yu, Lining, 2016. "TENET: Tail-Event driven NETwork risk," Journal of Econometrics, Elsevier, vol. 192(2), pages 499-513.
    31. Linh H. Nguyen & Linh X. D. Nguyen & Linzhi Tan, 2021. "Tail risk connectedness between US industries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3624-3650, July.
    32. Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2022. "Assessing the impact of policy and regulation interventions in European sovereign credit risk networks: What worked best?," Journal of International Economics, Elsevier, vol. 139(C).
    33. Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2023. "Quantile spillovers and connectedness analysis between oil and African stock markets," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 60-83.
    34. Cao, Guangxi & Xie, Wenhao, 2022. "Detrended multiple moving average cross-correlation analysis and its application in the correlation measurement of stock market in Shanghai, Shenzhen, and Hong Kong," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    35. G. Chiesa & J. M. Mansilla-Fern ndez, 2018. "Non-Performing Loans, Cost of Capital, and Lending Supply: Lessons from the Eurozone Banking Crisi," Working Papers wp1124, Dipartimento Scienze Economiche, Universita' di Bologna.
    36. Nandita Bhattacharjee & Ambika Prasad Pati, 2023. "Exploring Systemic Risk Measurement Issues in Shadow Banks: A Case of an Emerging Economy," South Asian Journal of Macroeconomics and Public Finance, , vol. 12(2), pages 186-217, December.
    37. Y'erali Gandica & Sophie B'ereau & Jean-Yves Gnabo, 2019. "A multilevel analysis to systemic exposure: insights from local and system-wide information," Papers 1910.08611, arXiv.org.
    38. Bellavite Pellegrini, Carlo & Meoli, Michele & Urga, Giovanni, 2017. "Money market funds, shadow banking and systemic risk in United Kingdom," Finance Research Letters, Elsevier, vol. 21(C), pages 163-171.
    39. Su, Xianfang, 2020. "Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    40. Shouwei Li & Shihang Wen, 2017. "Multiplex Networks of the Guarantee Market: Evidence from China," Complexity, Hindawi, vol. 2017, pages 1-7, July.
    41. Chen, Bin-xia & Sun, Yan-lin, 2024. "Financial market connectedness between the U.S. and China: A new perspective based on non-linear causality networks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    42. Naeem, Muhammad Abubakr & Yousaf, Imran & Karim, Sitara & Yarovaya, Larisa & Ali, Shoaib, 2023. "Tail-event driven NETwork dependence in emerging markets," Emerging Markets Review, Elsevier, vol. 55(C).
    43. Ben Amor, Souhir & Althof, Michael & Härdle, Wolfgang Karl, 2022. "Financial Risk Meter for emerging markets," Research in International Business and Finance, Elsevier, vol. 60(C).
    44. Zhang, Xingmin & Zhang, Shuai & Lu, Liping, 2022. "The banking instability and climate change: Evidence from China," Energy Economics, Elsevier, vol. 106(C).
    45. Simone Varotto & Lei Zhao, 2014. "Systemic Risk and Bank Size," ICMA Centre Discussion Papers in Finance icma-dp2014-17, Henley Business School, University of Reading.
    46. Beibei Zhang & Xuemei Xie & Chunmei Li, 2023. "How Connected Is China’s Systemic Financial Risk Contagion Network?—A Dynamic Network Perspective Analysis," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    47. Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: a network analysis," ESRB Working Paper Series 90, European Systemic Risk Board.
    48. Sophie Béreau & Nicolas Debarsy & Cyrille Dossougoin & Jean-Yves Gnabo, 2022. "Contagion in the Banking Industry: a Robust-to-Endogeneity Analysis," Working Papers halshs-03513049, HAL.
    49. Lim, Seo-Yeon & Choi, Sun-Yong, 2024. "Dynamic credit risk transmissions among global major industries: Evidence from the TVP-VAR spillover approach," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    50. Hué, Sullivan & Lucotte, Yannick & Tokpavi, Sessi, 2019. "Measuring network systemic risk contributions: A leave-one-out approach," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 86-114.
    51. Liu, Jiahao & Shen, Wenyu, 2024. "Financial instability in Europe: Does geopolitical risk from proximate countries and trading partners matter?," Finance Research Letters, Elsevier, vol. 66(C).
    52. Liao, Yin & Pan, Zheyao, 2022. "Extreme risk connectedness among global major financial institutions: Links to globalization and emerging market fear," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    53. Nekhili, Ramzi & Foglia, Matteo & Bouri, Elie, 2023. "European bank credit risk transmission during the credit Suisse collapse," Finance Research Letters, Elsevier, vol. 58(PB).
    54. Abbassi, Puriya & Brownlees, Christian & Hans, Christina & Podlich, Natalia, 2016. "Credit risk interconnectedness: What does the market really know?," Discussion Papers 09/2016, Deutsche Bundesbank.
    55. Pham, Thach N. & Powell, Robert & Bannigidadmath, Deepa, 2024. "Tail risk network analysis of Asian banks," Global Finance Journal, Elsevier, vol. 62(C).
    56. Jingyi TIAN & Jun NAGAYASU, 2024. "AI and Financial Systemic Risk in the Global Market," TUPD Discussion Papers 55, Graduate School of Economics and Management, Tohoku University.
    57. Sullivan HUE & Yannick LUCOTTE & Sessi TOKPAVI, 2018. "Measuring Network Systemic Risk Contributions: A Leave-one-out Approach," LEO Working Papers / DR LEO 2608, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    58. Dai, Zhifeng & Zhang, Xiaotong & Yin, Zhujia, 2023. "Extreme time-varying spillovers between high carbon emission stocks, green bond and crude oil: Evidence from a quantile-based analysis," Energy Economics, Elsevier, vol. 118(C).
    59. Foglia, Matteo & Addi, Abdelhamid & Wang, Gang-Jin & Angelini, Eliana, 2022. "Bearish Vs Bullish risk network: A Eurozone financial system analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    60. Jose Arreola Hernandez & Sang Hoon Kang & Seong‐Min Yoon, 2022. "Interdependence and portfolio optimisation of bank equity returns from developed and emerging Europe," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 678-696, January.
    61. Dong, Xiyong & Yoon, Seong-Min, 2023. "Effect of weather and environmental attentions on financial system risks: Evidence from Chinese high- and low-carbon assets," Energy Economics, Elsevier, vol. 121(C).
    62. Nguyen, Linh Hoang & Lambe, Brendan John, 2021. "International tail risk connectedness: Network and determinants," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    63. Chen, Jinyu & Liang, Zhipeng & Ding, Qian & Liu, Zhenhua, 2022. "Extreme spillovers among fossil energy, clean energy, and metals markets: Evidence from a quantile-based analysis," Energy Economics, Elsevier, vol. 107(C).
    64. Wu, Shan & Liu, Yilong & Song, Ziyu & Zhou, Yuqin & Guo, Wenjing, 2024. "Network structure, dynamic evolution and block characteristics of sovereign debt risk: The global evidence," Research in International Business and Finance, Elsevier, vol. 72(PA).
    65. Saeed, Tareq & Bouri, Elie & Alsulami, Hamed, 2021. "Extreme return connectedness and its determinants between clean/green and dirty energy investments," Energy Economics, Elsevier, vol. 96(C).
    66. Arnold, Ivo J.M. & Soederhuizen, Beau, 2018. "Sovereign bond holdings and monetary policy operations in the euro area," Journal of Policy Modeling, Elsevier, vol. 40(6), pages 1243-1254.
    67. Nistor Simona, 2017. "Banks’ Vulnerability and Financial Openness across Central and Eastern Europe," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, vol. 62(3), pages 47-66, December.
    68. Tomohiro Ando & Matthew Greenwood-Nimmo & Yongcheol Shin, 2022. "Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks," Management Science, INFORMS, vol. 68(4), pages 2401-2431, April.
    69. Liu, Bing-Yue & Fan, Ying & Ji, Qiang & Hussain, Nazim, 2022. "High-dimensional CoVaR network connectedness for measuring conditional financial contagion and risk spillovers from oil markets to the G20 stock system," Energy Economics, Elsevier, vol. 105(C).
    70. Sudarshan Kumar & Tiziana Di Matteo & Anindya S. Chakrabarti, 2020. "Disentangling shock diffusion on complex networks: Identification through graph planarity," Papers 2001.01518, arXiv.org.
    71. Chen, Yan & Wang, Gang-Jin & Zhu, You & Xie, Chi & Uddin, Gazi Salah, 2023. "Quantile connectedness and the determinants between FinTech and traditional financial institutions: Evidence from China," Global Finance Journal, Elsevier, vol. 58(C).
    72. Foglia, Matteo & Angelini, Eliana, 2020. "From me to you: Measuring connectedness between Eurozone financial institutions," Research in International Business and Finance, Elsevier, vol. 54(C).
    73. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2020. "Extreme spillovers across Asian-Pacific currencies: A quantile-based analysis," International Review of Financial Analysis, Elsevier, vol. 72(C).
    74. Bouri, Elie & Saeed, Tareq & Vo, Xuan Vinh & Roubaud, David, 2021. "Quantile connectedness in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    75. Jose Arreola Hernandez & Sang Hoon Kang & Ron P. McIver & Seong-Min Yoon, 2021. "Network Interdependence and Optimization of Bank Portfolios from Developed and Emerging Asia Pacific Countries," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 613-647, December.
    76. Chen, Bin-xia & Sun, Yan-lin, 2023. "Extreme risk contagion between international crude oil and China's energy-intensive sectors: New evidence from quantile Granger causality and spillover methods," Energy, Elsevier, vol. 285(C).
    77. Li, Wenwei & Hommel, Ulrich & Paterlini, Sandra, 2018. "Network topology and systemic risk: Evidence from the Euro Stoxx market," Finance Research Letters, Elsevier, vol. 27(C), pages 105-112.
    78. Huang, Zhigang & Zhang, Weilan, 2024. "Exploring the Spillover effects of tail risk fluctuations in the RMB exchange rate—The time-frequency and quantile connectivity perspective," Research in International Business and Finance, Elsevier, vol. 72(PB).
    79. Sui, Xin & Li, Liang & Chen, Xiaohui, 2020. "Risk contagion caused by interactions between credit and guarantee networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    80. Zhang, Xingmin & Zhang, Shuai, 2021. "Optimal time-varying tail risk network with a rolling window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    81. Nadal De Simone, Francisco, 2021. "Measuring the deadly embrace: Systemic and sovereign risks," Research in International Business and Finance, Elsevier, vol. 56(C).
    82. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.

  14. Hautsch, Nikolaus & Okhrin, Ostap & Ristig, Alexander, 2014. "Efficient iterative maximum likelihood estimation of high-parameterized time series models," SFB 649 Discussion Papers 2014-010, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    2. Mat'uv{s} Maciak & Ostap Okhrin & Michal Pev{s}ta, 2018. "Dynamic and granular loss reserving with copulae," Papers 1801.01792, arXiv.org.

  15. Bibinger, Markus & Hautsch, Nikolaus & Malec, Peter & Reiss, Markus, 2014. "Estimating the spot covariation of asset prices: Statistical theory and empirical evidence," SFB 649 Discussion Papers 2014-055, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Gustavo Fruet Dias & Marcelo Fernandes & Cristina Mabel Scherrer, 2019. "Price discovery in a continuous-time setting," University of East Anglia School of Economics Working Paper Series 2019-02, School of Economics, University of East Anglia, Norwich, UK..
    2. Todorov, Viktor & Zhang, Yang, 2023. "Bias reduction in spot volatility estimation from options," Journal of Econometrics, Elsevier, vol. 234(1), pages 53-81.
    3. Torben G. Andersen & Martin Thyrsgaard & Viktor Todorov, 2021. "Recalcitrant betas: Intraday variation in the cross‐sectional dispersion of systematic risk," Quantitative Economics, Econometric Society, vol. 12(2), pages 647-682, May.
    4. Bibinger, Markus & Winkelmann, Lars, 2014. "Common price and volatility jumps in noisy high-frequency data," SFB 649 Discussion Papers 2014-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    6. Hautsch, Nikolaus & Horvath, Akos, 2017. "How effective are trading pauses?," CFS Working Paper Series 571, Center for Financial Studies (CFS).
    7. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
    8. Chae-Deug, Yi, 2024. "Realized normal volatility and maximum outlying jumps in high frequency returns for Korean won–US Dollar," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    9. Kim Christensen & Ulrich Hounyo & Zhi Liu, 2024. "A nonparametric test for diurnal variation in spot correlation processes," Papers 2408.02757, arXiv.org.
    10. Markus Bibinger & Nikolaus Hautsch & Alexander Ristig, 2024. "Jump detection in high-frequency order prices," Papers 2403.00819, arXiv.org.
    11. Markus Bibinger & Christopher J. Neely & Lars Winkelmann, 2017. "Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book," Working Papers 2017-12, Federal Reserve Bank of St. Louis.
    12. Jakob Albers & Mihai Cucuringu & Sam Howison & Alexander Y. Shestopaloff, 2021. "Fragmentation, Price Formation, and Cross-Impact in Bitcoin Markets," Papers 2108.09750, arXiv.org.
    13. Mustafayeva, Konul & Wang, Weining, 2020. "Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data," IRTG 1792 Discussion Papers 2020-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    14. Žikica Lukić & Bojana Milošević, 2024. "A novel two-sample test within the space of symmetric positive definite matrix distributions and its application in finance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(5), pages 797-820, October.
    15. Bibinger, Markus & Madensoy, Mehmet, 2019. "Change-point inference on volatility in noisy Itô semimartingales," Stochastic Processes and their Applications, Elsevier, vol. 129(12), pages 4878-4925.
    16. Jacod, Jean & Mykland, Per A., 2015. "Microstructure noise in the continuous case: Approximate efficiency of the adaptive pre-averaging method," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2910-2936.
    17. Rui Da & Dacheng Xiu, 2021. "When Moving‐Average Models Meet High‐Frequency Data: Uniform Inference on Volatility," Econometrica, Econometric Society, vol. 89(6), pages 2787-2825, November.
    18. Zhang, Congshan & Li, Jia & Bollerslev, Tim, 2022. "Occupation density estimation for noisy high-frequency data," Journal of Econometrics, Elsevier, vol. 227(1), pages 189-211.
    19. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
    20. Dalderop, Jeroen, 2020. "Nonparametric filtering of conditional state-price densities," Journal of Econometrics, Elsevier, vol. 214(2), pages 295-325.
    21. Richard Y. Chen, 2019. "The Fourier Transform Method for Volatility Functional Inference by Asynchronous Observations," Papers 1911.02205, arXiv.org.
    22. Yucheng Sun, 2024. "Testing for jumps with robust spot volatility estimators," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 78(1), pages 79-104, February.
    23. Jir^o Akahori & Nien-Lin Liu & Maria Elvira Mancino & Tommaso Mariotti & Yukie Yasuda, 2023. "Symmetric positive semi-definite Fourier estimator of instantaneous variance-covariance matrix," Papers 2304.04372, arXiv.org.

  16. Hautsch, Nikolaus & Kyj, Lada. M. & Malec, Peter, 2013. "Do high-frequency data improve high-dimensional portfolio allocations?," SFB 649 Discussion Papers 2013-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    3. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    4. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    5. Dong Hwan Oh & Andrew J. Patton, 2015. "High-Dimensional Copula-Based Distributions with Mixed Frequency Data," Finance and Economics Discussion Series 2015-50, Board of Governors of the Federal Reserve System (U.S.).
    6. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    7. Llorens-Terrazas, Jordi & Brownlees, Christian, 2023. "Projected Dynamic Conditional Correlations," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1761-1776.
    8. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    9. Taras Bodnar & Nestor Parolya & Erik Thorsen, 2021. "Dynamic Shrinkage Estimation of the High-Dimensional Minimum-Variance Portfolio," Papers 2106.02131, arXiv.org, revised Nov 2021.
    10. Bodnar, Taras & Lindholm, Mathias & Niklasson, Vilhelm & Thorsén, Erik, 2022. "Bayesian portfolio selection using VaR and CVaR," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    11. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    12. Arumugam, Devika, 2023. "Algorithmic trading: Intraday profitability and trading behavior," Economic Modelling, Elsevier, vol. 128(C).
    13. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
    14. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    15. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto Calogero, 2017. "Estimation and model-based combination of causality networks," SAFE Working Paper Series 165, Leibniz Institute for Financial Research SAFE.
    16. Cui, Tianxiang & Du, Nanjiang & Yang, Xiaoying & Ding, Shusheng, 2024. "Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    17. Taras Bodnar & Mathias Lindholm & Vilhelm Niklasson & Erik Thors'en, 2020. "Bayesian Quantile-Based Portfolio Selection," Papers 2012.01819, arXiv.org.
    18. Weigand, Roland, 2014. "Matrix Box-Cox Models for Multivariate Realized Volatility," University of Regensburg Working Papers in Business, Economics and Management Information Systems 478, University of Regensburg, Department of Economics.
    19. Luo, Jiawen & Chen, Langnan, 2020. "Realized volatility forecast with the Bayesian random compressed multivariate HAR model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 781-799.
    20. Qu, Hui & Zhang, Yi, 2022. "Asymmetric multivariate HAR models for realized covariance matrix: A study based on volatility timing strategies," Economic Modelling, Elsevier, vol. 106(C).
    21. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    22. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    23. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    24. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
    25. Yu-Sheng Lai, 2018. "Dynamic hedging with futures: a copula-based GARCH model with high-frequency data," Review of Derivatives Research, Springer, vol. 21(3), pages 307-329, October.
    26. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
    27. Laurent A. F. Callot & Anders B. Kock & Marcelo C. Medeiros, 2014. "Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice," CREATES Research Papers 2014-42, Department of Economics and Business Economics, Aarhus University.
    28. Xiangyu Cui & Xuan Zhang, 2021. "Index tracking strategy based on mixed-frequency financial data," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-15, April.
    29. Timo Dimitriadis & Yannick Hoga, 2022. "Dynamic CoVaR Modeling and Estimation," Papers 2206.14275, arXiv.org, revised Jan 2025.
    30. Lai, Yu-Sheng, 2023. "Economic evaluation of dynamic hedging strategies using high-frequency data," Finance Research Letters, Elsevier, vol. 57(C).
    31. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    32. Alfelt, Gustav & Bodnar, Taras & Javed, Farrukh & Tyrcha, Joanna, 2020. "Singular conditional autoregressive Wishart model for realized covariance matrices," Working Papers 2021:1, Örebro University, School of Business.
    33. Wang, Jiazhen & Jiang, Yuexiang & Zhu, Yanjian & Yu, Jing, 2020. "Prediction of volatility based on realized-GARCH-kernel-type models: Evidence from China and the U.S," Economic Modelling, Elsevier, vol. 91(C), pages 428-444.
    34. Laura Capera Romero & Anne Opschoor, 2024. "Realized Variances vs. Correlations: Unlocking the Gains in Multivariate Volatility Forecasting," Tinbergen Institute Discussion Papers 24-059/III, Tinbergen Institute.
    35. Vladim'ir Hol'y & Petra Tomanov'a, 2020. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Papers 2003.13062, arXiv.org, revised Dec 2021.

  17. Bibinger, Markus & Hautsch, Nikolaus & Malec, Peter & Reiss, Markus, 2013. "Estimating the quadratic covariation matrix from noisy observations: Local method of moments and efficiency," SFB 649 Discussion Papers 2013-017, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Bibinger, Markus & Hautsch, Nikolaus & Malec, Peter & Reiss, Markus, 2014. "Estimating the spot covariation of asset prices: Statistical theory and empirical evidence," SFB 649 Discussion Papers 2014-055, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    3. Donggyu Kim & Xinyu Song & Yazhen Wang, 2020. "Unified Discrete-Time Factor Stochastic Volatility and Continuous-Time Ito Models for Combining Inference Based on Low-Frequency and High-Frequency," Papers 2006.12039, arXiv.org.
    4. Altmeyer, Randolf & Bibinger, Markus, 2014. "Functional stable limit theorems for efficient spectral covolatility estimators," SFB 649 Discussion Papers 2014-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Altmeyer, Randolf & Bibinger, Markus, 2015. "Functional stable limit theorems for quasi-efficient spectral covolatility estimators," Stochastic Processes and their Applications, Elsevier, vol. 125(12), pages 4556-4600.
    6. Richard Y. Chen & Per A. Mykland, 2015. "Model-Free Approaches to Discern Non-Stationary Microstructure Noise and Time-Varying Liquidity in High-Frequency Data," Papers 1512.06159, arXiv.org, revised Oct 2018.
    7. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
    8. Bibinger, Markus & Winkelmann, Lars, 2013. "Econometrics of co-jumps in high-frequency data with noise," SFB 649 Discussion Papers 2013-021, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Bibinger, Markus & Winkelmann, Lars, 2015. "Econometrics of co-jumps in high-frequency data with noise," Journal of Econometrics, Elsevier, vol. 184(2), pages 361-378.
    10. Richard Y. Chen, 2018. "Inference for Volatility Functionals of Multivariate It\^o Semimartingales Observed with Jump and Noise," Papers 1810.04725, arXiv.org, revised Nov 2019.
    11. Bibinger, Markus & Winkelmann, Lars, 2014. "Common price and volatility jumps in noisy high-frequency data," SFB 649 Discussion Papers 2014-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
    13. Hautsch, Nikolaus & Horvath, Akos, 2017. "How effective are trading pauses?," CFS Working Paper Series 571, Center for Financial Studies (CFS).
    14. Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
    15. Ogihara, Teppei & Yoshida, Nakahiro, 2014. "Quasi-likelihood analysis for nonsynchronously observed diffusion processes," Stochastic Processes and their Applications, Elsevier, vol. 124(9), pages 2954-3008.
    16. Markus Bibinger & Christopher J. Neely & Lars Winkelmann, 2017. "Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book," Working Papers 2017-12, Federal Reserve Bank of St. Louis.
    17. Jean Jacod, 2019. "Estimation of volatility in a high-frequency setting: a short review," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 351-385, December.
    18. Andersen, Torben G. & Cebiroglu, Gökhan & Hautsch, Nikolaus, 2017. "Volatility, information feedback and market microstructure noise: A tale of two regimes," CFS Working Paper Series 569, Center for Financial Studies (CFS).
    19. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    20. Jianqing Fan & Alex Furger & Dacheng Xiu, 2016. "Incorporating Global Industrial Classification Standard Into Portfolio Allocation: A Simple Factor-Based Large Covariance Matrix Estimator With High-Frequency Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 489-503, October.
    21. Fan, Jianqing & Kim, Donggyu, 2019. "Structured volatility matrix estimation for non-synchronized high-frequency financial data," Journal of Econometrics, Elsevier, vol. 209(1), pages 61-78.
    22. Marcio Laurini & Alberto Ohashi, 2014. "A Noisy Principal Component Analysis for Forward Rate Curves," Papers 1408.6279, arXiv.org.
    23. Yuta Koike, 2017. "Time endogeneity and an optimal weight function in pre-averaging covariance estimation," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 15-56, April.
    24. Reiß, Markus & Todorov, Viktor & Tauchen, George, 2015. "Nonparametric test for a constant beta between Itô semi-martingales based on high-frequency data," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2955-2988.
    25. Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
    26. Lars Winkelmann & Markus Bibinger & Tobias Linzert, 2016. "ECB Monetary Policy Surprises: Identification Through Cojumps in Interest Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(4), pages 613-629, June.
    27. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    28. Linzert, Tobias & Winkelmann, Lars & Bibinger, Markus, 2014. "ECB monetary policy surprises: identification through cojumps in interest rates," Working Paper Series 1674, European Central Bank.
    29. Alberto Ohashi & Alexandre B Simas, 2015. "Principal Components Analysis for Semimartingales and Stochastic PDE," Papers 1503.05909, arXiv.org, revised Mar 2016.

  18. Hautsch, Nikolaus & Kyj, Lada. M. & Malec, Peter, 2013. "Do high-frequency data improve high-dimensional portfolio allocations?," SFB 649 Discussion Papers 2013-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    3. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    4. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    5. Dong Hwan Oh & Andrew J. Patton, 2015. "High-Dimensional Copula-Based Distributions with Mixed Frequency Data," Finance and Economics Discussion Series 2015-50, Board of Governors of the Federal Reserve System (U.S.).
    6. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    7. Llorens-Terrazas, Jordi & Brownlees, Christian, 2023. "Projected Dynamic Conditional Correlations," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1761-1776.
    8. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    9. Taras Bodnar & Nestor Parolya & Erik Thorsen, 2021. "Dynamic Shrinkage Estimation of the High-Dimensional Minimum-Variance Portfolio," Papers 2106.02131, arXiv.org, revised Nov 2021.
    10. Bodnar, Taras & Lindholm, Mathias & Niklasson, Vilhelm & Thorsén, Erik, 2022. "Bayesian portfolio selection using VaR and CVaR," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    11. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    12. Arumugam, Devika, 2023. "Algorithmic trading: Intraday profitability and trading behavior," Economic Modelling, Elsevier, vol. 128(C).
    13. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
    14. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    15. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto Calogero, 2017. "Estimation and model-based combination of causality networks," SAFE Working Paper Series 165, Leibniz Institute for Financial Research SAFE.
    16. Cui, Tianxiang & Du, Nanjiang & Yang, Xiaoying & Ding, Shusheng, 2024. "Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    17. Taras Bodnar & Mathias Lindholm & Vilhelm Niklasson & Erik Thors'en, 2020. "Bayesian Quantile-Based Portfolio Selection," Papers 2012.01819, arXiv.org.
    18. Weigand, Roland, 2014. "Matrix Box-Cox Models for Multivariate Realized Volatility," University of Regensburg Working Papers in Business, Economics and Management Information Systems 478, University of Regensburg, Department of Economics.
    19. Luo, Jiawen & Chen, Langnan, 2020. "Realized volatility forecast with the Bayesian random compressed multivariate HAR model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 781-799.
    20. Qu, Hui & Zhang, Yi, 2022. "Asymmetric multivariate HAR models for realized covariance matrix: A study based on volatility timing strategies," Economic Modelling, Elsevier, vol. 106(C).
    21. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    22. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    23. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    24. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
    25. Yu-Sheng Lai, 2018. "Dynamic hedging with futures: a copula-based GARCH model with high-frequency data," Review of Derivatives Research, Springer, vol. 21(3), pages 307-329, October.
    26. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
    27. Laurent A. F. Callot & Anders B. Kock & Marcelo C. Medeiros, 2014. "Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice," CREATES Research Papers 2014-42, Department of Economics and Business Economics, Aarhus University.
    28. Xiangyu Cui & Xuan Zhang, 2021. "Index tracking strategy based on mixed-frequency financial data," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-15, April.
    29. Timo Dimitriadis & Yannick Hoga, 2022. "Dynamic CoVaR Modeling and Estimation," Papers 2206.14275, arXiv.org, revised Jan 2025.
    30. Lai, Yu-Sheng, 2023. "Economic evaluation of dynamic hedging strategies using high-frequency data," Finance Research Letters, Elsevier, vol. 57(C).
    31. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    32. Alfelt, Gustav & Bodnar, Taras & Javed, Farrukh & Tyrcha, Joanna, 2020. "Singular conditional autoregressive Wishart model for realized covariance matrices," Working Papers 2021:1, Örebro University, School of Business.
    33. Wang, Jiazhen & Jiang, Yuexiang & Zhu, Yanjian & Yu, Jing, 2020. "Prediction of volatility based on realized-GARCH-kernel-type models: Evidence from China and the U.S," Economic Modelling, Elsevier, vol. 91(C), pages 428-444.
    34. Laura Capera Romero & Anne Opschoor, 2024. "Realized Variances vs. Correlations: Unlocking the Gains in Multivariate Volatility Forecasting," Tinbergen Institute Discussion Papers 24-059/III, Tinbergen Institute.
    35. Vladim'ir Hol'y & Petra Tomanov'a, 2020. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Papers 2003.13062, arXiv.org, revised Dec 2021.

  19. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).

    Cited by:

    1. Hautsch, Nikolaus & Okhrin, Ostap & Ristig, Alexander, 2014. "Efficient iterative maximum likelihood estimation of high-parameterized time series models," SFB 649 Discussion Papers 2014-010, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  20. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Forecasting systemic impact in financial networks," SFB 649 Discussion Papers 2013-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Robin L. Lumsdaine & Daniel N. Rockmore & Nicholas Foti & Gregory Leibon & J. Doyne Farmer, 2015. "The Intrafirm Complexity of Systemically Important Financial Institutions," Papers 1505.02305, arXiv.org.
    2. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Matteo Barigozzi & Christian Brownlees, 2015. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona School of Economics.
    4. van de Leur, Michiel C.W. & Lucas, André & Seeger, Norman J., 2017. "Network, market, and book-based systemic risk rankings," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 84-90.
    5. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Fang, Libing & Sun, Boyang & Li, Huijing & Yu, Honghai, 2018. "Systemic risk network of Chinese financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 190-206.
    7. Gätjen, Rebekka & Schienle, Melanie, 2015. "Measuring connectedness of Euro area sovereign risk," SFB 649 Discussion Papers 2015-019, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Ben R. Craig & Martin Saldias Zambrana, 2016. "Spatial Dependence and Data-Driven Networks of International Banks," Working Papers (Old Series) 1627, Federal Reserve Bank of Cleveland.
    9. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    10. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," Bank of England working papers 660, Bank of England.
    11. Matteo Barigozzi & Marc Hallin, 2017. "A network analysis of the volatility of high dimensional financial series," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(3), pages 581-605, April.
    12. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    13. Geraci, Marco Valerio & Gnabo, Jean-Yves, 2018. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1371-1390, June.
    14. Paolo Giudici & Shatha Hashem, 2015. "Systemic risk of Islamic Banks," DEM Working Papers Series 103, University of Pavia, Department of Economics and Management.
    15. Yu Chen & Jie Hu & Weiping Zhang, 2020. "Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(6), pages 78-100, November.
    16. Shan, Yuan George & Wang, Yirui & Wu, Wuqing & Zhen, Weihao, 2023. "Does the Achilles heel of guarantee networks drive financial distress?," International Review of Financial Analysis, Elsevier, vol. 87(C).
    17. Kleinow, Jacob & Moreira, Fernando, 2016. "Systemic risk among European banks: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 27-42.
    18. Hong Fan & Allan Alvin Lee Lukaya Amalia & Qian Qian Gao, 2018. "The Assessment of Systemic Risk in the Kenyan Banking Sector," Complexity, Hindawi, vol. 2018, pages 1-15, January.
    19. Linh H. Nguyen & Linh X. D. Nguyen & Linzhi Tan, 2021. "Tail risk connectedness between US industries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3624-3650, July.
    20. Nicola, Giancarlo & Cerchiello, Paola & Aste, Tomaso, 2020. "Information network modeling for U.S. banking systemic risk," LSE Research Online Documents on Economics 107563, London School of Economics and Political Science, LSE Library.
    21. Petre Caraiani, 2020. "Forecasting Financial Networks," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 983-997, March.
    22. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
    23. Betz, Frank & Hautsch, Nikolaus & Peltonen, Tuomas A. & Schienle, Melanie, 2016. "Systemic risk spillovers in the European banking and sovereign network," Working Paper Series in Economics 79, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    24. Rodolfo C. Moura & Márcio P. Laurini, 2021. "Spillovers and jumps in global markets: A comparative analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5997-6013, October.
    25. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    26. Bellavite Pellegrini, Carlo & Cincinelli, Peter & Meoli, Michele & Urga, Giovanni, 2022. "The contribution of (shadow) banks and real estate to systemic risk in China," Journal of Financial Stability, Elsevier, vol. 60(C).
    27. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    28. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto Calogero, 2017. "Estimation and model-based combination of causality networks," SAFE Working Paper Series 165, Leibniz Institute for Financial Research SAFE.
    29. Simone Varotto & Lei Zhao, 2014. "Systemic Risk and Bank Size," ICMA Centre Discussion Papers in Finance icma-dp2014-17, Henley Business School, University of Reading.
    30. Yu Zhao & Huaming Du & Qing Li & Fuzhen Zhuang & Ji Liu & Gang Kou, 2022. "A Comprehensive Survey on Enterprise Financial Risk Analysis from Big Data Perspective," Papers 2211.14997, arXiv.org, revised May 2023.
    31. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
    32. Hué, Sullivan & Lucotte, Yannick & Tokpavi, Sessi, 2019. "Measuring network systemic risk contributions: A leave-one-out approach," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 86-114.
    33. Naeem, Muhammad Abubakr, 2024. "Navigating median and extreme volatility in stock markets: Implications for portfolio strategies," International Review of Economics & Finance, Elsevier, vol. 95(C).
    34. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    35. Wang, Gang-Jin & Jiang, Zhi-Qiang & Lin, Min & Xie, Chi & Stanley, H. Eugene, 2018. "Interconnectedness and systemic risk of China's financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 1-18.
    36. Pham, Thach N. & Powell, Robert & Bannigidadmath, Deepa, 2024. "Tail risk network analysis of Asian banks," Global Finance Journal, Elsevier, vol. 62(C).
    37. Sullivan HUE & Yannick LUCOTTE & Sessi TOKPAVI, 2018. "Measuring Network Systemic Risk Contributions: A Leave-one-out Approach," LEO Working Papers / DR LEO 2608, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    38. Nguyen, Linh Hoang & Lambe, Brendan John, 2021. "International tail risk connectedness: Network and determinants," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    39. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    40. Jacob Kleinow & Tobias Nell, 2015. "Determinants of systemically important banks: the case of Europe," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 7(4), pages 446-476, November.
    41. Ms. Franziska L Ohnsorge & Marcin Wolski & Ms. Yuanyan S Zhang, 2014. "Safe Havens, Feedback Loops, and Shock Propagation in Global Asset Prices," IMF Working Papers 2014/081, International Monetary Fund.
    42. Constantin, Andreea & Peltonen, Tuomas A. & Sarlin, Peter, 2018. "Network linkages to predict bank distress," Journal of Financial Stability, Elsevier, vol. 35(C), pages 226-241.
    43. Matteo Foglia & Eliana Angelini, 2021. "The triple (T3) dimension of systemic risk: Identifying systemically important banks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 7-26, January.
    44. Gustavo Peralta, 2015. "Network-based Measures as Leading Indicators of Market Instability: The case of the Spanish Stock," CNMV Working Papers CNMV Working Papers no 59, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    45. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARS," Working Papers ECARES ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    46. Zhang, Xingmin & Zhang, Shuai, 2021. "Optimal time-varying tail risk network with a rolling window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).

  21. Bibinger, Markus & Hautsch, Nikolaus & Malec, Peter & Reiss, Markus, 2013. "Estimating the quadratic covariation matrix from noisy observations: Local method of moments and efficiency," SFB 649 Discussion Papers 2013-017, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Bibinger, Markus & Hautsch, Nikolaus & Malec, Peter & Reiss, Markus, 2014. "Estimating the spot covariation of asset prices: Statistical theory and empirical evidence," SFB 649 Discussion Papers 2014-055, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    3. Donggyu Kim & Xinyu Song & Yazhen Wang, 2020. "Unified Discrete-Time Factor Stochastic Volatility and Continuous-Time Ito Models for Combining Inference Based on Low-Frequency and High-Frequency," Papers 2006.12039, arXiv.org.
    4. Altmeyer, Randolf & Bibinger, Markus, 2014. "Functional stable limit theorems for efficient spectral covolatility estimators," SFB 649 Discussion Papers 2014-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Altmeyer, Randolf & Bibinger, Markus, 2015. "Functional stable limit theorems for quasi-efficient spectral covolatility estimators," Stochastic Processes and their Applications, Elsevier, vol. 125(12), pages 4556-4600.
    6. Richard Y. Chen & Per A. Mykland, 2015. "Model-Free Approaches to Discern Non-Stationary Microstructure Noise and Time-Varying Liquidity in High-Frequency Data," Papers 1512.06159, arXiv.org, revised Oct 2018.
    7. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
    8. Bibinger, Markus & Winkelmann, Lars, 2013. "Econometrics of co-jumps in high-frequency data with noise," SFB 649 Discussion Papers 2013-021, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Bibinger, Markus & Winkelmann, Lars, 2015. "Econometrics of co-jumps in high-frequency data with noise," Journal of Econometrics, Elsevier, vol. 184(2), pages 361-378.
    10. Richard Y. Chen, 2018. "Inference for Volatility Functionals of Multivariate It\^o Semimartingales Observed with Jump and Noise," Papers 1810.04725, arXiv.org, revised Nov 2019.
    11. Bibinger, Markus & Winkelmann, Lars, 2014. "Common price and volatility jumps in noisy high-frequency data," SFB 649 Discussion Papers 2014-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
    13. Hautsch, Nikolaus & Horvath, Akos, 2017. "How effective are trading pauses?," CFS Working Paper Series 571, Center for Financial Studies (CFS).
    14. Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
    15. Ogihara, Teppei & Yoshida, Nakahiro, 2014. "Quasi-likelihood analysis for nonsynchronously observed diffusion processes," Stochastic Processes and their Applications, Elsevier, vol. 124(9), pages 2954-3008.
    16. Markus Bibinger & Christopher J. Neely & Lars Winkelmann, 2017. "Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book," Working Papers 2017-12, Federal Reserve Bank of St. Louis.
    17. Jean Jacod, 2019. "Estimation of volatility in a high-frequency setting: a short review," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 351-385, December.
    18. Andersen, Torben G. & Cebiroglu, Gökhan & Hautsch, Nikolaus, 2017. "Volatility, information feedback and market microstructure noise: A tale of two regimes," CFS Working Paper Series 569, Center for Financial Studies (CFS).
    19. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    20. Jianqing Fan & Alex Furger & Dacheng Xiu, 2016. "Incorporating Global Industrial Classification Standard Into Portfolio Allocation: A Simple Factor-Based Large Covariance Matrix Estimator With High-Frequency Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 489-503, October.
    21. Fan, Jianqing & Kim, Donggyu, 2019. "Structured volatility matrix estimation for non-synchronized high-frequency financial data," Journal of Econometrics, Elsevier, vol. 209(1), pages 61-78.
    22. Marcio Laurini & Alberto Ohashi, 2014. "A Noisy Principal Component Analysis for Forward Rate Curves," Papers 1408.6279, arXiv.org.
    23. Yuta Koike, 2017. "Time endogeneity and an optimal weight function in pre-averaging covariance estimation," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 15-56, April.
    24. Reiß, Markus & Todorov, Viktor & Tauchen, George, 2015. "Nonparametric test for a constant beta between Itô semi-martingales based on high-frequency data," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2955-2988.
    25. Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
    26. Lars Winkelmann & Markus Bibinger & Tobias Linzert, 2016. "ECB Monetary Policy Surprises: Identification Through Cojumps in Interest Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(4), pages 613-629, June.
    27. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    28. Linzert, Tobias & Winkelmann, Lars & Bibinger, Markus, 2014. "ECB monetary policy surprises: identification through cojumps in interest rates," Working Paper Series 1674, European Central Bank.
    29. Alberto Ohashi & Alexandre B Simas, 2015. "Principal Components Analysis for Semimartingales and Stochastic PDE," Papers 1503.05909, arXiv.org, revised Mar 2016.

  22. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Forecasting systemic impact in financial networks," SFB 649 Discussion Papers 2013-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Robin L. Lumsdaine & Daniel N. Rockmore & Nicholas Foti & Gregory Leibon & J. Doyne Farmer, 2015. "The Intrafirm Complexity of Systemically Important Financial Institutions," Papers 1505.02305, arXiv.org.
    2. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Matteo Barigozzi & Christian Brownlees, 2015. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona School of Economics.
    4. van de Leur, Michiel C.W. & Lucas, André & Seeger, Norman J., 2017. "Network, market, and book-based systemic risk rankings," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 84-90.
    5. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Fang, Libing & Sun, Boyang & Li, Huijing & Yu, Honghai, 2018. "Systemic risk network of Chinese financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 190-206.
    7. Gätjen, Rebekka & Schienle, Melanie, 2015. "Measuring connectedness of Euro area sovereign risk," SFB 649 Discussion Papers 2015-019, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Ben R. Craig & Martin Saldias Zambrana, 2016. "Spatial Dependence and Data-Driven Networks of International Banks," Working Papers (Old Series) 1627, Federal Reserve Bank of Cleveland.
    9. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    10. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," Bank of England working papers 660, Bank of England.
    11. Matteo Barigozzi & Marc Hallin, 2017. "A network analysis of the volatility of high dimensional financial series," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(3), pages 581-605, April.
    12. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    13. Geraci, Marco Valerio & Gnabo, Jean-Yves, 2018. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1371-1390, June.
    14. Paolo Giudici & Shatha Hashem, 2015. "Systemic risk of Islamic Banks," DEM Working Papers Series 103, University of Pavia, Department of Economics and Management.
    15. Yu Chen & Jie Hu & Weiping Zhang, 2020. "Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(6), pages 78-100, November.
    16. Shan, Yuan George & Wang, Yirui & Wu, Wuqing & Zhen, Weihao, 2023. "Does the Achilles heel of guarantee networks drive financial distress?," International Review of Financial Analysis, Elsevier, vol. 87(C).
    17. Kleinow, Jacob & Moreira, Fernando, 2016. "Systemic risk among European banks: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 27-42.
    18. Hong Fan & Allan Alvin Lee Lukaya Amalia & Qian Qian Gao, 2018. "The Assessment of Systemic Risk in the Kenyan Banking Sector," Complexity, Hindawi, vol. 2018, pages 1-15, January.
    19. Linh H. Nguyen & Linh X. D. Nguyen & Linzhi Tan, 2021. "Tail risk connectedness between US industries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3624-3650, July.
    20. Nicola, Giancarlo & Cerchiello, Paola & Aste, Tomaso, 2020. "Information network modeling for U.S. banking systemic risk," LSE Research Online Documents on Economics 107563, London School of Economics and Political Science, LSE Library.
    21. Petre Caraiani, 2020. "Forecasting Financial Networks," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 983-997, March.
    22. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
    23. Betz, Frank & Hautsch, Nikolaus & Peltonen, Tuomas A. & Schienle, Melanie, 2016. "Systemic risk spillovers in the European banking and sovereign network," Working Paper Series in Economics 79, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    24. Rodolfo C. Moura & Márcio P. Laurini, 2021. "Spillovers and jumps in global markets: A comparative analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5997-6013, October.
    25. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    26. Bellavite Pellegrini, Carlo & Cincinelli, Peter & Meoli, Michele & Urga, Giovanni, 2022. "The contribution of (shadow) banks and real estate to systemic risk in China," Journal of Financial Stability, Elsevier, vol. 60(C).
    27. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    28. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto Calogero, 2017. "Estimation and model-based combination of causality networks," SAFE Working Paper Series 165, Leibniz Institute for Financial Research SAFE.
    29. Simone Varotto & Lei Zhao, 2014. "Systemic Risk and Bank Size," ICMA Centre Discussion Papers in Finance icma-dp2014-17, Henley Business School, University of Reading.
    30. Yu Zhao & Huaming Du & Qing Li & Fuzhen Zhuang & Ji Liu & Gang Kou, 2022. "A Comprehensive Survey on Enterprise Financial Risk Analysis from Big Data Perspective," Papers 2211.14997, arXiv.org, revised May 2023.
    31. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
    32. Hué, Sullivan & Lucotte, Yannick & Tokpavi, Sessi, 2019. "Measuring network systemic risk contributions: A leave-one-out approach," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 86-114.
    33. Naeem, Muhammad Abubakr, 2024. "Navigating median and extreme volatility in stock markets: Implications for portfolio strategies," International Review of Economics & Finance, Elsevier, vol. 95(C).
    34. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    35. Wang, Gang-Jin & Jiang, Zhi-Qiang & Lin, Min & Xie, Chi & Stanley, H. Eugene, 2018. "Interconnectedness and systemic risk of China's financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 1-18.
    36. Pham, Thach N. & Powell, Robert & Bannigidadmath, Deepa, 2024. "Tail risk network analysis of Asian banks," Global Finance Journal, Elsevier, vol. 62(C).
    37. Sullivan HUE & Yannick LUCOTTE & Sessi TOKPAVI, 2018. "Measuring Network Systemic Risk Contributions: A Leave-one-out Approach," LEO Working Papers / DR LEO 2608, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    38. Nguyen, Linh Hoang & Lambe, Brendan John, 2021. "International tail risk connectedness: Network and determinants," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    39. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    40. Jacob Kleinow & Tobias Nell, 2015. "Determinants of systemically important banks: the case of Europe," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 7(4), pages 446-476, November.
    41. Ms. Franziska L Ohnsorge & Marcin Wolski & Ms. Yuanyan S Zhang, 2014. "Safe Havens, Feedback Loops, and Shock Propagation in Global Asset Prices," IMF Working Papers 2014/081, International Monetary Fund.
    42. Constantin, Andreea & Peltonen, Tuomas A. & Sarlin, Peter, 2018. "Network linkages to predict bank distress," Journal of Financial Stability, Elsevier, vol. 35(C), pages 226-241.
    43. Matteo Foglia & Eliana Angelini, 2021. "The triple (T3) dimension of systemic risk: Identifying systemically important banks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 7-26, January.
    44. Gustavo Peralta, 2015. "Network-based Measures as Leading Indicators of Market Instability: The case of the Spanish Stock," CNMV Working Papers CNMV Working Papers no 59, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    45. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARS," Working Papers ECARES ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    46. Zhang, Xingmin & Zhang, Shuai, 2021. "Optimal time-varying tail risk network with a rolling window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).

  23. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2012. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2012-053, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Somnath Chatterjee & Marea Sing, 2021. "Measuring Systemic Risk in South African Banks," Working Papers 11004, South African Reserve Bank.
    2. Abduraimova, Kumushoy, 2022. "Contagion and tail risk in complex financial networks," Journal of Banking & Finance, Elsevier, vol. 143(C).
    3. Nguyen, Linh Hoang & Chevapatrakul, Thanaset & Yao, Kai, 2020. "Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 333-355.
    4. Chang, Carolyn W. & Li, Xiaodan & Lin, Edward M.H. & Yu, Min-Teh, 2018. "Systemic risk, interconnectedness, and non-core activities in Taiwan insurance industry," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 273-284.
    5. Robin L. Lumsdaine & Daniel N. Rockmore & Nicholas Foti & Gregory Leibon & J. Doyne Farmer, 2015. "The Intrafirm Complexity of Systemically Important Financial Institutions," Papers 1505.02305, arXiv.org.
    6. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Li, Kelong & Xie, Chi & Ouyang, Yingbo & Mo, Tingcheng & Feng, Yusen, 2024. "Tail risk spillovers in the stock and forex markets at the major emergencies: Evidence from the G20 countries," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    8. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André & Nucera, Federico, 2016. "The information in systemic risk rankings," Working Paper Series 1875, European Central Bank.
    9. Paolo Giudici & Laura Parisi, 2016. "Bail in or Bail out? The Atlante example from a systemic risk perspective," DEM Working Papers Series 124, University of Pavia, Department of Economics and Management.
    10. Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2023. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Empirical Economics, Springer, vol. 65(1), pages 93-110, July.
    11. Eric Jondeau & Michael Rockinger, 2013. "Systemic Risk in Europe," Global Credit Review (GCR), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 1-6.
    12. Okhrin, Ostap & Ristig, Alexander & Sheen, Jeffrey R. & Trück, Stefan, 2015. "Conditional systemic risk with penalized copula," SFB 649 Discussion Papers 2015-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Chao, Xiangrui & Ran, Qin & Chen, Jia & Li, Tie & Qian, Qian & Ergu, Daji, 2022. "Regulatory technology (Reg-Tech) in financial stability supervision: Taxonomy, key methods, applications and future directions," International Review of Financial Analysis, Elsevier, vol. 80(C).
    14. Borghesi, Simone & Flori, Andrea, 2018. "EU ETS facets in the net: Structure and evolution of the EU ETS network," Energy Economics, Elsevier, vol. 75(C), pages 602-635.
    15. Asgharian, Hossein & Krygier, Dominika & Vilhelmsson, Anders, 2019. "Systemic Risk and Centrality Revisited: The Role of Interactions," Working Papers 2019:4, Lund University, Department of Economics.
    16. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhang, Wei, 2019. "Financial systemic risk measurement based on causal network connectedness analysis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 290-307.
    17. Matteo Barigozzi & Christian Brownlees, 2015. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona School of Economics.
    18. Du, Zaichao & Escanciano, Juan Carlos & Zhu, Guangwei, 2023. "The case for CASE: Estimating heterogeneous systemic effects," Journal of Banking & Finance, Elsevier, vol. 157(C).
    19. Bierth, Christopher & Irresberger, Felix & Weiß, Gregor N.F., 2015. "Systemic risk of insurers around the globe," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 232-245.
    20. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2020. "Modeling Turning Points In Global Equity Market," DEM Working Papers Series 195, University of Pavia, Department of Economics and Management.
    21. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.
    22. Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2019. "LASSO-Driven Inference in Time and Space," CeMMAP working papers CWP20/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. Wu, JunFeng & Zhang, Chao & Chen, Yun, 2022. "Analysis of risk correlations among stock markets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 83(C).
    24. Ge, S., 2020. "Text-Based Linkages and Local Risk Spillovers in the Equity Market," Cambridge Working Papers in Economics 20115, Faculty of Economics, University of Cambridge.
    25. Wang, Gang-Jin & Si, Hui-Bin & Chen, Yang-Yang & Xie, Chi & Chevallier, Julien, 2021. "Time domain and frequency domain Granger causality networks: Application to China’s financial institutions," Finance Research Letters, Elsevier, vol. 39(C).
    26. Name 1 Dieter Wang Email 1 & Iman (I.P.P.) van Lelyveld & Julia (J.) Schaumburg, 2018. "Do information contagion and business model similarities explain bank credit risk commonalities?," Tinbergen Institute Discussion Papers 18-100/IV, Tinbergen Institute.
    27. Denbee, Edward & Julliard, Christian & Li, Ye & Yuan, Kathy, 2021. "Network risk and key players: A structural analysis of interbank liquidity," Journal of Financial Economics, Elsevier, vol. 141(3), pages 831-859.
    28. Ouyang, Zisheng & Zhou, Xuewei & Wang, Gang-jin & Liu, Shuwen & Lu, Min, 2024. "Multilayer networks in the frequency domain: Measuring volatility connectedness among Chinese financial institutions," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 909-928.
    29. Paolo Giudici & Laura Parisi, 2017. "Sovereign risk in the Euro area: a multivariate stochastic process approach," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1995-2008, December.
    30. Fousekis, Panos & Grigoriadis, Vasilis, 2022. "Conditional tail price risk spillovers in coffee markets across quality, physical space, and time: Empirical analysis with penalized quantile regressions," Economic Modelling, Elsevier, vol. 106(C).
    31. Ouyang, Zisheng & Zhou, Xuewei, 2023. "Interconnected networks: Measuring extreme risk connectedness between China’s financial sector and real estate sector," International Review of Financial Analysis, Elsevier, vol. 90(C).
    32. Power, Michael, 2021. "The financial reporting system - what is it?," LSE Research Online Documents on Economics 110220, London School of Economics and Political Science, LSE Library.
    33. Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019. "Bayesian nonparametric sparse VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
    34. Xu, Qifa & Li, Mengting & Jiang, Cuixia & He, Yaoyao, 2019. "Interconnectedness and systemic risk network of Chinese financial institutions: A LASSO-CoVaR approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    35. Gian Paolo Clemente & Rosanna Grassi & Chiara Pederzoli, 2020. "Networks and market-based measures of systemic risk: the European banking system in the aftermath of the financial crisis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 159-181, January.
    36. De Novellis, G. & Musile Tanzi, P. & Ranalli, M.G. & Stanghellini, E., 2024. "Leveraged finance exposure in the banking system: Systemic risk and interconnectedness," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    37. Honghai Yu & Wencong Sun & Xiangting Ye & Libing Fang, 2019. "Measuring the increasing connectedness of Chinese assets with global assets: using a variance decompositions method," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(5), pages 1261-1290, March.
    38. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    39. Tan, Changchun & Mo, Lingyu & Wu, Xiaomeng & Zhou, Peng, 2024. "Fintech development and corporate credit risk: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 92(C).
    40. Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Jan 2025.
    41. Samuel Ronnqvist & Peter Sarlin, 2013. "From Text to Bank Interrelation Maps," Papers 1306.3856, arXiv.org.
    42. Borghesi, Simone & Flori, Andrea, 2016. "EU ETS Facets in the Net: How Account Types Influence the Structure of the System," MITP: Mitigation, Innovation and Transformation Pathways 232214, Fondazione Eni Enrico Mattei (FEEM).
    43. Fang, Libing & Sun, Boyang & Li, Huijing & Yu, Honghai, 2018. "Systemic risk network of Chinese financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 190-206.
    44. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    45. Panos Fousekis & Dimitra Tzaferi, 2022. "Tail price risk spillovers along the US beef and pork supply chains," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(2), pages 383-399, April.
    46. Bostandzic, Denefa & Weiß, Gregor N.F., 2018. "Why do some banks contribute more to global systemic risk?," Journal of Financial Intermediation, Elsevier, vol. 35(PA), pages 17-40.
    47. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Okhrin, Yarema, 2017. "Tail event driven networks of SIFIs," SFB 649 Discussion Papers 2017-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    48. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," Bank of England working papers 660, Bank of England.
    49. Ahelegbey, Daniel Felix, 2015. "The Econometrics of Bayesian Graphical Models: A Review With Financial Application," MPRA Paper 92634, University Library of Munich, Germany, revised 25 Apr 2016.
    50. Yajie Yang & Longfeng Zhao & Lin Chen & Chao Wang & Jihui Han, 2021. "Portfolio optimization with idiosyncratic and systemic risks for financial networks," Papers 2111.11286, arXiv.org.
    51. Li, Yueshan & Chen, Shoudong & Sensoy, Ahmet & Wang, Lu, 2024. "Over-expected shocks and financial market security: Evidence from China's markets," Research in International Business and Finance, Elsevier, vol. 68(C).
    52. Dingshi Tian & Zongwu Cai & Ying Fang, 2018. "Econometric Modeling of Risk Measures: A Selective Review of the Recent Literature," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201807, University of Kansas, Department of Economics, revised Oct 2018.
    53. Matteo Barigozzi & Marc Hallin, 2017. "A network analysis of the volatility of high dimensional financial series," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(3), pages 581-605, April.
    54. Xu, Hao & Li, Songsong, 2023. "What impacts foreign capital flows to China's stock markets? Evidence from financial risk spillover networks," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 559-577.
    55. Pierret, D., 2013. "The systemic risk of energy markets," LIDAM Discussion Papers ISBA 2013061, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    56. Foglia, Matteo & Addi, Abdelhamid & Angelini, Eliana, 2022. "The Eurozone banking sector in the time of COVID-19: Measuring volatility connectedness," Global Finance Journal, Elsevier, vol. 51(C).
    57. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    58. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
    59. Peralta, Gustavo & Zareei, Abalfazl, 2016. "A network approach to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 157-180.
    60. Craig, Ben & Karamysheva, Madina & Salakhova, Dilyara, 2023. "Do market-based networks reflect true exposures between banks?," Working Paper Series 2867, European Central Bank.
    61. He, Zhipeng & Zhang, Shuguang, 2024. "Risk contagion and diversification among sovereign CDS, stock, foreign exchange and commodity markets: Fresh evidence from G7 and BRICS countries," Finance Research Letters, Elsevier, vol. 62(PB).
    62. Mengting Li & Qifa Xu & Cuixia Jiang & Yezheng Liu, 2024. "The role of long‐ and short‐run correlation networks in international portfolio selection," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3147-3176, July.
    63. Ahelegbey, Daniel Felix & Giudici, Paolo & Hashem, Shatha Qamhieh, 2021. "Network VAR models to measure financial contagion," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    64. Samuel Ronnqvist & Peter Sarlin, 2014. "Bank Networks from Text: Interrelations, Centrality and Determinants," Papers 1406.7752, arXiv.org, revised Jul 2015.
    65. Geraci, Marco Valerio & Gnabo, Jean-Yves, 2018. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1371-1390, June.
    66. Daniel Felix Ahelegbey, 2022. "Statistical Modelling of Downside Risk Spillovers," FinTech, MDPI, vol. 1(2), pages 1-10, April.
    67. Deng, Yang & Zhang, Ziqing & Zhu, Li, 2021. "A model-based index for systemic risk contribution measurement in financial networks," Economic Modelling, Elsevier, vol. 95(C), pages 35-48.
    68. Ellis, Scott & Sharma, Satish & Brzeszczyński, Janusz, 2022. "Systemic risk measures and regulatory challenges," Journal of Financial Stability, Elsevier, vol. 61(C).
    69. Ouyang, Zisheng & Zhou, Xuewei & Lu, Min & Liu, Ke, 2024. "Imported financial risk in global stock markets: Evidence from the interconnected network," Research in International Business and Finance, Elsevier, vol. 69(C).
    70. Yu Chen & Jie Hu & Weiping Zhang, 2020. "Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(6), pages 78-100, November.
    71. Wang, Wei & Xu, Huifu & Ma, Tiejun, 2023. "Optimal scenario-dependent multivariate shortfall risk measure and its application in risk capital allocation," European Journal of Operational Research, Elsevier, vol. 306(1), pages 322-347.
    72. Yang Deng & Chenyin Gao, 2023. "Where does the risk lie? Systemic risk and tail risk networks in the Chinese financial market," Pacific Economic Review, Wiley Blackwell, vol. 28(2), pages 167-190, May.
    73. Brownlees, Christian & Engle, Robert F., 2017. "SRISK: a conditional capital shortfall measure of systemic risk," ESRB Working Paper Series 37, European Systemic Risk Board.
    74. Wang, Ze & Gao, Xiangyun & Huang, Shupei & Sun, Qingru & Chen, Zhihua & Tang, Renwu & Di, Zengru, 2022. "Measuring systemic risk contribution of global stock markets: A dynamic tail risk network approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
    75. Bianchi, Daniele & Billio, Monica & Casarin, Roberto & Guidolin, Massimo, 2019. "Modeling systemic risk with Markov Switching Graphical SUR models," Journal of Econometrics, Elsevier, vol. 210(1), pages 58-74.
    76. Chen, Ning & Li, Shaofang & Lu, Shuai, 2023. "The extreme risk connectedness of the global financial system: G7 and BRICS evidence," Journal of Multinational Financial Management, Elsevier, vol. 69(C).
    77. Yan, Guan & Liu, Zhidong, 2023. "Interconnectedness of financial institutions based on pledged shares in China," Finance Research Letters, Elsevier, vol. 57(C).
    78. Hong Fan & Allan Alvin Lee Lukaya Amalia & Qian Qian Gao, 2018. "The Assessment of Systemic Risk in the Kenyan Banking Sector," Complexity, Hindawi, vol. 2018, pages 1-15, January.
    79. Härdle, Wolfgang Karl & Wang, Weining & Yu, Lining, 2016. "TENET: Tail-Event driven NETwork risk," Journal of Econometrics, Elsevier, vol. 192(2), pages 499-513.
    80. Grzegorz Halaj & Ruben Hipp, 2024. "Decomposing Systemic Risk: The Roles of Contagion and Common Exposures," Staff Working Papers 24-19, Bank of Canada.
    81. Rui Ding & Siwei Shen & Yuqi Zhu & Linyu Du & Shihui Chen & Juan Liang & Kexing Wang & Wenqian Xiao & Yuxuan Hong, 2023. "Evolution, Forecasting, and Driving Mechanisms of the Digital Financial Network: Evidence from China," Sustainability, MDPI, vol. 15(22), pages 1-18, November.
    82. Huang, Wei-Qiang & Zhuang, Xin-Tian & Yao, Shuang & Uryasev, Stan, 2016. "A financial network perspective of financial institutions’ systemic risk contributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 183-196.
    83. Linh H. Nguyen & Linh X. D. Nguyen & Linzhi Tan, 2021. "Tail risk connectedness between US industries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3624-3650, July.
    84. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Forecasting systemic impact in financial networks," SFB 649 Discussion Papers 2013-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    85. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    86. Tobias Eckernkemper, 2018. "Modeling Systemic Risk: Time-Varying Tail Dependence When Forecasting Marginal Expected Shortfall," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 63-117.
    87. Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2022. "Assessing the impact of policy and regulation interventions in European sovereign credit risk networks: What worked best?," Journal of International Economics, Elsevier, vol. 139(C).
    88. Das, Sanjiv R. & Kalimipalli, Madhu & Nayak, Subhankar, 2022. "Banking networks, systemic risk, and the credit cycle in emerging markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    89. Gong, Xu & Liao, Qin, 2024. "Physical climate risk attention and dynamic volatility connectedness among new energy stocks," Energy Economics, Elsevier, vol. 136(C).
    90. Yao, Yinhong & Li, Jianping & Sun, Xiaolei, 2021. "Measuring the risk of Chinese Fintech industry: evidence from the stock index," Finance Research Letters, Elsevier, vol. 39(C).
    91. Bernardi Mauro & Roy Cerqueti & Arsen Palestini, 2016. "Allocation of risk capital in a cost cooperative game induced by a modified Expected Shortfall," Papers 1608.02365, arXiv.org.
    92. Roman Mestre, 2023. "Stock profiling using time–frequency-varying systematic risk measure," Post-Print hal-04058285, HAL.
    93. Bing‐Yue Liu & Qiang Ji & Duc Khuong Nguyen & Ying Fan, 2021. "Dynamic dependence and extreme risk comovement: The case of oil prices and exchange rates," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2612-2636, April.
    94. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang, 2021. "Financial Risk Meter based on expectiles," IRTG 1792 Discussion Papers 2021-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    95. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
    96. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, vol. 7(1), pages 1-25, January.
    97. Betz, Frank & Hautsch, Nikolaus & Peltonen, Tuomas A. & Schienle, Melanie, 2016. "Systemic risk spillovers in the European banking and sovereign network," Working Paper Series in Economics 79, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    98. Chen, Yan & Mo, Dongxu & Xu, Zezhou, 2022. "A study of interconnections and contagion among Chinese financial institutions using a ΔCoV aR network," Finance Research Letters, Elsevier, vol. 45(C).
    99. M. Bernardi & L. Petrella, 2014. "Interconnected risk contributions: an heavy-tail approach to analyse US financial sectors," Papers 1401.6408, arXiv.org, revised Apr 2014.
    100. Chabot, Miia & Bertrand, Jean-Louis, 2021. "Complexity, interconnectedness and stability: New perspectives applied to the European banking system," Journal of Business Research, Elsevier, vol. 129(C), pages 784-800.
    101. Jian, Zhihong & Li, Xupei, 2021. "Skewness-based market integration: A systemic risk measure across international equity markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    102. Carlos Castro & Stijn Ferrari, 2011. "Measuring and testing for the systemically important financial institutions," Documentos de Trabajo 8779, Universidad del Rosario.
    103. Addi, Abdelhamid & Bouoiyour, Jamal, 2023. "Interconnectedness and extreme risk: Evidence from dual banking systems," Economic Modelling, Elsevier, vol. 120(C).
    104. Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
    105. Wu, Shan & Tong, Mu & Yang, Zhongyi & Zhang, Tianyi, 2021. "Interconnectedness, systemic risk, and the influencing factors: Some evidence from China’s financial institutions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    106. Qicheng Zhao & Zhouwei Wang & Yuping Song, 2024. "Systematic Research on Multi-dimensional and Multiple Correlation Contagion Networks of Extreme Risk in China’s Banking Industry," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1137-1162, August.
    107. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    108. Zongwu Cai & Ying Fang & Dingshi Tian, 2024. "CAViaR Model Selection Via Adaptive Lasso," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202403, University of Kansas, Department of Economics, revised Jan 2024.
    109. Ahmad, Wasim & Tiwari, Shiv Ratan & Wadhwani, Akshay & Khan, Mohammad Azeem & Bekiros, Stelios, 2023. "Financial networks and systemic risk vulnerabilities: A tale of Indian banks," Research in International Business and Finance, Elsevier, vol. 65(C).
    110. Arnold Polanski & Evarist Stoja & Ching‐Wai (Jeremy) Chiu, 2021. "Tail risk interdependence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5499-5511, October.
    111. Mengting Li & Qifa Xu & Cuixia Jiang & Qinna Zhao, 2023. "The role of tail network topological characteristic in portfolio selection: A TNA‐PMC model," International Review of Finance, International Review of Finance Ltd., vol. 23(1), pages 37-57, March.
    112. Casarin, Roberto & Costola, Michele & Yenerdag, Erdem, 2018. "Financial bridges and network communities," SAFE Working Paper Series 208, Leibniz Institute for Financial Research SAFE, revised 2018.
    113. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Okhrin, Yarema, 2019. "Tail event driven networks of SIFIs," Journal of Econometrics, Elsevier, vol. 208(1), pages 282-298.
    114. Karim, Sitara & Shafiullah, Muhammad & Naeem, Muhammad Abubakr, 2024. "When one domino falls, others follow: A machine learning analysis of extreme risk spillovers in developed stock markets," International Review of Financial Analysis, Elsevier, vol. 93(C).
    115. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    116. Zbonakova, L. & Härdle, W.K. & Wang, W., 2016. "Time Varying Quantile Lasso," Working Papers 16/07, Department of Economics, City University London.
    117. Giulia Masi & Giorgio Ricchiuti, 2020. "From FDI network topology to macroeconomic instability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 133-158, January.
    118. Gong, Xiao-Li & Liu, Jian-Min & Xiong, Xiong & Zhang, Wei, 2022. "Research on stock volatility risk and investor sentiment contagion from the perspective of multi-layer dynamic network," International Review of Financial Analysis, Elsevier, vol. 84(C).
    119. Cincinelli, Peter & Pellini, Elisabetta & Urga, Giovanni, 2022. "Systemic risk in the Chinese financial system: A panel Granger causality analysis," International Review of Financial Analysis, Elsevier, vol. 82(C).
    120. Cai, Jian & Eidam, Frederik & Saunders, Anthony & Steffen, Sascha, 2018. "Syndication, interconnectedness, and systemic risk," Journal of Financial Stability, Elsevier, vol. 34(C), pages 105-120.
    121. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    122. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto Calogero, 2017. "Estimation and model-based combination of causality networks," SAFE Working Paper Series 165, Leibniz Institute for Financial Research SAFE.
    123. Paolo Giudici & Peter Sarlin & Alessandro Spelta, 2016. "The multivariate nature of systemic risk: direct and common exposures," DEM Working Papers Series 118, University of Pavia, Department of Economics and Management.
    124. Hałaj, Grzegorz & Hipp, Ruben, 2024. "Decomposing systemic risk: the roles of contagion and common exposures," Working Paper Series 2929, European Central Bank.
    125. Naeem, Muhammad Abubakr & Yousaf, Imran & Karim, Sitara & Yarovaya, Larisa & Ali, Shoaib, 2023. "Tail-event driven NETwork dependence in emerging markets," Emerging Markets Review, Elsevier, vol. 55(C).
    126. Muzi Chen & Yuhang Wang & Boyao Wu & Difang Huang, 2024. "Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information Entropy," Papers 2403.19439, arXiv.org.
    127. Huang, Wei-Qiang & Wang, Dan, 2018. "A return spillover network perspective analysis of Chinese financial institutions’ systemic importance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 405-421.
    128. Bluhm, Marcel & Krahnen, Jan Pieter, 2014. "Systemic risk in an interconnected banking system with endogenous asset markets," Journal of Financial Stability, Elsevier, vol. 13(C), pages 75-94.
    129. Alexandre Belloni & Victor Chernozhukov & Abhishek Kaul, 2017. "Confidence bands for coefficients in high dimensional linear models with error-in-variables," CeMMAP working papers 22/17, Institute for Fiscal Studies.
    130. Zhang, Xingmin & Zhang, Shuai & Lu, Liping, 2022. "The banking instability and climate change: Evidence from China," Energy Economics, Elsevier, vol. 106(C).
    131. Peltonen, Tuomas A. & Sarlin, Peter & Piloiu, Andreea, 2015. "Network linkages to predict bank distress," Working Paper Series 1828, European Central Bank.
    132. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    133. Simone Varotto & Lei Zhao, 2014. "Systemic Risk and Bank Size," ICMA Centre Discussion Papers in Finance icma-dp2014-17, Henley Business School, University of Reading.
    134. Xue Cui & Lu Yang, 2024. "Systemic risk and idiosyncratic networks among global systemically important banks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 58-75, January.
    135. Zhou, Dong-hai & Liu, Xiao-xing, 2024. "Does systemic risk in the fund markets predict future economic downturns?," International Review of Financial Analysis, Elsevier, vol. 92(C).
    136. Joerg Osterrieder & Stephen Chan & Jeffrey Chu & Yuanyuan Zhang & Branka Hadji Misheva & Codruta Mare, 2024. "Enhancing Security in Blockchain Networks: Anomalies, Frauds, and Advanced Detection Techniques," Papers 2402.11231, arXiv.org.
    137. Chao, Shih-kang & Härdle, Wolfgang Karl & Hien, Pham-thu, 2014. "Credit risk calibration based on CDS spreads," SFB 649 Discussion Papers 2014-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    138. Polanski, Arnold & Stoja, Evarist, 2015. "Extreme risk interdependence," Bank of England working papers 563, Bank of England.
    139. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
    140. Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: a network analysis," ESRB Working Paper Series 90, European Systemic Risk Board.
    141. Ning, Wei & Zhao, Jiahua & Jiang, Fuwei, 2024. "ETFs and tail dependence: Evidence from Chinese stock market," Journal of International Money and Finance, Elsevier, vol. 149(C).
    142. Jondeau, Eric & Khalilzadeh, Amir, 2022. "Predicting the stressed expected loss of large U.S. banks," Journal of Banking & Finance, Elsevier, vol. 134(C).
    143. Hué, Sullivan & Lucotte, Yannick & Tokpavi, Sessi, 2019. "Measuring network systemic risk contributions: A leave-one-out approach," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 86-114.
    144. Anna Denkowska & Stanisław Wanat, 2020. "A Tail Dependence-Based MST and Their Topological Indicators in Modeling Systemic Risk in the European Insurance Sector," Risks, MDPI, vol. 8(2), pages 1-22, April.
    145. Doğan, Buhari & Ben Jabeur, Sami & Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins, 2025. "Asymmetry in returns and volatility between green financial assets, sustainable investments, clean energy, and international stock markets," Research in International Business and Finance, Elsevier, vol. 73(PA).
    146. Lavín, Jaime F. & Valle, Mauricio A. & Magner, Nicolás S., 2024. "Stock market pattern recognition using symbol entropy analysis," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    147. Zhang, Weiping & Zhuang, Xintian & Wang, Jian & Lu, Yang, 2020. "Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    148. Naeem, Muhammad Abubakr, 2024. "Navigating median and extreme volatility in stock markets: Implications for portfolio strategies," International Review of Economics & Finance, Elsevier, vol. 95(C).
    149. Zbonakova, Lenka & Härdle, Wolfgang Karl & Wang, Weining, 2016. "Time varying quantile Lasso," SFB 649 Discussion Papers 2016-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    150. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    151. Huang, Wei-Qiang & Wang, Dan, 2020. "Financial network linkages to predict economic output," Finance Research Letters, Elsevier, vol. 33(C).
    152. Ren, Yinghua & Zhao, Wanru & You, Wanhai & Zhu, Huiming, 2022. "Multiscale features of extreme risk spillover networks among global stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    153. Haiming Long & Ji Zhang & Nengyu Tang, 2017. "Does network topology influence systemic risk contribution? A perspective from the industry indices in Chinese stock market," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-19, July.
    154. Tian, Sihua & Li, Shaofang & Gu, Qinen, 2023. "Measurement and contagion modelling of systemic risk in China's financial sectors: Evidence for functional data analysis and complex network," International Review of Financial Analysis, Elsevier, vol. 90(C).
    155. Ayoub Kyoud & Cherif El Msiyah & Jaouad Madkour, 2023. "Modelling Systemic Risk in Morocco’s Banking System," IJFS, MDPI, vol. 11(2), pages 1-16, May.
    156. Yu, Lining & Härdle, Wolfgang Karl & Borke, Lukas & Benschop, Thijs, 2017. "FRM: A financial risk meter based on penalizing tail events occurrence," SFB 649 Discussion Papers 2017-003, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    157. Deng, Chao & Su, Xiaojian & Wang, Gangjin & Peng, Cheng, 2022. "The existence of flight-to-quality under extreme conditions: Evidence from a nonlinear perspective in Chinese stocks and bonds' sectors," Economic Modelling, Elsevier, vol. 113(C).
    158. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    159. Wang, Gang-Jin & Jiang, Zhi-Qiang & Lin, Min & Xie, Chi & Stanley, H. Eugene, 2018. "Interconnectedness and systemic risk of China's financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 1-18.
    160. Cristina Zeldea, 2020. "Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions," Administrative Sciences, MDPI, vol. 10(3), pages 1-14, August.
    161. Weiß, Gregor N.F. & Mühlnickel, Janina, 2014. "Why do some insurers become systemically relevant?," Journal of Financial Stability, Elsevier, vol. 13(C), pages 95-117.
    162. Wang, Weining & Yu, Lining & Wang, Bingling, 2020. "Tail Event Driven Factor Augmented Dynamic Model," IRTG 1792 Discussion Papers 2020-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    163. Feng, Yusen & Wang, Gang-Jin & Zhu, You & Xie, Chi, 2023. "Systemic risk spillovers and the determinants in the stock markets of the Belt and Road countries," Emerging Markets Review, Elsevier, vol. 55(C).
    164. Pham, Thach N. & Powell, Robert & Bannigidadmath, Deepa, 2024. "Tail risk network analysis of Asian banks," Global Finance Journal, Elsevier, vol. 62(C).
    165. Jiang, Cuixia & Li, Yuqian & Xu, Qifa & Liu, Yezheng, 2021. "Measuring risk spillovers from multiple developed stock markets to China: A vine-copula-GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 386-398.
    166. Chao, Shih-Kang & Härdle, Wolfgang Karl & Wang, Weining, 2012. "Quantile regression in risk calibration," SFB 649 Discussion Papers 2012-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    167. Sullivan HUE & Yannick LUCOTTE & Sessi TOKPAVI, 2018. "Measuring Network Systemic Risk Contributions: A Leave-one-out Approach," LEO Working Papers / DR LEO 2608, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    168. Ouyang, Zisheng & Zhou, Xuewei, 2023. "Multilayer networks in the frequency domain: Measuring extreme risk connectedness of Chinese financial institutions," Research in International Business and Finance, Elsevier, vol. 65(C).
    169. Sarlin, Peter & Rönnqvist, Samuel, 2016. "Bank networks from text: interrelations, centrality and determinants," Working Paper Series 1876, European Central Bank.
    170. Liang, Qi & Lu, Yanchen & Li, Zheng, 2020. "Business connectedness or market risk? Evidence from financial institutions in China," China Economic Review, Elsevier, vol. 62(C).
    171. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    172. Jian, Zhihong & Lu, Haisong & Zhu, Zhican & Xu, Huiling, 2023. "Frequency heterogeneity of tail connectedness: Evidence from global stock markets," Economic Modelling, Elsevier, vol. 125(C).
    173. Trenca Ioan & Petria Nicolae & Corovei Emilia, 2015. "Idiosyncratic Risk And Systemic Risk In The European Banking System," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 912-919, July.
    174. Su, Zhi & Xu, Fuwei, 2021. "Dynamic identification of systemically important financial markets in the spread of contagion: A ripple network based collective spillover effect approach," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    175. Baltakienė, Margarita & Kanniainen, Juho & Baltakys, Kęstutis, 2021. "Identification of information networks in stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    176. Marcin Łupiński, 2019. "Wskaźniki wczesnego ostrzegania przed niestabilnością finansową polskiego sektora bankowego," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 55, pages 99-113.
    177. Uddin, Gazi Salah & Luo, Tianqi & Yahya, Muhammad & Jayasekera, Ranadeva & Rahman, Md Lutfur & Okhrin, Yarema, 2023. "Risk network of global energy markets," Energy Economics, Elsevier, vol. 125(C).
    178. Foglia, Matteo & Addi, Abdelhamid & Wang, Gang-Jin & Angelini, Eliana, 2022. "Bearish Vs Bullish risk network: A Eurozone financial system analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    179. Wang, Dan & Huang, Wei-Qiang, 2021. "Centrality-based measures of financial institutions’ systemic importance: A tail dependence network view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    180. Myšičková, Alena & Song, Song & Majer, Piotr & Mohr, Peter N. C. & Heekeren, Hauke R. & Härdle, Wolfgang Karl, 2011. "Risk patterns and correlated brain activities: Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers 2011-085, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    181. Samuel R�nnqvist & Peter Sarlin, 2015. "Bank networks from text: interrelations, centrality and determinants," Quantitative Finance, Taylor & Francis Journals, vol. 15(10), pages 1619-1635, October.
    182. Sla{dj}ana Babi'c & Christophe Ley & Lorenzo Ricci & David Veredas, 2020. "TailCoR," Papers 2011.14817, arXiv.org.
    183. Nicolás Magner & Jaime F. Lavín & Mauricio A. Valle, 2022. "Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach," Mathematics, MDPI, vol. 10(19), pages 1-30, October.
    184. Nguyen, Linh Hoang & Lambe, Brendan John, 2021. "International tail risk connectedness: Network and determinants," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    185. Fousekis, Panos, 2022. "Price risk connectedness in the principal olive oil markets of the EU," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    186. Yu, Jia-Wei & Xie, Wen-Jie & Jiang, Zhi-Qiang, 2018. "Early warning model based on correlated networks in global crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1335-1343.
    187. Daning Hu & Gerhard Schwabe & Xiao Li, 2015. "Systemic risk management and investment analysis with financial network analytics: research opportunities and challenges," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-9, December.
    188. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    189. Maghyereh, Aktham & Abdoh, Hussein, 2024. "Tail risk connectedness among GCC banks episodes from the Global Financial Crisis to COVID-19 pandemic," The Quarterly Review of Economics and Finance, Elsevier, vol. 96(C).
    190. Liu, Zixin & Hu, Jun & Zhang, Shuguang & He, Zhipeng, 2024. "Risk spillovers among oil, gold, stock, and foreign exchange markets: Evidence from G20 economies," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    191. Kraft, Holger & Schmidt, Alexander, 2013. "Systemic risk in the financial sector: What can se learn from option markets?," SAFE Working Paper Series 25, Leibniz Institute for Financial Research SAFE.
    192. Nistor Simona, 2017. "Banks’ Vulnerability and Financial Openness across Central and Eastern Europe," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, vol. 62(3), pages 47-66, December.
    193. Geert Mesters & Christian Brownlees, 2017. "Detecting Granular Time Series in Large Panels," Working Papers 991, Barcelona School of Economics.
    194. Xin Yang & Shan Chen & Hong Liu & Xiaoguang Yang & Chuangxia Huang, 2023. "Jump volatility spillover network based measurement of systemic importance of Chinese financial institutions," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1201-1213, April.
    195. Keilbar, Georg & Wang, Weining, 2019. "Modelling Systemic Risk Using Neural Network Quantile Regression," IRTG 1792 Discussion Papers 2019-019, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    196. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    197. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
    198. Yaya Su & Zhehao Huang & Benjamin M. Drakeford, 2019. "Monetary Policy, Industry Heterogeneity and Systemic Risk—Based on a High Dimensional Network Analysis," Sustainability, MDPI, vol. 11(22), pages 1-15, November.
    199. Emanuele De Meo & Giacomo Tizzanini, 2021. "GDP‐network CoVaR: A tool for assessing growth‐at‐risk," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 50(2), July.
    200. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    201. Liu, Bing-Yue & Fan, Ying & Ji, Qiang & Hussain, Nazim, 2022. "High-dimensional CoVaR network connectedness for measuring conditional financial contagion and risk spillovers from oil markets to the G20 stock system," Energy Economics, Elsevier, vol. 105(C).
    202. Abendschein, Michael & Grundke, Peter, 2018. "On the ranking consistency of global systemic risk measures: empirical evidence," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181623, Verein für Socialpolitik / German Economic Association.
    203. Chen, Yan & Wang, Gang-Jin & Zhu, You & Xie, Chi & Uddin, Gazi Salah, 2023. "Quantile connectedness and the determinants between FinTech and traditional financial institutions: Evidence from China," Global Finance Journal, Elsevier, vol. 58(C).
    204. Fang, Ming & Taylor, Stephen & Uddin, Ajim, 2022. "The network structure of overnight index swap rates," Finance Research Letters, Elsevier, vol. 46(PB).
    205. Gao, Haoyu & Ouyang, Yiling & Wang, Yaxin, 2024. "Corporate bond defaults and spillover effects on bank risk: Evidence from city commercial banks in China," Research in International Business and Finance, Elsevier, vol. 69(C).
    206. Xu, Qiuhua & Yan, Haoyang & Zhao, Tianyu, 2022. "Contagion effect of systemic risk among industry sectors in China’s stock market," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    207. Paolo Giudici & Laura Parisi, 2015. "Modeling Systemic Risk with Correlated Stochastic Processes," DEM Working Papers Series 110, University of Pavia, Department of Economics and Management.
    208. Badics, Milan Csaba & Huszar, Zsuzsa R. & Kotro, Balazs B., 2023. "The impact of crisis periods and monetary decisions of the Fed and the ECB on the sovereign yield curve network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    209. Foglia, Matteo & Angelini, Eliana, 2020. "From me to you: Measuring connectedness between Eurozone financial institutions," Research in International Business and Finance, Elsevier, vol. 54(C).
    210. Frank Emmert-Streib & Aliyu Musa & Kestutis Baltakys & Juho Kanniainen & Shailesh Tripathi & Olli Yli-Harja & Herbert Jodlbauer & Matthias Dehmer, 2017. "Computational Analysis of the structural properties of Economic and Financial Networks," Papers 1710.04455, arXiv.org.
    211. Nadine M Walters & Conrad Beyers & Gusti van Zyl & Rolf van den Heever, 2018. "A framework for simulating systemic risk and its application to the South African banking sector," Papers 1811.04223, arXiv.org.
    212. Lining Yu & Wolfgang Karl Hardle & Lukas Borke & Thijs Benschop, 2020. "An AI approach to measuring financial risk," Papers 2009.13222, arXiv.org.
    213. Zhu, Bo & Deng, Yuanyue & Lin, Renda & Hu, Xin & Chen, Pingshe, 2022. "Energy security: Does systemic risk spillover matter? Evidence from China," Energy Economics, Elsevier, vol. 114(C).
    214. Atasoy, Burak Sencer & Özkan, İbrahim & Erden, Lütfi, 2024. "The determinants of systemic risk contagion," Economic Modelling, Elsevier, vol. 130(C).
    215. Fuwei Xu, 2024. "Modeling the Paths of China’s Systemic Financial Risk Contagion: A Ripple Network Perspective Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 47-73, January.
    216. Zhang, Weiping & Zhuang, Xintian & Lu, Yang & Wang, Jian, 2020. "Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework," International Review of Financial Analysis, Elsevier, vol. 71(C).
    217. Diebold, Francis X. & Yılmaz, Kamil, 2023. "Reprint of: On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 234(S), pages 70-90.
    218. Du, Ruijin & Dong, Gaogao & Tian, Lixin & Wang, Yougui & Zhao, Longfeng & Zhang, Xin & Vilela, André L.M. & Stanley, H. Eugene, 2019. "Identifying the peak point of systemic risk in international crude oil importing trade," Energy, Elsevier, vol. 176(C), pages 281-291.
    219. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARS," Working Papers ECARES ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    220. Wang, Gang-Jin & Chen, Yan & Zhu, You & Xie, Chi, 2024. "Systemic risk prediction using machine learning: Does network connectedness help prediction?," International Review of Financial Analysis, Elsevier, vol. 93(C).
    221. Zhou, Dong-hai & Liu, Xiao-xing & Tang, Chun & Yang, Guang-yi, 2023. "Time-varying risk spillovers in Chinese stock market – New evidence from high-frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    222. Daniel Felix Ahelegbey, 2015. "The Econometrics of Networks: A Review," Working Papers 2015:13, Department of Economics, University of Venice "Ca' Foscari".
    223. Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020. "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series 181, University of Pavia, Department of Economics and Management.
    224. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.
    225. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).
    226. Wu, Baohui & Zhu, Pingheng & Yin, Hua & Wen, Fenghua, 2023. "The risk spillover of high carbon enterprises in China: Evidence from the stock market," Energy Economics, Elsevier, vol. 126(C).
    227. Li, Yanshuang & Zhuang, Xintian & Wang, Jian, 2021. "Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    228. Ko, Bonggyun & Song, Jae Wook, 2018. "A simple analytics framework for evaluating mean escape time in different term structures with stochastic volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 398-412.
    229. Huang, Wei-Qiang & Wang, Dan, 2018. "Systemic importance analysis of chinese financial institutions based on volatility spillover network," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 19-30.

  24. Hautsch, Nikolaus & Huang, Ruihong, 2012. "On the dark side of the market: Identifying and analyzing hidden order placements," SFB 649 Discussion Papers 2012-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Katarzyna Bień-Barkowska, 2014. "“Every move you make, every step you take, I’ll be watching you” – the quest for hidden orders in the interbank FX spot market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(3), pages 197-224.
    2. Mahmoud Mahfouz & Angelos Filos & Cyrine Chtourou & Joshua Lockhart & Samuel Assefa & Manuela Veloso & Danilo Mandic & Tucker Balch, 2019. "On the Importance of Opponent Modeling in Auction Markets," Papers 1911.12816, arXiv.org.
    3. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
    4. Quanbiao Shang & Teresa Serra & Philip Garcia & Mindy Mallory, 2021. "Looking under the surface: An analysis of iceberg orders in the U.S. agricultural futures markets," Agricultural Economics, International Association of Agricultural Economists, vol. 52(4), pages 679-699, July.
    5. Garvey, Ryan & Huang, Tao & Wu, Fei, 2016. "Why do traders choose dark markets?," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 12-28.
    6. Degryse, Hans & Karagiannis, Nikolaos & Tombeur, Geoffrey & Wuyts, Gunther, 2021. "Two shades of opacity: Hidden orders and dark trading," Journal of Financial Intermediation, Elsevier, vol. 47(C).
    7. Mahmoud Mahfouz & Tucker Balch & Manuela Veloso & Danilo Mandic, 2021. "Learning to Classify and Imitate Trading Agents in Continuous Double Auction Markets," Papers 2110.01325, arXiv.org, revised Oct 2021.
    8. Arzandeh, Mehdi & Frank, Julieta, 2017. "The Information Content of the Limit Order Book," 7th Annual Canadian Agri-Food Policy Conference, January 11-13, 2017, Ottawa, ON 253251, Canadian Agricultural Economics Society.
    9. Arzandeh, Mehdi & Frank, Julieta, 2017. "Price Discovery in Agricultural Futures Markets: Should We Look Beyond the Best Bid-Ask Spread?," Annual Meeting, 2017, June 18-21, Montreal, Canada 259344, Canadian Agricultural Economics Society.
    10. Hagströmer, Björn & Nordén, Lars, 2013. "The diversity of high-frequency traders," Journal of Financial Markets, Elsevier, vol. 16(4), pages 741-770.

  25. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Local adaptive multiplicative error models for high-frequency forecasts," SFB 649 Discussion Papers 2012-031, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the Term Structure of Option Implied Volatility: The Power of an Adaptive Method," IRTG 1792 Discussion Papers 2018-046, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
    4. Khowaja, Kainat & Saef, Danial & Sizov, Sergej & Härdle, Wolfgang Karl, 2020. "Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition," IRTG 1792 Discussion Papers 2020-026, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Shen, Zhiwei, 2016. "Adaptive local parametric estimation of crop yields: implication for crop insurance ratemaking," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249984, European Association of Agricultural Economists.
    6. Tapia, Sebastian & Kristjanpoller, Werner, 2022. "Framework based on multiplicative error and residual analysis to forecast bitcoin intraday-volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    7. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.
    8. Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.
    9. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
    10. Cipollini, Fabrizio & Gallo, Giampiero M., 2025. "Multiplicative Error Models: 20 years on," Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
    11. Härdle, Wolfgang Karl & Mihoci, Andrija & Ting, Christopher Hian-Ann, 2014. "Adaptive order flow forecasting with multiplicative error models," SFB 649 Discussion Papers 2014-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.
    13. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    14. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
    15. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
    16. Perera, Indeewara & Koul, Hira L., 2017. "Fitting a two phase threshold multiplicative error model," Journal of Econometrics, Elsevier, vol. 197(2), pages 348-367.
    17. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
    18. Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019. "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1473-1489, September.

  26. Hautsch, Nikolaus & Huang, Ruihong, 2012. "On the dark side of the market: Identifying and analyzing hidden order placements," SFB 649 Discussion Papers 2012-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Katarzyna Bień-Barkowska, 2014. "“Every move you make, every step you take, I’ll be watching you” – the quest for hidden orders in the interbank FX spot market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(3), pages 197-224.
    2. Mahmoud Mahfouz & Angelos Filos & Cyrine Chtourou & Joshua Lockhart & Samuel Assefa & Manuela Veloso & Danilo Mandic & Tucker Balch, 2019. "On the Importance of Opponent Modeling in Auction Markets," Papers 1911.12816, arXiv.org.
    3. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
    4. Quanbiao Shang & Teresa Serra & Philip Garcia & Mindy Mallory, 2021. "Looking under the surface: An analysis of iceberg orders in the U.S. agricultural futures markets," Agricultural Economics, International Association of Agricultural Economists, vol. 52(4), pages 679-699, July.
    5. Garvey, Ryan & Huang, Tao & Wu, Fei, 2016. "Why do traders choose dark markets?," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 12-28.
    6. Degryse, Hans & Karagiannis, Nikolaos & Tombeur, Geoffrey & Wuyts, Gunther, 2021. "Two shades of opacity: Hidden orders and dark trading," Journal of Financial Intermediation, Elsevier, vol. 47(C).
    7. Mahmoud Mahfouz & Tucker Balch & Manuela Veloso & Danilo Mandic, 2021. "Learning to Classify and Imitate Trading Agents in Continuous Double Auction Markets," Papers 2110.01325, arXiv.org, revised Oct 2021.
    8. Arzandeh, Mehdi & Frank, Julieta, 2017. "The Information Content of the Limit Order Book," 7th Annual Canadian Agri-Food Policy Conference, January 11-13, 2017, Ottawa, ON 253251, Canadian Agricultural Economics Society.
    9. Arzandeh, Mehdi & Frank, Julieta, 2017. "Price Discovery in Agricultural Futures Markets: Should We Look Beyond the Best Bid-Ask Spread?," Annual Meeting, 2017, June 18-21, Montreal, Canada 259344, Canadian Agricultural Economics Society.
    10. Hagströmer, Björn & Nordén, Lars, 2013. "The diversity of high-frequency traders," Journal of Financial Markets, Elsevier, vol. 16(4), pages 741-770.

  27. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Local adaptive multiplicative error models for high-frequency forecasts," SFB 649 Discussion Papers 2012-031, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the Term Structure of Option Implied Volatility: The Power of an Adaptive Method," IRTG 1792 Discussion Papers 2018-046, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
    4. Khowaja, Kainat & Saef, Danial & Sizov, Sergej & Härdle, Wolfgang Karl, 2020. "Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition," IRTG 1792 Discussion Papers 2020-026, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Shen, Zhiwei, 2016. "Adaptive local parametric estimation of crop yields: implication for crop insurance ratemaking," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249984, European Association of Agricultural Economists.
    6. Tapia, Sebastian & Kristjanpoller, Werner, 2022. "Framework based on multiplicative error and residual analysis to forecast bitcoin intraday-volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    7. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.
    8. Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.
    9. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
    10. Cipollini, Fabrizio & Gallo, Giampiero M., 2025. "Multiplicative Error Models: 20 years on," Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
    11. Härdle, Wolfgang Karl & Mihoci, Andrija & Ting, Christopher Hian-Ann, 2014. "Adaptive order flow forecasting with multiplicative error models," SFB 649 Discussion Papers 2014-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.
    13. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    14. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
    15. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
    16. Perera, Indeewara & Koul, Hira L., 2017. "Fitting a two phase threshold multiplicative error model," Journal of Econometrics, Elsevier, vol. 197(2), pages 348-367.
    17. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
    18. Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019. "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1473-1489, September.

  28. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    2. Anne Michaels & Michael Grüning, 2017. "Relationship of corporate social responsibility disclosure on information asymmetry and the cost of capital," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 28(3), pages 251-274, October.
    3. Carl Chiarella & Xue-Zhong He & Lei Shi & Lijian Wei, 2017. "A behavioural model of investor sentiment in limit order markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(1), pages 71-86, January.
    4. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Bagnara, Matteo & Jappelli, Ruggero, 2022. "Liquidity derivatives," SAFE Working Paper Series 358, Leibniz Institute for Financial Research SAFE.
    6. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Gianbiagio Curato & Fabrizio Lillo, 2013. "Modeling the coupled return-spread high frequency dynamics of large tick assets," Papers 1310.4539, arXiv.org.
    8. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
    9. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Gong, Yuting & Chen, Qiang & Liang, Jufang, 2018. "A mixed data sampling copula model for the return-liquidity dependence in stock index futures markets," Economic Modelling, Elsevier, vol. 68(C), pages 586-598.
    11. Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019. "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1473-1489, September.
    12. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    13. Arifovic, Jasmina & He, Xue-zhong & Wei, Lijian, 2022. "Machine learning and speed in high-frequency trading," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).

  29. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Somnath Chatterjee & Marea Sing, 2021. "Measuring Systemic Risk in South African Banks," Working Papers 11004, South African Reserve Bank.
    2. Abduraimova, Kumushoy, 2022. "Contagion and tail risk in complex financial networks," Journal of Banking & Finance, Elsevier, vol. 143(C).
    3. Nguyen, Linh Hoang & Chevapatrakul, Thanaset & Yao, Kai, 2020. "Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 333-355.
    4. Chang, Carolyn W. & Li, Xiaodan & Lin, Edward M.H. & Yu, Min-Teh, 2018. "Systemic risk, interconnectedness, and non-core activities in Taiwan insurance industry," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 273-284.
    5. Robin L. Lumsdaine & Daniel N. Rockmore & Nicholas Foti & Gregory Leibon & J. Doyne Farmer, 2015. "The Intrafirm Complexity of Systemically Important Financial Institutions," Papers 1505.02305, arXiv.org.
    6. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Li, Kelong & Xie, Chi & Ouyang, Yingbo & Mo, Tingcheng & Feng, Yusen, 2024. "Tail risk spillovers in the stock and forex markets at the major emergencies: Evidence from the G20 countries," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    8. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André & Nucera, Federico, 2016. "The information in systemic risk rankings," Working Paper Series 1875, European Central Bank.
    9. Paolo Giudici & Laura Parisi, 2016. "Bail in or Bail out? The Atlante example from a systemic risk perspective," DEM Working Papers Series 124, University of Pavia, Department of Economics and Management.
    10. Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2023. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Empirical Economics, Springer, vol. 65(1), pages 93-110, July.
    11. Eric Jondeau & Michael Rockinger, 2013. "Systemic Risk in Europe," Global Credit Review (GCR), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 1-6.
    12. Okhrin, Ostap & Ristig, Alexander & Sheen, Jeffrey R. & Trück, Stefan, 2015. "Conditional systemic risk with penalized copula," SFB 649 Discussion Papers 2015-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Chao, Xiangrui & Ran, Qin & Chen, Jia & Li, Tie & Qian, Qian & Ergu, Daji, 2022. "Regulatory technology (Reg-Tech) in financial stability supervision: Taxonomy, key methods, applications and future directions," International Review of Financial Analysis, Elsevier, vol. 80(C).
    14. Borghesi, Simone & Flori, Andrea, 2018. "EU ETS facets in the net: Structure and evolution of the EU ETS network," Energy Economics, Elsevier, vol. 75(C), pages 602-635.
    15. Asgharian, Hossein & Krygier, Dominika & Vilhelmsson, Anders, 2019. "Systemic Risk and Centrality Revisited: The Role of Interactions," Working Papers 2019:4, Lund University, Department of Economics.
    16. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhang, Wei, 2019. "Financial systemic risk measurement based on causal network connectedness analysis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 290-307.
    17. Matteo Barigozzi & Christian Brownlees, 2015. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona School of Economics.
    18. Du, Zaichao & Escanciano, Juan Carlos & Zhu, Guangwei, 2023. "The case for CASE: Estimating heterogeneous systemic effects," Journal of Banking & Finance, Elsevier, vol. 157(C).
    19. Bierth, Christopher & Irresberger, Felix & Weiß, Gregor N.F., 2015. "Systemic risk of insurers around the globe," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 232-245.
    20. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2020. "Modeling Turning Points In Global Equity Market," DEM Working Papers Series 195, University of Pavia, Department of Economics and Management.
    21. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.
    22. Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2019. "LASSO-Driven Inference in Time and Space," CeMMAP working papers CWP20/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. Wu, JunFeng & Zhang, Chao & Chen, Yun, 2022. "Analysis of risk correlations among stock markets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 83(C).
    24. Ge, S., 2020. "Text-Based Linkages and Local Risk Spillovers in the Equity Market," Cambridge Working Papers in Economics 20115, Faculty of Economics, University of Cambridge.
    25. Wang, Gang-Jin & Si, Hui-Bin & Chen, Yang-Yang & Xie, Chi & Chevallier, Julien, 2021. "Time domain and frequency domain Granger causality networks: Application to China’s financial institutions," Finance Research Letters, Elsevier, vol. 39(C).
    26. Name 1 Dieter Wang Email 1 & Iman (I.P.P.) van Lelyveld & Julia (J.) Schaumburg, 2018. "Do information contagion and business model similarities explain bank credit risk commonalities?," Tinbergen Institute Discussion Papers 18-100/IV, Tinbergen Institute.
    27. Denbee, Edward & Julliard, Christian & Li, Ye & Yuan, Kathy, 2021. "Network risk and key players: A structural analysis of interbank liquidity," Journal of Financial Economics, Elsevier, vol. 141(3), pages 831-859.
    28. Ouyang, Zisheng & Zhou, Xuewei & Wang, Gang-jin & Liu, Shuwen & Lu, Min, 2024. "Multilayer networks in the frequency domain: Measuring volatility connectedness among Chinese financial institutions," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 909-928.
    29. Paolo Giudici & Laura Parisi, 2017. "Sovereign risk in the Euro area: a multivariate stochastic process approach," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1995-2008, December.
    30. Fousekis, Panos & Grigoriadis, Vasilis, 2022. "Conditional tail price risk spillovers in coffee markets across quality, physical space, and time: Empirical analysis with penalized quantile regressions," Economic Modelling, Elsevier, vol. 106(C).
    31. Ouyang, Zisheng & Zhou, Xuewei, 2023. "Interconnected networks: Measuring extreme risk connectedness between China’s financial sector and real estate sector," International Review of Financial Analysis, Elsevier, vol. 90(C).
    32. Power, Michael, 2021. "The financial reporting system - what is it?," LSE Research Online Documents on Economics 110220, London School of Economics and Political Science, LSE Library.
    33. Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019. "Bayesian nonparametric sparse VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
    34. Xu, Qifa & Li, Mengting & Jiang, Cuixia & He, Yaoyao, 2019. "Interconnectedness and systemic risk network of Chinese financial institutions: A LASSO-CoVaR approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    35. Gian Paolo Clemente & Rosanna Grassi & Chiara Pederzoli, 2020. "Networks and market-based measures of systemic risk: the European banking system in the aftermath of the financial crisis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 159-181, January.
    36. De Novellis, G. & Musile Tanzi, P. & Ranalli, M.G. & Stanghellini, E., 2024. "Leveraged finance exposure in the banking system: Systemic risk and interconnectedness," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    37. Honghai Yu & Wencong Sun & Xiangting Ye & Libing Fang, 2019. "Measuring the increasing connectedness of Chinese assets with global assets: using a variance decompositions method," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(5), pages 1261-1290, March.
    38. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    39. Tan, Changchun & Mo, Lingyu & Wu, Xiaomeng & Zhou, Peng, 2024. "Fintech development and corporate credit risk: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 92(C).
    40. Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Jan 2025.
    41. Samuel Ronnqvist & Peter Sarlin, 2013. "From Text to Bank Interrelation Maps," Papers 1306.3856, arXiv.org.
    42. Borghesi, Simone & Flori, Andrea, 2016. "EU ETS Facets in the Net: How Account Types Influence the Structure of the System," MITP: Mitigation, Innovation and Transformation Pathways 232214, Fondazione Eni Enrico Mattei (FEEM).
    43. Fang, Libing & Sun, Boyang & Li, Huijing & Yu, Honghai, 2018. "Systemic risk network of Chinese financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 190-206.
    44. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    45. Panos Fousekis & Dimitra Tzaferi, 2022. "Tail price risk spillovers along the US beef and pork supply chains," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(2), pages 383-399, April.
    46. Bostandzic, Denefa & Weiß, Gregor N.F., 2018. "Why do some banks contribute more to global systemic risk?," Journal of Financial Intermediation, Elsevier, vol. 35(PA), pages 17-40.
    47. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Okhrin, Yarema, 2017. "Tail event driven networks of SIFIs," SFB 649 Discussion Papers 2017-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    48. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," Bank of England working papers 660, Bank of England.
    49. Ahelegbey, Daniel Felix, 2015. "The Econometrics of Bayesian Graphical Models: A Review With Financial Application," MPRA Paper 92634, University Library of Munich, Germany, revised 25 Apr 2016.
    50. Yajie Yang & Longfeng Zhao & Lin Chen & Chao Wang & Jihui Han, 2021. "Portfolio optimization with idiosyncratic and systemic risks for financial networks," Papers 2111.11286, arXiv.org.
    51. Li, Yueshan & Chen, Shoudong & Sensoy, Ahmet & Wang, Lu, 2024. "Over-expected shocks and financial market security: Evidence from China's markets," Research in International Business and Finance, Elsevier, vol. 68(C).
    52. Dingshi Tian & Zongwu Cai & Ying Fang, 2018. "Econometric Modeling of Risk Measures: A Selective Review of the Recent Literature," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201807, University of Kansas, Department of Economics, revised Oct 2018.
    53. Matteo Barigozzi & Marc Hallin, 2017. "A network analysis of the volatility of high dimensional financial series," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(3), pages 581-605, April.
    54. Xu, Hao & Li, Songsong, 2023. "What impacts foreign capital flows to China's stock markets? Evidence from financial risk spillover networks," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 559-577.
    55. Pierret, D., 2013. "The systemic risk of energy markets," LIDAM Discussion Papers ISBA 2013061, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    56. Foglia, Matteo & Addi, Abdelhamid & Angelini, Eliana, 2022. "The Eurozone banking sector in the time of COVID-19: Measuring volatility connectedness," Global Finance Journal, Elsevier, vol. 51(C).
    57. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    58. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
    59. Peralta, Gustavo & Zareei, Abalfazl, 2016. "A network approach to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 157-180.
    60. Craig, Ben & Karamysheva, Madina & Salakhova, Dilyara, 2023. "Do market-based networks reflect true exposures between banks?," Working Paper Series 2867, European Central Bank.
    61. He, Zhipeng & Zhang, Shuguang, 2024. "Risk contagion and diversification among sovereign CDS, stock, foreign exchange and commodity markets: Fresh evidence from G7 and BRICS countries," Finance Research Letters, Elsevier, vol. 62(PB).
    62. Mengting Li & Qifa Xu & Cuixia Jiang & Yezheng Liu, 2024. "The role of long‐ and short‐run correlation networks in international portfolio selection," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3147-3176, July.
    63. Ahelegbey, Daniel Felix & Giudici, Paolo & Hashem, Shatha Qamhieh, 2021. "Network VAR models to measure financial contagion," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    64. Samuel Ronnqvist & Peter Sarlin, 2014. "Bank Networks from Text: Interrelations, Centrality and Determinants," Papers 1406.7752, arXiv.org, revised Jul 2015.
    65. Geraci, Marco Valerio & Gnabo, Jean-Yves, 2018. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1371-1390, June.
    66. Daniel Felix Ahelegbey, 2022. "Statistical Modelling of Downside Risk Spillovers," FinTech, MDPI, vol. 1(2), pages 1-10, April.
    67. Deng, Yang & Zhang, Ziqing & Zhu, Li, 2021. "A model-based index for systemic risk contribution measurement in financial networks," Economic Modelling, Elsevier, vol. 95(C), pages 35-48.
    68. Ellis, Scott & Sharma, Satish & Brzeszczyński, Janusz, 2022. "Systemic risk measures and regulatory challenges," Journal of Financial Stability, Elsevier, vol. 61(C).
    69. Ouyang, Zisheng & Zhou, Xuewei & Lu, Min & Liu, Ke, 2024. "Imported financial risk in global stock markets: Evidence from the interconnected network," Research in International Business and Finance, Elsevier, vol. 69(C).
    70. Yu Chen & Jie Hu & Weiping Zhang, 2020. "Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(6), pages 78-100, November.
    71. Wang, Wei & Xu, Huifu & Ma, Tiejun, 2023. "Optimal scenario-dependent multivariate shortfall risk measure and its application in risk capital allocation," European Journal of Operational Research, Elsevier, vol. 306(1), pages 322-347.
    72. Yang Deng & Chenyin Gao, 2023. "Where does the risk lie? Systemic risk and tail risk networks in the Chinese financial market," Pacific Economic Review, Wiley Blackwell, vol. 28(2), pages 167-190, May.
    73. Brownlees, Christian & Engle, Robert F., 2017. "SRISK: a conditional capital shortfall measure of systemic risk," ESRB Working Paper Series 37, European Systemic Risk Board.
    74. Wang, Ze & Gao, Xiangyun & Huang, Shupei & Sun, Qingru & Chen, Zhihua & Tang, Renwu & Di, Zengru, 2022. "Measuring systemic risk contribution of global stock markets: A dynamic tail risk network approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
    75. Bianchi, Daniele & Billio, Monica & Casarin, Roberto & Guidolin, Massimo, 2019. "Modeling systemic risk with Markov Switching Graphical SUR models," Journal of Econometrics, Elsevier, vol. 210(1), pages 58-74.
    76. Chen, Ning & Li, Shaofang & Lu, Shuai, 2023. "The extreme risk connectedness of the global financial system: G7 and BRICS evidence," Journal of Multinational Financial Management, Elsevier, vol. 69(C).
    77. Yan, Guan & Liu, Zhidong, 2023. "Interconnectedness of financial institutions based on pledged shares in China," Finance Research Letters, Elsevier, vol. 57(C).
    78. Hong Fan & Allan Alvin Lee Lukaya Amalia & Qian Qian Gao, 2018. "The Assessment of Systemic Risk in the Kenyan Banking Sector," Complexity, Hindawi, vol. 2018, pages 1-15, January.
    79. Härdle, Wolfgang Karl & Wang, Weining & Yu, Lining, 2016. "TENET: Tail-Event driven NETwork risk," Journal of Econometrics, Elsevier, vol. 192(2), pages 499-513.
    80. Grzegorz Halaj & Ruben Hipp, 2024. "Decomposing Systemic Risk: The Roles of Contagion and Common Exposures," Staff Working Papers 24-19, Bank of Canada.
    81. Rui Ding & Siwei Shen & Yuqi Zhu & Linyu Du & Shihui Chen & Juan Liang & Kexing Wang & Wenqian Xiao & Yuxuan Hong, 2023. "Evolution, Forecasting, and Driving Mechanisms of the Digital Financial Network: Evidence from China," Sustainability, MDPI, vol. 15(22), pages 1-18, November.
    82. Huang, Wei-Qiang & Zhuang, Xin-Tian & Yao, Shuang & Uryasev, Stan, 2016. "A financial network perspective of financial institutions’ systemic risk contributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 183-196.
    83. Linh H. Nguyen & Linh X. D. Nguyen & Linzhi Tan, 2021. "Tail risk connectedness between US industries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3624-3650, July.
    84. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Forecasting systemic impact in financial networks," SFB 649 Discussion Papers 2013-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    85. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    86. Tobias Eckernkemper, 2018. "Modeling Systemic Risk: Time-Varying Tail Dependence When Forecasting Marginal Expected Shortfall," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 63-117.
    87. Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2022. "Assessing the impact of policy and regulation interventions in European sovereign credit risk networks: What worked best?," Journal of International Economics, Elsevier, vol. 139(C).
    88. Das, Sanjiv R. & Kalimipalli, Madhu & Nayak, Subhankar, 2022. "Banking networks, systemic risk, and the credit cycle in emerging markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    89. Gong, Xu & Liao, Qin, 2024. "Physical climate risk attention and dynamic volatility connectedness among new energy stocks," Energy Economics, Elsevier, vol. 136(C).
    90. Yao, Yinhong & Li, Jianping & Sun, Xiaolei, 2021. "Measuring the risk of Chinese Fintech industry: evidence from the stock index," Finance Research Letters, Elsevier, vol. 39(C).
    91. Bernardi Mauro & Roy Cerqueti & Arsen Palestini, 2016. "Allocation of risk capital in a cost cooperative game induced by a modified Expected Shortfall," Papers 1608.02365, arXiv.org.
    92. Roman Mestre, 2023. "Stock profiling using time–frequency-varying systematic risk measure," Post-Print hal-04058285, HAL.
    93. Bing‐Yue Liu & Qiang Ji & Duc Khuong Nguyen & Ying Fan, 2021. "Dynamic dependence and extreme risk comovement: The case of oil prices and exchange rates," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2612-2636, April.
    94. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang, 2021. "Financial Risk Meter based on expectiles," IRTG 1792 Discussion Papers 2021-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    95. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
    96. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, vol. 7(1), pages 1-25, January.
    97. Betz, Frank & Hautsch, Nikolaus & Peltonen, Tuomas A. & Schienle, Melanie, 2016. "Systemic risk spillovers in the European banking and sovereign network," Working Paper Series in Economics 79, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    98. Chen, Yan & Mo, Dongxu & Xu, Zezhou, 2022. "A study of interconnections and contagion among Chinese financial institutions using a ΔCoV aR network," Finance Research Letters, Elsevier, vol. 45(C).
    99. M. Bernardi & L. Petrella, 2014. "Interconnected risk contributions: an heavy-tail approach to analyse US financial sectors," Papers 1401.6408, arXiv.org, revised Apr 2014.
    100. Chabot, Miia & Bertrand, Jean-Louis, 2021. "Complexity, interconnectedness and stability: New perspectives applied to the European banking system," Journal of Business Research, Elsevier, vol. 129(C), pages 784-800.
    101. Jian, Zhihong & Li, Xupei, 2021. "Skewness-based market integration: A systemic risk measure across international equity markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    102. Carlos Castro & Stijn Ferrari, 2011. "Measuring and testing for the systemically important financial institutions," Documentos de Trabajo 8779, Universidad del Rosario.
    103. Addi, Abdelhamid & Bouoiyour, Jamal, 2023. "Interconnectedness and extreme risk: Evidence from dual banking systems," Economic Modelling, Elsevier, vol. 120(C).
    104. Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
    105. Wu, Shan & Tong, Mu & Yang, Zhongyi & Zhang, Tianyi, 2021. "Interconnectedness, systemic risk, and the influencing factors: Some evidence from China’s financial institutions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    106. Qicheng Zhao & Zhouwei Wang & Yuping Song, 2024. "Systematic Research on Multi-dimensional and Multiple Correlation Contagion Networks of Extreme Risk in China’s Banking Industry," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1137-1162, August.
    107. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    108. Zongwu Cai & Ying Fang & Dingshi Tian, 2024. "CAViaR Model Selection Via Adaptive Lasso," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202403, University of Kansas, Department of Economics, revised Jan 2024.
    109. Ahmad, Wasim & Tiwari, Shiv Ratan & Wadhwani, Akshay & Khan, Mohammad Azeem & Bekiros, Stelios, 2023. "Financial networks and systemic risk vulnerabilities: A tale of Indian banks," Research in International Business and Finance, Elsevier, vol. 65(C).
    110. Arnold Polanski & Evarist Stoja & Ching‐Wai (Jeremy) Chiu, 2021. "Tail risk interdependence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5499-5511, October.
    111. Mengting Li & Qifa Xu & Cuixia Jiang & Qinna Zhao, 2023. "The role of tail network topological characteristic in portfolio selection: A TNA‐PMC model," International Review of Finance, International Review of Finance Ltd., vol. 23(1), pages 37-57, March.
    112. Casarin, Roberto & Costola, Michele & Yenerdag, Erdem, 2018. "Financial bridges and network communities," SAFE Working Paper Series 208, Leibniz Institute for Financial Research SAFE, revised 2018.
    113. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Okhrin, Yarema, 2019. "Tail event driven networks of SIFIs," Journal of Econometrics, Elsevier, vol. 208(1), pages 282-298.
    114. Karim, Sitara & Shafiullah, Muhammad & Naeem, Muhammad Abubakr, 2024. "When one domino falls, others follow: A machine learning analysis of extreme risk spillovers in developed stock markets," International Review of Financial Analysis, Elsevier, vol. 93(C).
    115. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    116. Zbonakova, L. & Härdle, W.K. & Wang, W., 2016. "Time Varying Quantile Lasso," Working Papers 16/07, Department of Economics, City University London.
    117. Giulia Masi & Giorgio Ricchiuti, 2020. "From FDI network topology to macroeconomic instability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 133-158, January.
    118. Gong, Xiao-Li & Liu, Jian-Min & Xiong, Xiong & Zhang, Wei, 2022. "Research on stock volatility risk and investor sentiment contagion from the perspective of multi-layer dynamic network," International Review of Financial Analysis, Elsevier, vol. 84(C).
    119. Cincinelli, Peter & Pellini, Elisabetta & Urga, Giovanni, 2022. "Systemic risk in the Chinese financial system: A panel Granger causality analysis," International Review of Financial Analysis, Elsevier, vol. 82(C).
    120. Cai, Jian & Eidam, Frederik & Saunders, Anthony & Steffen, Sascha, 2018. "Syndication, interconnectedness, and systemic risk," Journal of Financial Stability, Elsevier, vol. 34(C), pages 105-120.
    121. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    122. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto Calogero, 2017. "Estimation and model-based combination of causality networks," SAFE Working Paper Series 165, Leibniz Institute for Financial Research SAFE.
    123. Paolo Giudici & Peter Sarlin & Alessandro Spelta, 2016. "The multivariate nature of systemic risk: direct and common exposures," DEM Working Papers Series 118, University of Pavia, Department of Economics and Management.
    124. Hałaj, Grzegorz & Hipp, Ruben, 2024. "Decomposing systemic risk: the roles of contagion and common exposures," Working Paper Series 2929, European Central Bank.
    125. Naeem, Muhammad Abubakr & Yousaf, Imran & Karim, Sitara & Yarovaya, Larisa & Ali, Shoaib, 2023. "Tail-event driven NETwork dependence in emerging markets," Emerging Markets Review, Elsevier, vol. 55(C).
    126. Muzi Chen & Yuhang Wang & Boyao Wu & Difang Huang, 2024. "Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information Entropy," Papers 2403.19439, arXiv.org.
    127. Huang, Wei-Qiang & Wang, Dan, 2018. "A return spillover network perspective analysis of Chinese financial institutions’ systemic importance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 405-421.
    128. Bluhm, Marcel & Krahnen, Jan Pieter, 2014. "Systemic risk in an interconnected banking system with endogenous asset markets," Journal of Financial Stability, Elsevier, vol. 13(C), pages 75-94.
    129. Alexandre Belloni & Victor Chernozhukov & Abhishek Kaul, 2017. "Confidence bands for coefficients in high dimensional linear models with error-in-variables," CeMMAP working papers 22/17, Institute for Fiscal Studies.
    130. Zhang, Xingmin & Zhang, Shuai & Lu, Liping, 2022. "The banking instability and climate change: Evidence from China," Energy Economics, Elsevier, vol. 106(C).
    131. Peltonen, Tuomas A. & Sarlin, Peter & Piloiu, Andreea, 2015. "Network linkages to predict bank distress," Working Paper Series 1828, European Central Bank.
    132. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    133. Simone Varotto & Lei Zhao, 2014. "Systemic Risk and Bank Size," ICMA Centre Discussion Papers in Finance icma-dp2014-17, Henley Business School, University of Reading.
    134. Xue Cui & Lu Yang, 2024. "Systemic risk and idiosyncratic networks among global systemically important banks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 58-75, January.
    135. Zhou, Dong-hai & Liu, Xiao-xing, 2024. "Does systemic risk in the fund markets predict future economic downturns?," International Review of Financial Analysis, Elsevier, vol. 92(C).
    136. Joerg Osterrieder & Stephen Chan & Jeffrey Chu & Yuanyuan Zhang & Branka Hadji Misheva & Codruta Mare, 2024. "Enhancing Security in Blockchain Networks: Anomalies, Frauds, and Advanced Detection Techniques," Papers 2402.11231, arXiv.org.
    137. Chao, Shih-kang & Härdle, Wolfgang Karl & Hien, Pham-thu, 2014. "Credit risk calibration based on CDS spreads," SFB 649 Discussion Papers 2014-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    138. Polanski, Arnold & Stoja, Evarist, 2015. "Extreme risk interdependence," Bank of England working papers 563, Bank of England.
    139. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
    140. Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: a network analysis," ESRB Working Paper Series 90, European Systemic Risk Board.
    141. Ning, Wei & Zhao, Jiahua & Jiang, Fuwei, 2024. "ETFs and tail dependence: Evidence from Chinese stock market," Journal of International Money and Finance, Elsevier, vol. 149(C).
    142. Jondeau, Eric & Khalilzadeh, Amir, 2022. "Predicting the stressed expected loss of large U.S. banks," Journal of Banking & Finance, Elsevier, vol. 134(C).
    143. Hué, Sullivan & Lucotte, Yannick & Tokpavi, Sessi, 2019. "Measuring network systemic risk contributions: A leave-one-out approach," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 86-114.
    144. Anna Denkowska & Stanisław Wanat, 2020. "A Tail Dependence-Based MST and Their Topological Indicators in Modeling Systemic Risk in the European Insurance Sector," Risks, MDPI, vol. 8(2), pages 1-22, April.
    145. Doğan, Buhari & Ben Jabeur, Sami & Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins, 2025. "Asymmetry in returns and volatility between green financial assets, sustainable investments, clean energy, and international stock markets," Research in International Business and Finance, Elsevier, vol. 73(PA).
    146. Lavín, Jaime F. & Valle, Mauricio A. & Magner, Nicolás S., 2024. "Stock market pattern recognition using symbol entropy analysis," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    147. Zhang, Weiping & Zhuang, Xintian & Wang, Jian & Lu, Yang, 2020. "Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    148. Naeem, Muhammad Abubakr, 2024. "Navigating median and extreme volatility in stock markets: Implications for portfolio strategies," International Review of Economics & Finance, Elsevier, vol. 95(C).
    149. Zbonakova, Lenka & Härdle, Wolfgang Karl & Wang, Weining, 2016. "Time varying quantile Lasso," SFB 649 Discussion Papers 2016-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    150. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    151. Huang, Wei-Qiang & Wang, Dan, 2020. "Financial network linkages to predict economic output," Finance Research Letters, Elsevier, vol. 33(C).
    152. Ren, Yinghua & Zhao, Wanru & You, Wanhai & Zhu, Huiming, 2022. "Multiscale features of extreme risk spillover networks among global stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    153. Haiming Long & Ji Zhang & Nengyu Tang, 2017. "Does network topology influence systemic risk contribution? A perspective from the industry indices in Chinese stock market," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-19, July.
    154. Tian, Sihua & Li, Shaofang & Gu, Qinen, 2023. "Measurement and contagion modelling of systemic risk in China's financial sectors: Evidence for functional data analysis and complex network," International Review of Financial Analysis, Elsevier, vol. 90(C).
    155. Ayoub Kyoud & Cherif El Msiyah & Jaouad Madkour, 2023. "Modelling Systemic Risk in Morocco’s Banking System," IJFS, MDPI, vol. 11(2), pages 1-16, May.
    156. Yu, Lining & Härdle, Wolfgang Karl & Borke, Lukas & Benschop, Thijs, 2017. "FRM: A financial risk meter based on penalizing tail events occurrence," SFB 649 Discussion Papers 2017-003, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    157. Deng, Chao & Su, Xiaojian & Wang, Gangjin & Peng, Cheng, 2022. "The existence of flight-to-quality under extreme conditions: Evidence from a nonlinear perspective in Chinese stocks and bonds' sectors," Economic Modelling, Elsevier, vol. 113(C).
    158. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    159. Wang, Gang-Jin & Jiang, Zhi-Qiang & Lin, Min & Xie, Chi & Stanley, H. Eugene, 2018. "Interconnectedness and systemic risk of China's financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 1-18.
    160. Cristina Zeldea, 2020. "Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions," Administrative Sciences, MDPI, vol. 10(3), pages 1-14, August.
    161. Weiß, Gregor N.F. & Mühlnickel, Janina, 2014. "Why do some insurers become systemically relevant?," Journal of Financial Stability, Elsevier, vol. 13(C), pages 95-117.
    162. Wang, Weining & Yu, Lining & Wang, Bingling, 2020. "Tail Event Driven Factor Augmented Dynamic Model," IRTG 1792 Discussion Papers 2020-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    163. Feng, Yusen & Wang, Gang-Jin & Zhu, You & Xie, Chi, 2023. "Systemic risk spillovers and the determinants in the stock markets of the Belt and Road countries," Emerging Markets Review, Elsevier, vol. 55(C).
    164. Pham, Thach N. & Powell, Robert & Bannigidadmath, Deepa, 2024. "Tail risk network analysis of Asian banks," Global Finance Journal, Elsevier, vol. 62(C).
    165. Jiang, Cuixia & Li, Yuqian & Xu, Qifa & Liu, Yezheng, 2021. "Measuring risk spillovers from multiple developed stock markets to China: A vine-copula-GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 386-398.
    166. Chao, Shih-Kang & Härdle, Wolfgang Karl & Wang, Weining, 2012. "Quantile regression in risk calibration," SFB 649 Discussion Papers 2012-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    167. Sullivan HUE & Yannick LUCOTTE & Sessi TOKPAVI, 2018. "Measuring Network Systemic Risk Contributions: A Leave-one-out Approach," LEO Working Papers / DR LEO 2608, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    168. Ouyang, Zisheng & Zhou, Xuewei, 2023. "Multilayer networks in the frequency domain: Measuring extreme risk connectedness of Chinese financial institutions," Research in International Business and Finance, Elsevier, vol. 65(C).
    169. Sarlin, Peter & Rönnqvist, Samuel, 2016. "Bank networks from text: interrelations, centrality and determinants," Working Paper Series 1876, European Central Bank.
    170. Liang, Qi & Lu, Yanchen & Li, Zheng, 2020. "Business connectedness or market risk? Evidence from financial institutions in China," China Economic Review, Elsevier, vol. 62(C).
    171. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    172. Jian, Zhihong & Lu, Haisong & Zhu, Zhican & Xu, Huiling, 2023. "Frequency heterogeneity of tail connectedness: Evidence from global stock markets," Economic Modelling, Elsevier, vol. 125(C).
    173. Trenca Ioan & Petria Nicolae & Corovei Emilia, 2015. "Idiosyncratic Risk And Systemic Risk In The European Banking System," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 912-919, July.
    174. Su, Zhi & Xu, Fuwei, 2021. "Dynamic identification of systemically important financial markets in the spread of contagion: A ripple network based collective spillover effect approach," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    175. Baltakienė, Margarita & Kanniainen, Juho & Baltakys, Kęstutis, 2021. "Identification of information networks in stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    176. Marcin Łupiński, 2019. "Wskaźniki wczesnego ostrzegania przed niestabilnością finansową polskiego sektora bankowego," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 55, pages 99-113.
    177. Uddin, Gazi Salah & Luo, Tianqi & Yahya, Muhammad & Jayasekera, Ranadeva & Rahman, Md Lutfur & Okhrin, Yarema, 2023. "Risk network of global energy markets," Energy Economics, Elsevier, vol. 125(C).
    178. Foglia, Matteo & Addi, Abdelhamid & Wang, Gang-Jin & Angelini, Eliana, 2022. "Bearish Vs Bullish risk network: A Eurozone financial system analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    179. Wang, Dan & Huang, Wei-Qiang, 2021. "Centrality-based measures of financial institutions’ systemic importance: A tail dependence network view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    180. Myšičková, Alena & Song, Song & Majer, Piotr & Mohr, Peter N. C. & Heekeren, Hauke R. & Härdle, Wolfgang Karl, 2011. "Risk patterns and correlated brain activities: Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers 2011-085, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    181. Samuel R�nnqvist & Peter Sarlin, 2015. "Bank networks from text: interrelations, centrality and determinants," Quantitative Finance, Taylor & Francis Journals, vol. 15(10), pages 1619-1635, October.
    182. Sla{dj}ana Babi'c & Christophe Ley & Lorenzo Ricci & David Veredas, 2020. "TailCoR," Papers 2011.14817, arXiv.org.
    183. Nicolás Magner & Jaime F. Lavín & Mauricio A. Valle, 2022. "Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach," Mathematics, MDPI, vol. 10(19), pages 1-30, October.
    184. Nguyen, Linh Hoang & Lambe, Brendan John, 2021. "International tail risk connectedness: Network and determinants," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    185. Fousekis, Panos, 2022. "Price risk connectedness in the principal olive oil markets of the EU," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    186. Yu, Jia-Wei & Xie, Wen-Jie & Jiang, Zhi-Qiang, 2018. "Early warning model based on correlated networks in global crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1335-1343.
    187. Daning Hu & Gerhard Schwabe & Xiao Li, 2015. "Systemic risk management and investment analysis with financial network analytics: research opportunities and challenges," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-9, December.
    188. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    189. Maghyereh, Aktham & Abdoh, Hussein, 2024. "Tail risk connectedness among GCC banks episodes from the Global Financial Crisis to COVID-19 pandemic," The Quarterly Review of Economics and Finance, Elsevier, vol. 96(C).
    190. Liu, Zixin & Hu, Jun & Zhang, Shuguang & He, Zhipeng, 2024. "Risk spillovers among oil, gold, stock, and foreign exchange markets: Evidence from G20 economies," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    191. Kraft, Holger & Schmidt, Alexander, 2013. "Systemic risk in the financial sector: What can se learn from option markets?," SAFE Working Paper Series 25, Leibniz Institute for Financial Research SAFE.
    192. Nistor Simona, 2017. "Banks’ Vulnerability and Financial Openness across Central and Eastern Europe," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, vol. 62(3), pages 47-66, December.
    193. Geert Mesters & Christian Brownlees, 2017. "Detecting Granular Time Series in Large Panels," Working Papers 991, Barcelona School of Economics.
    194. Xin Yang & Shan Chen & Hong Liu & Xiaoguang Yang & Chuangxia Huang, 2023. "Jump volatility spillover network based measurement of systemic importance of Chinese financial institutions," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1201-1213, April.
    195. Keilbar, Georg & Wang, Weining, 2019. "Modelling Systemic Risk Using Neural Network Quantile Regression," IRTG 1792 Discussion Papers 2019-019, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    196. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    197. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
    198. Yaya Su & Zhehao Huang & Benjamin M. Drakeford, 2019. "Monetary Policy, Industry Heterogeneity and Systemic Risk—Based on a High Dimensional Network Analysis," Sustainability, MDPI, vol. 11(22), pages 1-15, November.
    199. Emanuele De Meo & Giacomo Tizzanini, 2021. "GDP‐network CoVaR: A tool for assessing growth‐at‐risk," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 50(2), July.
    200. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    201. Liu, Bing-Yue & Fan, Ying & Ji, Qiang & Hussain, Nazim, 2022. "High-dimensional CoVaR network connectedness for measuring conditional financial contagion and risk spillovers from oil markets to the G20 stock system," Energy Economics, Elsevier, vol. 105(C).
    202. Abendschein, Michael & Grundke, Peter, 2018. "On the ranking consistency of global systemic risk measures: empirical evidence," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181623, Verein für Socialpolitik / German Economic Association.
    203. Chen, Yan & Wang, Gang-Jin & Zhu, You & Xie, Chi & Uddin, Gazi Salah, 2023. "Quantile connectedness and the determinants between FinTech and traditional financial institutions: Evidence from China," Global Finance Journal, Elsevier, vol. 58(C).
    204. Fang, Ming & Taylor, Stephen & Uddin, Ajim, 2022. "The network structure of overnight index swap rates," Finance Research Letters, Elsevier, vol. 46(PB).
    205. Gao, Haoyu & Ouyang, Yiling & Wang, Yaxin, 2024. "Corporate bond defaults and spillover effects on bank risk: Evidence from city commercial banks in China," Research in International Business and Finance, Elsevier, vol. 69(C).
    206. Xu, Qiuhua & Yan, Haoyang & Zhao, Tianyu, 2022. "Contagion effect of systemic risk among industry sectors in China’s stock market," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    207. Paolo Giudici & Laura Parisi, 2015. "Modeling Systemic Risk with Correlated Stochastic Processes," DEM Working Papers Series 110, University of Pavia, Department of Economics and Management.
    208. Badics, Milan Csaba & Huszar, Zsuzsa R. & Kotro, Balazs B., 2023. "The impact of crisis periods and monetary decisions of the Fed and the ECB on the sovereign yield curve network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    209. Foglia, Matteo & Angelini, Eliana, 2020. "From me to you: Measuring connectedness between Eurozone financial institutions," Research in International Business and Finance, Elsevier, vol. 54(C).
    210. Frank Emmert-Streib & Aliyu Musa & Kestutis Baltakys & Juho Kanniainen & Shailesh Tripathi & Olli Yli-Harja & Herbert Jodlbauer & Matthias Dehmer, 2017. "Computational Analysis of the structural properties of Economic and Financial Networks," Papers 1710.04455, arXiv.org.
    211. Nadine M Walters & Conrad Beyers & Gusti van Zyl & Rolf van den Heever, 2018. "A framework for simulating systemic risk and its application to the South African banking sector," Papers 1811.04223, arXiv.org.
    212. Lining Yu & Wolfgang Karl Hardle & Lukas Borke & Thijs Benschop, 2020. "An AI approach to measuring financial risk," Papers 2009.13222, arXiv.org.
    213. Zhu, Bo & Deng, Yuanyue & Lin, Renda & Hu, Xin & Chen, Pingshe, 2022. "Energy security: Does systemic risk spillover matter? Evidence from China," Energy Economics, Elsevier, vol. 114(C).
    214. Atasoy, Burak Sencer & Özkan, İbrahim & Erden, Lütfi, 2024. "The determinants of systemic risk contagion," Economic Modelling, Elsevier, vol. 130(C).
    215. Fuwei Xu, 2024. "Modeling the Paths of China’s Systemic Financial Risk Contagion: A Ripple Network Perspective Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 47-73, January.
    216. Zhang, Weiping & Zhuang, Xintian & Lu, Yang & Wang, Jian, 2020. "Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework," International Review of Financial Analysis, Elsevier, vol. 71(C).
    217. Diebold, Francis X. & Yılmaz, Kamil, 2023. "Reprint of: On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 234(S), pages 70-90.
    218. Du, Ruijin & Dong, Gaogao & Tian, Lixin & Wang, Yougui & Zhao, Longfeng & Zhang, Xin & Vilela, André L.M. & Stanley, H. Eugene, 2019. "Identifying the peak point of systemic risk in international crude oil importing trade," Energy, Elsevier, vol. 176(C), pages 281-291.
    219. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARS," Working Papers ECARES ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    220. Wang, Gang-Jin & Chen, Yan & Zhu, You & Xie, Chi, 2024. "Systemic risk prediction using machine learning: Does network connectedness help prediction?," International Review of Financial Analysis, Elsevier, vol. 93(C).
    221. Zhou, Dong-hai & Liu, Xiao-xing & Tang, Chun & Yang, Guang-yi, 2023. "Time-varying risk spillovers in Chinese stock market – New evidence from high-frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    222. Daniel Felix Ahelegbey, 2015. "The Econometrics of Networks: A Review," Working Papers 2015:13, Department of Economics, University of Venice "Ca' Foscari".
    223. Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020. "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series 181, University of Pavia, Department of Economics and Management.
    224. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.
    225. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).
    226. Wu, Baohui & Zhu, Pingheng & Yin, Hua & Wen, Fenghua, 2023. "The risk spillover of high carbon enterprises in China: Evidence from the stock market," Energy Economics, Elsevier, vol. 126(C).
    227. Li, Yanshuang & Zhuang, Xintian & Wang, Jian, 2021. "Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    228. Ko, Bonggyun & Song, Jae Wook, 2018. "A simple analytics framework for evaluating mean escape time in different term structures with stochastic volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 398-412.
    229. Huang, Wei-Qiang & Wang, Dan, 2018. "Systemic importance analysis of chinese financial institutions based on volatility spillover network," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 19-30.

  30. Hautsch, Nikolaus & Kyj, Lada M. & Malec, Peter, 2011. "The merit of high-frequency data in portfolio allocation," SFB 649 Discussion Papers 2011-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Fengler, Matthias R. & Okhrin, Ostap, 2012. "Realized copula," SFB 649 Discussion Papers 2012-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.
    3. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2014. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers 2014-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Muhammad Ali Nasir & Milton Yago & Alaa M. Soliman & Junjie Wu, 2016. "Financial stability, wealth effects and optimal macroeconomic policy combination in the United Kingdom: A new-Keynesian dynamic stochastic general equilibrium framework," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1136098-113, December.
    7. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Roxana Halbleib & Valeri Voev, 2011. "Forecasting Covariance Matrices: A Mixed Frequency Approach," CREATES Research Papers 2011-03, Department of Economics and Business Economics, Aarhus University.
    9. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Heyne, Gregor & Kupper, Michael & Mainberger, Christoph, 2011. "Minimal supersolutions of BSDEs with lower semicontinuous generations," SFB 649 Discussion Papers 2011-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    11. Muhammad Ali Nasir & Alaa M. Soliman & Milton Yago & Junjie Wu, 2016. "Macroeconomic Policies Interaction & the Symmetry of Financial Markets’ Responses," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 5(1), pages 53-69.
    12. Muhammad Ali Nasir & Alaa M. Soliman & Muhammad Shahbaz, 2021. "Operational aspect of the policy coordination for financial stability: role of Jeffreys–Lindley’s paradox in operations research," Annals of Operations Research, Springer, vol. 306(1), pages 57-81, November.
    13. Tischer, Sven & Hildebrandt, Lutz, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers 2011-065, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Schneider, Dorothee, 2011. "The labor share: A review of theory and evidence," SFB 649 Discussion Papers 2011-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Bannouh, K. & Martens, M.P.E. & Oomen, R.C.A. & van Dijk, D.J.C., 2012. "Realized mixed-frequency factor models for vast dimensional covariance estimation," ERIM Report Series Research in Management ERS-2012-017-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    16. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    17. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
    18. Myšičková, Alena & Song, Song & Majer, Piotr & Mohr, Peter N. C. & Heekeren, Hauke R. & Härdle, Wolfgang Karl, 2011. "Risk patterns and correlated brain activities: Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers 2011-085, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Muhammad Ali Nasir & Alaa M. Soliman, 2014. "Aspects of Macroeconomic Policy Combinations and Their Effects on Financial Markets," Economic Issues Journal Articles, Economic Issues, vol. 19(1), pages 95-118, March.
    20. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    21. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 383-417.

  31. Hautsch, Nikolaus & Huang, Ruihong, 2011. "Limit order flow, market impact and optimal order sizes: Evidence from NASDAQ TotalView-ITCH data," SFB 649 Discussion Papers 2011-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," CFS Working Paper Series 2009/23, Center for Financial Studies (CFS).
    2. Anastasia Bugaenko, 2020. "Empirical Study of Market Impact Conditional on Order-Flow Imbalance," Papers 2004.08290, arXiv.org, revised Apr 2020.
    3. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.
    4. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2014. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers 2014-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Chen, Shi & Härdle, Wolfgang & Schienle, Melanie, 2021. "High-dimensional statistical learning techniques for time-varying limit order book networks," IRTG 1792 Discussion Papers 2021-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    9. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Martin Theissen & Sebastian M. Krause & Thomas Guhr, 2017. "Regularities and irregularities in order flow data," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 90(11), pages 1-9, November.
    11. Heyne, Gregor & Kupper, Michael & Mainberger, Christoph, 2011. "Minimal supersolutions of BSDEs with lower semicontinuous generations," SFB 649 Discussion Papers 2011-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Cebiroğlu, Gökhan & Horst, Ulrich, 2011. "Optimal display of Iceberg orders," SFB 649 Discussion Papers 2011-057, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Tischer, Sven & Hildebrandt, Lutz, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers 2011-065, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Schneider, Dorothee, 2011. "The labor share: A review of theory and evidence," SFB 649 Discussion Papers 2011-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Aaron Wheeler & Jeffrey D. Varner, 2024. "MarketGPT: Developing a Pre-trained transformer (GPT) for Modeling Financial Time Series," Papers 2411.16585, arXiv.org.
    16. Xintong Wang & Christopher Hoang & Yevgeniy Vorobeychik & Michael P. Wellman, 2021. "Spoofing the Limit Order Book: A Strategic Agent-Based Analysis," Games, MDPI, vol. 12(2), pages 1-43, May.
    17. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    18. Myšičková, Alena & Song, Song & Majer, Piotr & Mohr, Peter N. C. & Heekeren, Hauke R. & Härdle, Wolfgang Karl, 2011. "Risk patterns and correlated brain activities: Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers 2011-085, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    20. Kratz, Peter & Schöneborn, Torsten, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers 2011-058, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    21. Xuefeng Gao & S. J. Deng, 2014. "Hydrodynamic limit of order book dynamics," Papers 1411.7502, arXiv.org, revised Feb 2016.

  32. Hautsch, Nikolaus & Kyj, Lada M. & Malec, Peter, 2011. "The merit of high-frequency data in portfolio allocation," SFB 649 Discussion Papers 2011-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Fengler, Matthias R. & Okhrin, Ostap, 2012. "Realized copula," SFB 649 Discussion Papers 2012-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.
    3. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2014. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers 2014-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Muhammad Ali Nasir & Milton Yago & Alaa M. Soliman & Junjie Wu, 2016. "Financial stability, wealth effects and optimal macroeconomic policy combination in the United Kingdom: A new-Keynesian dynamic stochastic general equilibrium framework," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1136098-113, December.
    7. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Roxana Halbleib & Valeri Voev, 2011. "Forecasting Covariance Matrices: A Mixed Frequency Approach," CREATES Research Papers 2011-03, Department of Economics and Business Economics, Aarhus University.
    9. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Heyne, Gregor & Kupper, Michael & Mainberger, Christoph, 2011. "Minimal supersolutions of BSDEs with lower semicontinuous generations," SFB 649 Discussion Papers 2011-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    11. Muhammad Ali Nasir & Alaa M. Soliman & Milton Yago & Junjie Wu, 2016. "Macroeconomic Policies Interaction & the Symmetry of Financial Markets’ Responses," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 5(1), pages 53-69.
    12. Muhammad Ali Nasir & Alaa M. Soliman & Muhammad Shahbaz, 2021. "Operational aspect of the policy coordination for financial stability: role of Jeffreys–Lindley’s paradox in operations research," Annals of Operations Research, Springer, vol. 306(1), pages 57-81, November.
    13. Tischer, Sven & Hildebrandt, Lutz, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers 2011-065, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Schneider, Dorothee, 2011. "The labor share: A review of theory and evidence," SFB 649 Discussion Papers 2011-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Bannouh, K. & Martens, M.P.E. & Oomen, R.C.A. & van Dijk, D.J.C., 2012. "Realized mixed-frequency factor models for vast dimensional covariance estimation," ERIM Report Series Research in Management ERS-2012-017-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    16. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    17. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
    18. Myšičková, Alena & Song, Song & Majer, Piotr & Mohr, Peter N. C. & Heekeren, Hauke R. & Härdle, Wolfgang Karl, 2011. "Risk patterns and correlated brain activities: Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers 2011-085, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Muhammad Ali Nasir & Alaa M. Soliman, 2014. "Aspects of Macroeconomic Policy Combinations and Their Effects on Financial Markets," Economic Issues Journal Articles, Economic Issues, vol. 19(1), pages 95-118, March.
    20. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    21. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 383-417.

  33. Hautsch, Nikolaus & Huang, Ruihong, 2011. "Limit order flow, market impact and optimal order sizes: Evidence from NASDAQ TotalView-ITCH data," SFB 649 Discussion Papers 2011-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," CFS Working Paper Series 2009/23, Center for Financial Studies (CFS).
    2. Anastasia Bugaenko, 2020. "Empirical Study of Market Impact Conditional on Order-Flow Imbalance," Papers 2004.08290, arXiv.org, revised Apr 2020.
    3. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.
    4. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2014. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers 2014-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Chen, Shi & Härdle, Wolfgang & Schienle, Melanie, 2021. "High-dimensional statistical learning techniques for time-varying limit order book networks," IRTG 1792 Discussion Papers 2021-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    9. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Martin Theissen & Sebastian M. Krause & Thomas Guhr, 2017. "Regularities and irregularities in order flow data," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 90(11), pages 1-9, November.
    11. Heyne, Gregor & Kupper, Michael & Mainberger, Christoph, 2011. "Minimal supersolutions of BSDEs with lower semicontinuous generations," SFB 649 Discussion Papers 2011-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Cebiroğlu, Gökhan & Horst, Ulrich, 2011. "Optimal display of Iceberg orders," SFB 649 Discussion Papers 2011-057, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Tischer, Sven & Hildebrandt, Lutz, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers 2011-065, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Schneider, Dorothee, 2011. "The labor share: A review of theory and evidence," SFB 649 Discussion Papers 2011-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Aaron Wheeler & Jeffrey D. Varner, 2024. "MarketGPT: Developing a Pre-trained transformer (GPT) for Modeling Financial Time Series," Papers 2411.16585, arXiv.org.
    16. Xintong Wang & Christopher Hoang & Yevgeniy Vorobeychik & Michael P. Wellman, 2021. "Spoofing the Limit Order Book: A Strategic Agent-Based Analysis," Games, MDPI, vol. 12(2), pages 1-43, May.
    17. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    18. Myšičková, Alena & Song, Song & Majer, Piotr & Mohr, Peter N. C. & Heekeren, Hauke R. & Härdle, Wolfgang Karl, 2011. "Risk patterns and correlated brain activities: Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers 2011-085, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    20. Kratz, Peter & Schöneborn, Torsten, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers 2011-058, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    21. Xuefeng Gao & S. J. Deng, 2014. "Hydrodynamic limit of order book dynamics," Papers 1411.7502, arXiv.org, revised Feb 2016.

  34. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    2. Anne Michaels & Michael Grüning, 2017. "Relationship of corporate social responsibility disclosure on information asymmetry and the cost of capital," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 28(3), pages 251-274, October.
    3. Carl Chiarella & Xue-Zhong He & Lei Shi & Lijian Wei, 2017. "A behavioural model of investor sentiment in limit order markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(1), pages 71-86, January.
    4. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Bagnara, Matteo & Jappelli, Ruggero, 2022. "Liquidity derivatives," SAFE Working Paper Series 358, Leibniz Institute for Financial Research SAFE.
    6. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Gianbiagio Curato & Fabrizio Lillo, 2013. "Modeling the coupled return-spread high frequency dynamics of large tick assets," Papers 1310.4539, arXiv.org.
    8. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
    9. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Gong, Yuting & Chen, Qiang & Liang, Jufang, 2018. "A mixed data sampling copula model for the return-liquidity dependence in stock index futures markets," Economic Modelling, Elsevier, vol. 68(C), pages 586-598.
    11. Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019. "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1473-1489, September.
    12. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    13. Arifovic, Jasmina & He, Xue-zhong & Wei, Lijian, 2022. "Machine learning and speed in high-frequency trading," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).

  35. Hautsch, Nikolaus & Hess, Dieter E. & Veredas, David, 2010. "The impact of macroeconomic news on quote adjustments, noise, and informational volatility," SFB 649 Discussion Papers 2010-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Adam Clements & Neda Todorova, 2014. "The impact of information flow and trading activity on gold and oil futures volatility," NCER Working Paper Series 102, National Centre for Econometric Research.
    2. Han, Liyan & Xu, Yang & Yin, Libo, 2017. "Does investor attention matter? The attention-return relation in gold futures market," Economics Discussion Papers 2017-37, Kiel Institute for the World Economy (IfW Kiel).
    3. Basteck, Christian & Daniëls, Tijmen R., 2010. "Every symmetric 3 x 3 global game of strategic complementarities is noise independent," SFB 649 Discussion Papers 2010-061, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Kurov, Alexander & Sancetta, Alessio & Strasser, Georg & Wolfe, Marketa Halova, 2019. "Price Drift Before U.S. Macroeconomic News: Private Information about Public Announcements?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(1), pages 449-479, February.
    5. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2015. "Which continuous-time model is most appropriate for exchange rates?," Post-Print hal-01457402, HAL.
    6. Füss, Roland & Grabellus, Markus & Mager, Ferdinand & Stein, Michael, 2018. "Something in the air: Information density, news surprises, and price jumps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 50-75.
    7. Burnecki, Krzysztof & Janczura, Joanna & Weron, Rafal, 2010. "Building Loss Models," MPRA Paper 25492, University Library of Munich, Germany.
    8. Melody Y. Huang & Randall R. Rojas & Patrick D. Convery, 2020. "Forecasting stock market movements using Google Trend searches," Empirical Economics, Springer, vol. 59(6), pages 2821-2839, December.
    9. Agnieszka Janek & Tino Kluge & Rafal Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," Papers 1010.1617, arXiv.org.
    10. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    11. Borak, Szymon & Misiorek, Adam & Weron, Rafal, 2010. "Models for Heavy-tailed Asset Returns," MPRA Paper 25494, University Library of Munich, Germany.
    12. Panov, Vladimir, 2010. "Estimation of the signal subspace without estimation of the inverse covariance matrix," SFB 649 Discussion Papers 2010-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Wiebach, Nicole & Hildebrandt, Lutz, 2010. "Context effects as customer reaction on delisting of brands," SFB 649 Discussion Papers 2010-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    15. Adam E. Clements & Neda Todorova, 2016. "Information Flow, Trading Activity and Commodity Futures Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(1), pages 88-104, January.
    16. Bian, Siyu & Serra, Teresa & Garcia, Philip & Irwin, Scott, 2022. "New evidence on market response to public announcements in the presence of microstructure noise," European Journal of Operational Research, Elsevier, vol. 298(2), pages 785-800.
    17. Hecht, Carolin & Hanewald, Katja, 2010. "Sociodemographic, economic, and psychological drivers of the demand for life insurance: Evidence from the German Retirement Income Act," SFB 649 Discussion Papers 2010-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    18. Schulze, Franziska, 2010. "Spatial dependencies in German matching functions," SFB 649 Discussion Papers 2010-054, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Hautsch, Nikolaus & Noé, Michael & Zhang, S. Sarah, 2017. "The ambivalent role of high-frequency trading in turbulent market periods," CFS Working Paper Series 580, Center for Financial Studies (CFS).
    20. Lei Wu & Kuan Xu & Qingbin Meng, 2021. "Information flow and price discovery dynamics," Review of Quantitative Finance and Accounting, Springer, vol. 56(1), pages 329-367, January.
    21. Carlo Campajola & Domenico Di Gangi & Fabrizio Lillo & Daniele Tantari, 2020. "Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model," Papers 2007.15545, arXiv.org, revised Aug 2021.
    22. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Forecasting the CNY-CNH pricing differential: The role of investor attention," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 232-247.
    23. Feng, Lingbing & Fu, Tong & Shi, Yanlin, 2022. "How does news sentiment affect the states of Japanese stock return volatility?," International Review of Financial Analysis, Elsevier, vol. 84(C).
    24. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Does investor attention matter? The attention-return relationships in FX markets," Economic Modelling, Elsevier, vol. 68(C), pages 644-660.
    25. Banerjee, Ameet Kumar & Pradhan, H.K. & Akhtaruzzaman, Md & Sensoy, Ahmet & Dann, Susan, 2024. "Anatomy of sovereign yield behaviour using textual news," Research in International Business and Finance, Elsevier, vol. 71(C).
    26. Baranovski, Alexander L., 2010. "Dynamical systems forced by shot noise as a new paradigm in the interest rate modeling," SFB 649 Discussion Papers 2010-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    27. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    28. Ulrich Horst & Santiago Moreno-Bromberg, 2011. "Efficiency and Equilibria in Games of Optimal Derivative Design," Papers 1107.0839, arXiv.org.
    29. Grith, Maria & Krätschmer, Volker, 2010. "Parametric estimation of risk neutral density functions," SFB 649 Discussion Papers 2010-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    30. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2010. "Nonparametric regression with nonparametrically generated covariates," SFB 649 Discussion Papers 2010-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    31. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
    32. Härdle, Wolfgang Karl & Moro, Rouslan A. & Hoffmann, Linda, 2010. "Learning machines supporting bankruptcy prediction," SFB 649 Discussion Papers 2010-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    33. Martin Hauptfleisch, 2019. "Financial Decision-Making Using Data," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 6-2019, January-A.
    34. Christoph Schmidhammer & Sebastian Lobe & Klaus Röder, 2014. "The real benchmark of DAX index products and the influence of information dissemination: A natural experiment," Journal of Asset Management, Palgrave Macmillan, vol. 15(2), pages 129-149, April.
    35. Sabiwalsky, Ralf, 2010. "Executive compensation regulation and the dynamics of the pay-performance sensitivity," SFB 649 Discussion Papers 2010-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    36. Barbopoulos, Leonidas G. & Adra, Samer & Saunders, Anthony, 2020. "Macroeconomic news and acquirer returns in M&As: The impact of investor alertness," Journal of Corporate Finance, Elsevier, vol. 64(C).
    37. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.
    38. Zhang, Junru & Zhang, Zhaoyong, 2021. "CSR, Media and Stock Illiquidity: Evidence from Chinese Listed Financial Firms," Finance Research Letters, Elsevier, vol. 41(C).
    39. Riordan, Ryan & Storkenmaier, Andreas & Wagener, Martin & Sarah Zhang, S., 2013. "Public information arrival: Price discovery and liquidity in electronic limit order markets," Journal of Banking & Finance, Elsevier, vol. 37(4), pages 1148-1159.

  36. Hautsch, Nikolaus & Malec, Peter & Schienle, Melanie, 2010. "Capturing the zero: A new class of zero-augmented distributions and multiplicative error processes," SFB 649 Discussion Papers 2010-055, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hiroyuki Kawakatsu, 2019. "Jointly Modeling Autoregressive Conditional Mean and Variance of Non-Negative Valued Time Series," Econometrics, MDPI, vol. 7(4), pages 1-19, December.
    2. Basteck, Christian & Daniëls, Tijmen R., 2010. "Every symmetric 3 x 3 global game of strategic complementarities is noise independent," SFB 649 Discussion Papers 2010-061, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.
    4. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," MPRA Paper 93802, University Library of Munich, Germany.
    6. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
    7. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    8. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    9. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2019. "Dynamic discrete mixtures for high frequency prices," Discussion Papers 19/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    10. Sucarrat, Genaro & Grønneberg, Steffen, 2016. "Models of Financial Return With Time-Varying Zero Probability," MPRA Paper 68931, University Library of Munich, Germany.
    11. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.
    12. Wiebach, Nicole & Hildebrandt, Lutz, 2010. "Context effects as customer reaction on delisting of brands," SFB 649 Discussion Papers 2010-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Carol Alexander & Daniel F. Heck & Andreas Kaeck, 2022. "The Role of Binance in Bitcoin Volatility Transmission," Applied Mathematical Finance, Taylor & Francis Journals, vol. 29(1), pages 1-32, January.
    14. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    15. Cipollini, Fabrizio & Gallo, Giampiero M., 2025. "Multiplicative Error Models: 20 years on," Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
    16. Andreea Röthig & Andreas Röthig & Carl Chiarella, 2015. "On Candlestick-based Trading Rules Profitability Analysis via Parametric Bootstraps and Multivariate Pair-Copula based Models," Research Paper Series 362, Quantitative Finance Research Centre, University of Technology, Sydney.
    17. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    18. Stanislav Anatolyev & Sergei Seleznev & Veronika Selezneva, 2021. "How does the financial market update beliefs about the real economy? Evidence from the oil market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 938-961, November.
    19. Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
    20. Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.
    21. Sucarrat, Genaro, 2020. "Identification of Volatility Proxies as Expectations of Squared Financial Return," MPRA Paper 101953, University Library of Munich, Germany.
    22. Malec, Peter & Schienle, Melanie, 2012. "Nonparametric Kernel density estimation near the boundary," SFB 649 Discussion Papers 2012-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    23. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    24. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula–Based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics, MDPI, vol. 5(2), pages 1-24, April.
    25. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    26. Mariana Rodrigues-Motta & Johannes Forkman, 2022. "Bayesian Analysis of Nonnegative Data Using Dependency-Extended Two-Part Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 201-221, June.
    27. Stanislav Anatolyev & Sergei Seleznev & Veronika Selezneva, 2018. "Formation of Market Beliefs in the Oil Market," CERGE-EI Working Papers wp619, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    28. Wolfgang K. Härdle & Nikolaus Hautsch & Andrija Mihoci, 2015. "Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 529-550, June.
    29. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    30. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2010. "Nonparametric regression with nonparametrically generated covariates," SFB 649 Discussion Papers 2010-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    31. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
    32. Harvey, Andrew & Ito, Ryoko, 2020. "Modeling time series when some observations are zero," Journal of Econometrics, Elsevier, vol. 214(1), pages 33-45.
    33. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    34. Sucarrat, Genaro, 2021. "Identification of volatility proxies as expectations of squared financial returns," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1677-1690.

  37. Hautsch, Nikolaus & Yang, Fuyu, 2010. "Bayesian inference in a stochastic volatility Nelson-Siegel Model," SFB 649 Discussion Papers 2010-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hautsch, Nikolaus & Ou, Yangguoyi, 2009. "Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields," CFS Working Paper Series 2009/03, Center for Financial Studies (CFS).
    2. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    3. Basteck, Christian & Daniëls, Tijmen R., 2010. "Every symmetric 3 x 3 global game of strategic complementarities is noise independent," SFB 649 Discussion Papers 2010-061, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Márcio Laurini, 2012. "Dynamic Functional Data Analysis with Nonparametric State Space Models," IBMEC RJ Economics Discussion Papers 2012-01, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    5. Joseph P. Byrne & Shuo Cao. & Dimitris Korobilis., 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," Working Papers 2015_08, Business School - Economics, University of Glasgow.
    6. Burnecki, Krzysztof & Janczura, Joanna & Weron, Rafal, 2010. "Building Loss Models," MPRA Paper 25492, University Library of Munich, Germany.
    7. Agnieszka Janek & Tino Kluge & Rafal Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," Papers 1010.1617, arXiv.org.
    8. Hong, Zhiwu & Niu, Linlin & Zhang, Chen, 2022. "Affine arbitrage-free yield net models with application to the euro debt crisis," Journal of Econometrics, Elsevier, vol. 230(1), pages 201-220.
    9. Borak, Szymon & Misiorek, Adam & Weron, Rafal, 2010. "Models for Heavy-tailed Asset Returns," MPRA Paper 25494, University Library of Munich, Germany.
    10. Panov, Vladimir, 2010. "Estimation of the signal subspace without estimation of the inverse covariance matrix," SFB 649 Discussion Papers 2010-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    11. Wiebach, Nicole & Hildebrandt, Lutz, 2010. "Context effects as customer reaction on delisting of brands," SFB 649 Discussion Papers 2010-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Raviv, Eran, 2015. "Prediction bias correction for dynamic term structure models," Economics Letters, Elsevier, vol. 129(C), pages 112-115.
    13. Hecht, Carolin & Hanewald, Katja, 2010. "Sociodemographic, economic, and psychological drivers of the demand for life insurance: Evidence from the German Retirement Income Act," SFB 649 Discussion Papers 2010-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Schulze, Franziska, 2010. "Spatial dependencies in German matching functions," SFB 649 Discussion Papers 2010-054, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Laurini, Márcio P. & Caldeira, João F., 2016. "A macro-finance term structure model with multivariate stochastic volatility," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 68-90.
    16. Márcio Poletti Laurini & Armênio Westin Neto, 2014. "Arbitrage in the Term Structure of Interest Rates: a Bayesian Approach," International Econometric Review (IER), Econometric Research Association, vol. 6(2), pages 77-99, September.
    17. Choi, Ahjin & Kang, Kyu Ho, 2023. "Modeling the time-varying dynamic term structure of interest rates," Journal of Banking & Finance, Elsevier, vol. 153(C).
    18. Baranovski, Alexander L., 2010. "Dynamical systems forced by shot noise as a new paradigm in the interest rate modeling," SFB 649 Discussion Papers 2010-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    20. Ulrich Horst & Santiago Moreno-Bromberg, 2011. "Efficiency and Equilibria in Games of Optimal Derivative Design," Papers 1107.0839, arXiv.org.
    21. Grith, Maria & Krätschmer, Volker, 2010. "Parametric estimation of risk neutral density functions," SFB 649 Discussion Papers 2010-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    22. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2010. "Nonparametric regression with nonparametrically generated covariates," SFB 649 Discussion Papers 2010-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    23. Härdle, Wolfgang Karl & Moro, Rouslan A. & Hoffmann, Linda, 2010. "Learning machines supporting bankruptcy prediction," SFB 649 Discussion Papers 2010-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    24. Sabiwalsky, Ralf, 2010. "Executive compensation regulation and the dynamics of the pay-performance sensitivity," SFB 649 Discussion Papers 2010-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    25. Sourish Das, 2018. "Modeling Nelson-Siegel Yield Curve using Bayesian Approach," Papers 1809.06077, arXiv.org, revised Oct 2018.
    26. Cem Çakmakli, 2012. "Bayesian Semiparametric Dynamic Nelson-Siegel Model," Working Paper series 59_12, Rimini Centre for Economic Analysis, revised Sep 2012.

  38. Nikolaus Hautsch & Dieter Hess & David Veredas, 2010. "The impact of macroeconomic news on quote adjustments, noise and informational volatility," Working Papers ECARES 2010-004, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Adam Clements & Neda Todorova, 2014. "The impact of information flow and trading activity on gold and oil futures volatility," NCER Working Paper Series 102, National Centre for Econometric Research.
    2. Han, Liyan & Xu, Yang & Yin, Libo, 2017. "Does investor attention matter? The attention-return relation in gold futures market," Economics Discussion Papers 2017-37, Kiel Institute for the World Economy (IfW Kiel).
    3. Basteck, Christian & Daniëls, Tijmen R., 2010. "Every symmetric 3 x 3 global game of strategic complementarities is noise independent," SFB 649 Discussion Papers 2010-061, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Kurov, Alexander & Sancetta, Alessio & Strasser, Georg & Wolfe, Marketa Halova, 2019. "Price Drift Before U.S. Macroeconomic News: Private Information about Public Announcements?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(1), pages 449-479, February.
    5. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2015. "Which continuous-time model is most appropriate for exchange rates?," Post-Print hal-01457402, HAL.
    6. Füss, Roland & Grabellus, Markus & Mager, Ferdinand & Stein, Michael, 2018. "Something in the air: Information density, news surprises, and price jumps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 50-75.
    7. Burnecki, Krzysztof & Janczura, Joanna & Weron, Rafal, 2010. "Building Loss Models," MPRA Paper 25492, University Library of Munich, Germany.
    8. Melody Y. Huang & Randall R. Rojas & Patrick D. Convery, 2020. "Forecasting stock market movements using Google Trend searches," Empirical Economics, Springer, vol. 59(6), pages 2821-2839, December.
    9. Agnieszka Janek & Tino Kluge & Rafal Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," Papers 1010.1617, arXiv.org.
    10. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    11. Borak, Szymon & Misiorek, Adam & Weron, Rafal, 2010. "Models for Heavy-tailed Asset Returns," MPRA Paper 25494, University Library of Munich, Germany.
    12. Panov, Vladimir, 2010. "Estimation of the signal subspace without estimation of the inverse covariance matrix," SFB 649 Discussion Papers 2010-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Wiebach, Nicole & Hildebrandt, Lutz, 2010. "Context effects as customer reaction on delisting of brands," SFB 649 Discussion Papers 2010-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    15. Adam E. Clements & Neda Todorova, 2016. "Information Flow, Trading Activity and Commodity Futures Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(1), pages 88-104, January.
    16. Bian, Siyu & Serra, Teresa & Garcia, Philip & Irwin, Scott, 2022. "New evidence on market response to public announcements in the presence of microstructure noise," European Journal of Operational Research, Elsevier, vol. 298(2), pages 785-800.
    17. Hecht, Carolin & Hanewald, Katja, 2010. "Sociodemographic, economic, and psychological drivers of the demand for life insurance: Evidence from the German Retirement Income Act," SFB 649 Discussion Papers 2010-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    18. Schulze, Franziska, 2010. "Spatial dependencies in German matching functions," SFB 649 Discussion Papers 2010-054, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Hautsch, Nikolaus & Noé, Michael & Zhang, S. Sarah, 2017. "The ambivalent role of high-frequency trading in turbulent market periods," CFS Working Paper Series 580, Center for Financial Studies (CFS).
    20. Lei Wu & Kuan Xu & Qingbin Meng, 2021. "Information flow and price discovery dynamics," Review of Quantitative Finance and Accounting, Springer, vol. 56(1), pages 329-367, January.
    21. Carlo Campajola & Domenico Di Gangi & Fabrizio Lillo & Daniele Tantari, 2020. "Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model," Papers 2007.15545, arXiv.org, revised Aug 2021.
    22. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Forecasting the CNY-CNH pricing differential: The role of investor attention," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 232-247.
    23. Feng, Lingbing & Fu, Tong & Shi, Yanlin, 2022. "How does news sentiment affect the states of Japanese stock return volatility?," International Review of Financial Analysis, Elsevier, vol. 84(C).
    24. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Does investor attention matter? The attention-return relationships in FX markets," Economic Modelling, Elsevier, vol. 68(C), pages 644-660.
    25. Banerjee, Ameet Kumar & Pradhan, H.K. & Akhtaruzzaman, Md & Sensoy, Ahmet & Dann, Susan, 2024. "Anatomy of sovereign yield behaviour using textual news," Research in International Business and Finance, Elsevier, vol. 71(C).
    26. Baranovski, Alexander L., 2010. "Dynamical systems forced by shot noise as a new paradigm in the interest rate modeling," SFB 649 Discussion Papers 2010-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    27. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    28. Ulrich Horst & Santiago Moreno-Bromberg, 2011. "Efficiency and Equilibria in Games of Optimal Derivative Design," Papers 1107.0839, arXiv.org.
    29. Grith, Maria & Krätschmer, Volker, 2010. "Parametric estimation of risk neutral density functions," SFB 649 Discussion Papers 2010-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    30. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2010. "Nonparametric regression with nonparametrically generated covariates," SFB 649 Discussion Papers 2010-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    31. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
    32. Härdle, Wolfgang Karl & Moro, Rouslan A. & Hoffmann, Linda, 2010. "Learning machines supporting bankruptcy prediction," SFB 649 Discussion Papers 2010-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    33. Martin Hauptfleisch, 2019. "Financial Decision-Making Using Data," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 6-2019, January-A.
    34. Christoph Schmidhammer & Sebastian Lobe & Klaus Röder, 2014. "The real benchmark of DAX index products and the influence of information dissemination: A natural experiment," Journal of Asset Management, Palgrave Macmillan, vol. 15(2), pages 129-149, April.
    35. Sabiwalsky, Ralf, 2010. "Executive compensation regulation and the dynamics of the pay-performance sensitivity," SFB 649 Discussion Papers 2010-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    36. Barbopoulos, Leonidas G. & Adra, Samer & Saunders, Anthony, 2020. "Macroeconomic news and acquirer returns in M&As: The impact of investor alertness," Journal of Corporate Finance, Elsevier, vol. 64(C).
    37. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.
    38. Zhang, Junru & Zhang, Zhaoyong, 2021. "CSR, Media and Stock Illiquidity: Evidence from Chinese Listed Financial Firms," Finance Research Letters, Elsevier, vol. 41(C).
    39. Riordan, Ryan & Storkenmaier, Andreas & Wagener, Martin & Sarah Zhang, S., 2013. "Public information arrival: Price discovery and liquidity in electronic limit order markets," Journal of Banking & Finance, Elsevier, vol. 37(4), pages 1148-1159.

  39. Nikolaus Hautsch & Mark Podolskij, 2010. "Pre-Averaging Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence," CREATES Research Papers 2010-29, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Bibinger, Markus & Hautsch, Nikolaus & Malec, Peter & Reiss, Markus, 2014. "Estimating the spot covariation of asset prices: Statistical theory and empirical evidence," SFB 649 Discussion Papers 2014-055, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Basteck, Christian & Daniëls, Tijmen R., 2010. "Every symmetric 3 x 3 global game of strategic complementarities is noise independent," SFB 649 Discussion Papers 2010-061, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.
    4. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
    5. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    6. Härdle, Wolfgang Karl & Chen, Shi & Liang, Chong & Schienle, Melanie, 2018. "Time-varying Limit Order Book Networks," IRTG 1792 Discussion Papers 2018-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
    8. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    9. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    10. Agnieszka Janek & Tino Kluge & Rafal Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," Papers 1010.1617, arXiv.org.
    11. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2013. "A nonparametric test of a strong leverage hypothesis," CeMMAP working papers 28/13, Institute for Fiscal Studies.
    12. Ulrich Hounyo & Silvia Gonçalves & Nour Meddahi, 2016. "Bootstrapping pre-averaged realized volatility under market microstructure noise," CIRANO Working Papers 2016s-25, CIRANO.
    13. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
    14. Chen, Shi & Härdle, Wolfgang & Schienle, Melanie, 2021. "High-dimensional statistical learning techniques for time-varying limit order book networks," IRTG 1792 Discussion Papers 2021-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    15. Borak, Szymon & Misiorek, Adam & Weron, Rafal, 2010. "Models for Heavy-tailed Asset Returns," MPRA Paper 25494, University Library of Munich, Germany.
    16. Panov, Vladimir, 2010. "Estimation of the signal subspace without estimation of the inverse covariance matrix," SFB 649 Discussion Papers 2010-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    17. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    18. Wiebach, Nicole & Hildebrandt, Lutz, 2010. "Context effects as customer reaction on delisting of brands," SFB 649 Discussion Papers 2010-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Carol Alexander & Daniel F. Heck & Andreas Kaeck, 2022. "The Role of Binance in Bitcoin Volatility Transmission," Applied Mathematical Finance, Taylor & Francis Journals, vol. 29(1), pages 1-32, January.
    20. James, Robert & Leung, Henry & Prokhorov, Artem, 2023. "A machine learning attack on illegal trading," Journal of Banking & Finance, Elsevier, vol. 148(C).
    21. Aït-Sahalia, Yacine & Xiu, Dacheng, 2016. "Increased correlation among asset classes: Are volatility or jumps to blame, or both?," Journal of Econometrics, Elsevier, vol. 194(2), pages 205-219.
    22. Vladimír Holý & Petra Tomanová, 2023. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 463-485, June.
    23. Li, M. Z. & Linton, O., 2021. "Robust Estimation of Integrated and Spot Volatility," Cambridge Working Papers in Economics 2115, Faculty of Economics, University of Cambridge.
    24. Schulze, Franziska, 2010. "Spatial dependencies in German matching functions," SFB 649 Discussion Papers 2010-054, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    25. Saef, Danial & Nagy, Odett & Sizov, Sergej & Härdle, Wolfgang, 2021. "Understanding jumps in high frequency digital asset markets," IRTG 1792 Discussion Papers 2021-019, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    26. Chaker, Selma, 2017. "On high frequency estimation of the frictionless price: The use of observed liquidity variables," Journal of Econometrics, Elsevier, vol. 201(1), pages 127-143.
    27. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    28. Bollerslev, Tim & Meddahi, Nour & Nyawa, Serge, 2019. "High-dimensional multivariate realized volatility estimation," Journal of Econometrics, Elsevier, vol. 212(1), pages 116-136.
    29. Caporin, Massimiliano & Kolokolov, Aleksey & Renò, Roberto, 2014. "Multi-jumps," MPRA Paper 58175, University Library of Munich, Germany.
    30. Huang, Zih-Chun & Sangiorgi, Ivan & Urquhart, Andrew, 2024. "Forecasting Bitcoin volatility using machine learning techniques," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 97(C).
    31. Caporin, Massimiliano & Kolokolov, Alexey & Renò, Roberto, 2016. "Systemic co-jumps," SAFE Working Paper Series 149, Leibniz Institute for Financial Research SAFE.
    32. Jacod, Jean & Li, Yingying & Zheng, Xinghua, 2019. "Estimating the integrated volatility with tick observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 80-100.
    33. Yafeng Shi & Tingting Ying & Yanlong Shi & Chunrong Ai, 2020. "A comparison of conditional predictive ability of implied volatility and realized measures in forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1025-1034, November.
    34. Hounyo, Ulrich, 2017. "Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading," Journal of Econometrics, Elsevier, vol. 197(1), pages 130-152.
    35. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    36. Podolskij, Mark & Veliyev, Bezirgen & Yoshida, Nakahiro, 2017. "Edgeworth expansion for the pre-averaging estimator," Stochastic Processes and their Applications, Elsevier, vol. 127(11), pages 3558-3595.
    37. Danial Saef & Odett Nagy & Sergej Sizov & Wolfgang Karl Härdle, 2024. "Understanding temporal dynamics of jumps in cryptocurrency markets: evidence from tick-by-tick data," Digital Finance, Springer, vol. 6(4), pages 605-638, December.
    38. Li, Z. M. & Laeven, R. J. A. & Vellekoop, M. H., 2019. "Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data," Cambridge Working Papers in Economics 1952, Faculty of Economics, University of Cambridge.
    39. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    40. Grith, Maria & Krätschmer, Volker, 2010. "Parametric estimation of risk neutral density functions," SFB 649 Discussion Papers 2010-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    41. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2010. "Nonparametric regression with nonparametrically generated covariates," SFB 649 Discussion Papers 2010-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    42. Rui Da & Dacheng Xiu, 2021. "When Moving‐Average Models Meet High‐Frequency Data: Uniform Inference on Volatility," Econometrica, Econometric Society, vol. 89(6), pages 2787-2825, November.
    43. Yuta Koike, 2017. "Time endogeneity and an optimal weight function in pre-averaging covariance estimation," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 15-56, April.
    44. Ulrich Hounyo & Bezirgen Veliyev, 2015. "Validity of Edgeworth expansions for realized volatility estimators," CREATES Research Papers 2015-21, Department of Economics and Business Economics, Aarhus University.
    45. Boudt, Kris & Cornelissen, Jonathan & Croux, Christophe, 2012. "Jump robust daily covariance estimation by disentangling variance and correlation components," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 2993-3005.
    46. Zhang, Chuanhai & Liu, Zhi & Liu, Qiang, 2021. "Jumps at ultra-high frequency: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    47. Sabiwalsky, Ralf, 2010. "Executive compensation regulation and the dynamics of the pay-performance sensitivity," SFB 649 Discussion Papers 2010-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    48. Mathias Pohl & Alexander Ristig & Walter Schachermayer & Ludovic Tangpi, 2018. "Theoretical and empirical analysis of trading activity," Papers 1803.04892, arXiv.org, revised Oct 2018.
    49. Danial Saef & Odett Nagy & Sergej Sizov & Wolfgang Karl Hardle, 2021. "Understanding jumps in high frequency digital asset markets," Papers 2110.09429, arXiv.org.
    50. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    51. Wang, Jiazhen & Jiang, Yuexiang & Zhu, Yanjian & Yu, Jing, 2020. "Prediction of volatility based on realized-GARCH-kernel-type models: Evidence from China and the U.S," Economic Modelling, Elsevier, vol. 91(C), pages 428-444.
    52. Vladim'ir Hol'y & Petra Tomanov'a, 2020. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Papers 2003.13062, arXiv.org, revised Dec 2021.

  40. Hautsch, Nikolaus & Yang, Fuyu, 2010. "Bayesian inference in a stochastic volatility Nelson-Siegel Model," SFB 649 Discussion Papers 2010-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hautsch, Nikolaus & Ou, Yangguoyi, 2009. "Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields," CFS Working Paper Series 2009/03, Center for Financial Studies (CFS).
    2. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    3. Basteck, Christian & Daniëls, Tijmen R., 2010. "Every symmetric 3 x 3 global game of strategic complementarities is noise independent," SFB 649 Discussion Papers 2010-061, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Márcio Laurini, 2012. "Dynamic Functional Data Analysis with Nonparametric State Space Models," IBMEC RJ Economics Discussion Papers 2012-01, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    5. Joseph P. Byrne & Shuo Cao. & Dimitris Korobilis., 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," Working Papers 2015_08, Business School - Economics, University of Glasgow.
    6. Burnecki, Krzysztof & Janczura, Joanna & Weron, Rafal, 2010. "Building Loss Models," MPRA Paper 25492, University Library of Munich, Germany.
    7. Agnieszka Janek & Tino Kluge & Rafal Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," Papers 1010.1617, arXiv.org.
    8. Hong, Zhiwu & Niu, Linlin & Zhang, Chen, 2022. "Affine arbitrage-free yield net models with application to the euro debt crisis," Journal of Econometrics, Elsevier, vol. 230(1), pages 201-220.
    9. Borak, Szymon & Misiorek, Adam & Weron, Rafal, 2010. "Models for Heavy-tailed Asset Returns," MPRA Paper 25494, University Library of Munich, Germany.
    10. Panov, Vladimir, 2010. "Estimation of the signal subspace without estimation of the inverse covariance matrix," SFB 649 Discussion Papers 2010-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    11. Wiebach, Nicole & Hildebrandt, Lutz, 2010. "Context effects as customer reaction on delisting of brands," SFB 649 Discussion Papers 2010-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Raviv, Eran, 2015. "Prediction bias correction for dynamic term structure models," Economics Letters, Elsevier, vol. 129(C), pages 112-115.
    13. Hecht, Carolin & Hanewald, Katja, 2010. "Sociodemographic, economic, and psychological drivers of the demand for life insurance: Evidence from the German Retirement Income Act," SFB 649 Discussion Papers 2010-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Schulze, Franziska, 2010. "Spatial dependencies in German matching functions," SFB 649 Discussion Papers 2010-054, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Laurini, Márcio P. & Caldeira, João F., 2016. "A macro-finance term structure model with multivariate stochastic volatility," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 68-90.
    16. Márcio Poletti Laurini & Armênio Westin Neto, 2014. "Arbitrage in the Term Structure of Interest Rates: a Bayesian Approach," International Econometric Review (IER), Econometric Research Association, vol. 6(2), pages 77-99, September.
    17. Choi, Ahjin & Kang, Kyu Ho, 2023. "Modeling the time-varying dynamic term structure of interest rates," Journal of Banking & Finance, Elsevier, vol. 153(C).
    18. Baranovski, Alexander L., 2010. "Dynamical systems forced by shot noise as a new paradigm in the interest rate modeling," SFB 649 Discussion Papers 2010-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    20. Ulrich Horst & Santiago Moreno-Bromberg, 2011. "Efficiency and Equilibria in Games of Optimal Derivative Design," Papers 1107.0839, arXiv.org.
    21. Grith, Maria & Krätschmer, Volker, 2010. "Parametric estimation of risk neutral density functions," SFB 649 Discussion Papers 2010-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    22. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2010. "Nonparametric regression with nonparametrically generated covariates," SFB 649 Discussion Papers 2010-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    23. Härdle, Wolfgang Karl & Moro, Rouslan A. & Hoffmann, Linda, 2010. "Learning machines supporting bankruptcy prediction," SFB 649 Discussion Papers 2010-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    24. Sabiwalsky, Ralf, 2010. "Executive compensation regulation and the dynamics of the pay-performance sensitivity," SFB 649 Discussion Papers 2010-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    25. Sourish Das, 2018. "Modeling Nelson-Siegel Yield Curve using Bayesian Approach," Papers 1809.06077, arXiv.org, revised Oct 2018.
    26. Cem Çakmakli, 2012. "Bayesian Semiparametric Dynamic Nelson-Siegel Model," Working Paper series 59_12, Rimini Centre for Economic Analysis, revised Sep 2012.

  41. Hautsch, Nikolaus & Malec, Peter & Schienle, Melanie, 2010. "Capturing the zero: A new class of zero-augmented distributions and multiplicative error processes," SFB 649 Discussion Papers 2010-055, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hiroyuki Kawakatsu, 2019. "Jointly Modeling Autoregressive Conditional Mean and Variance of Non-Negative Valued Time Series," Econometrics, MDPI, vol. 7(4), pages 1-19, December.
    2. Basteck, Christian & Daniëls, Tijmen R., 2010. "Every symmetric 3 x 3 global game of strategic complementarities is noise independent," SFB 649 Discussion Papers 2010-061, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.
    4. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," MPRA Paper 93802, University Library of Munich, Germany.
    6. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
    7. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    8. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    9. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2019. "Dynamic discrete mixtures for high frequency prices," Discussion Papers 19/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    10. Sucarrat, Genaro & Grønneberg, Steffen, 2016. "Models of Financial Return With Time-Varying Zero Probability," MPRA Paper 68931, University Library of Munich, Germany.
    11. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.
    12. Wiebach, Nicole & Hildebrandt, Lutz, 2010. "Context effects as customer reaction on delisting of brands," SFB 649 Discussion Papers 2010-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Carol Alexander & Daniel F. Heck & Andreas Kaeck, 2022. "The Role of Binance in Bitcoin Volatility Transmission," Applied Mathematical Finance, Taylor & Francis Journals, vol. 29(1), pages 1-32, January.
    14. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    15. Cipollini, Fabrizio & Gallo, Giampiero M., 2025. "Multiplicative Error Models: 20 years on," Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
    16. Andreea Röthig & Andreas Röthig & Carl Chiarella, 2015. "On Candlestick-based Trading Rules Profitability Analysis via Parametric Bootstraps and Multivariate Pair-Copula based Models," Research Paper Series 362, Quantitative Finance Research Centre, University of Technology, Sydney.
    17. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    18. Stanislav Anatolyev & Sergei Seleznev & Veronika Selezneva, 2021. "How does the financial market update beliefs about the real economy? Evidence from the oil market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 938-961, November.
    19. Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
    20. Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.
    21. Sucarrat, Genaro, 2020. "Identification of Volatility Proxies as Expectations of Squared Financial Return," MPRA Paper 101953, University Library of Munich, Germany.
    22. Malec, Peter & Schienle, Melanie, 2012. "Nonparametric Kernel density estimation near the boundary," SFB 649 Discussion Papers 2012-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    23. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    24. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula–Based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics, MDPI, vol. 5(2), pages 1-24, April.
    25. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    26. Mariana Rodrigues-Motta & Johannes Forkman, 2022. "Bayesian Analysis of Nonnegative Data Using Dependency-Extended Two-Part Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 201-221, June.
    27. Stanislav Anatolyev & Sergei Seleznev & Veronika Selezneva, 2018. "Formation of Market Beliefs in the Oil Market," CERGE-EI Working Papers wp619, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    28. Wolfgang K. Härdle & Nikolaus Hautsch & Andrija Mihoci, 2015. "Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 529-550, June.
    29. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    30. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2010. "Nonparametric regression with nonparametrically generated covariates," SFB 649 Discussion Papers 2010-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    31. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
    32. Harvey, Andrew & Ito, Ryoko, 2020. "Modeling time series when some observations are zero," Journal of Econometrics, Elsevier, vol. 214(1), pages 33-45.
    33. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    34. Sucarrat, Genaro, 2021. "Identification of volatility proxies as expectations of squared financial returns," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1677-1690.

  42. Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," SFB 649 Discussion Papers 2009-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Fabrizio Pomponio & Frédéric Abergel, 2013. "Multiple-limit trades : empirical facts and application to lead-lag measures," Post-Print hal-00745317, HAL.
    2. Cebiroğlu, Gökhan & Horst, Ulrich, 2012. "Hidden liquidity: Determinants and impact," SFB 649 Discussion Papers 2012-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Fleming, Michael J. & Mizrach, Bruce & Nguyen, Giang, 2018. "The microstructure of a U.S. Treasury ECN: The BrokerTec platform," Journal of Financial Markets, Elsevier, vol. 40(C), pages 2-22.
    4. Mehdi Arzandeh & Julieta Frank, 2019. "Price Discovery in Agricultural Futures Markets: Should We Look beyond the Best Bid-Ask Spread?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(5), pages 1482-1498.
    5. Esen Onur & John S. Roberts & Tugkan Tuzun, 2017. "Trader Positions and Marketwide Liquidity Demand," Finance and Economics Discussion Series 2017-103, Board of Governors of the Federal Reserve System (U.S.).
    6. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
    7. Baruch, Shmuel & Panayides, Marios & Venkataraman, Kumar, 2017. "Informed trading and price discovery before corporate events," Journal of Financial Economics, Elsevier, vol. 125(3), pages 561-588.
    8. Timoth'ee Fabre & Vincent Ragel, 2023. "Interpretable ML for High-Frequency Execution," Papers 2307.04863, arXiv.org, revised Sep 2024.
    9. Cebiroglu, Gökhan & Hautsch, Nikolaus & Horst, Ulrich, 2014. "Order exposure and liquidity coordination: Does hidden liquidity harm price efficiency?," CFS Working Paper Series 468, Center for Financial Studies (CFS).
    10. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    11. Härdle, Wolfgang Karl & Chen, Shi & Liang, Chong & Schienle, Melanie, 2018. "Time-varying Limit Order Book Networks," IRTG 1792 Discussion Papers 2018-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Han, SeungOh, 2024. "Price clustering on cryptocurrency order books at a US-based exchange," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    13. Jose Blanchet & Xinyun Chen, 2013. "Continuous-time Modeling of Bid-Ask Spread and Price Dynamics in Limit Order Books," Papers 1310.1103, arXiv.org.
    14. Zhu, Hongyu & Yamamoto, Ryuichi, 2022. "Order submission, information asymmetry, and tick size," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    15. Hautsch, Nikolaus & Huang, Ruihong, 2011. "Limit order flow, market impact and optimal order sizes: Evidence from NASDAQ TotalView-ITCH data," SFB 649 Discussion Papers 2011-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. Nikolaus Hautsch & Mark Podolskij, 2010. "Pre-Averaging Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence," CREATES Research Papers 2010-29, Department of Economics and Business Economics, Aarhus University.
    17. Xue, Yi & Gençay, Ramazan, 2012. "Hierarchical information and the rate of information diffusion," Journal of Economic Dynamics and Control, Elsevier, vol. 36(9), pages 1372-1401.
    18. Yi Cao & Jia Zhai, 2022. "Estimating price impact via deep reinforcement learning," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3954-3970, October.
    19. Chen, Shi & Härdle, Wolfgang & Schienle, Melanie, 2021. "High-dimensional statistical learning techniques for time-varying limit order book networks," IRTG 1792 Discussion Papers 2021-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    20. Yergeau, Gabriel, 2016. "Profitability and Market Quality of High Frequency Market-makers: An Empirical Investigation," Working Papers 16-3, HEC Montreal, Canada Research Chair in Risk Management.
    21. Tejas Ramdas & Martin T. Wells, 2024. "Bellwether Trades: Characteristics of Trades influential in Predicting Future Price Movements in Markets," Papers 2409.05192, arXiv.org.
    22. Erdinc Akyildirim & Shaen Corbet & Guzhan Gulay & Duc Khuong Nguyen & Ahmet Sensoy, 2019. "Order Flow Persistence in Equity Spot and Futures Markets: Evidence from a Dynamic Emerging Market," Working Papers 2019-011, Department of Research, Ipag Business School.
    23. Comerton-Forde, Carole & Putniņš, Tālis J., 2015. "Dark trading and price discovery," Journal of Financial Economics, Elsevier, vol. 118(1), pages 70-92.
    24. Nikolaus Hautsch & Dieter Hess & David Veredas, 2010. "The impact of macroeconomic news on quote adjustments, noise and informational volatility," Working Papers ECARES 2010-004, ULB -- Universite Libre de Bruxelles.
    25. Francesco Calvori & Fabrizio Cipollini & Giampiero M. Gallo, 2014. "Go with the Flow: A GAS model for Predicting Intra-daily Volume Shares," Econometrics Working Papers Archive 2014_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    26. Fabrizio Pomponio & Frederic Abergel, 2012. "Multiple-limit trades: empirical facts and application to lead--lag measures," Quantitative Finance, Taylor & Francis Journals, vol. 13(5), pages 783-793, September.
    27. Lo, Danny K. & Hall, Anthony D., 2015. "Resiliency of the limit order book," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 222-244.
    28. Chaboud, Alain & Hjalmarsson, Erik & Zikes, Filip, 2021. "The evolution of price discovery in an electronic market," Journal of Banking & Finance, Elsevier, vol. 130(C).
    29. Zoltán Eisler & Jean-Philippe Bouchaud & Julien Kockelkoren, 2012. "The price impact of order book events: market orders, limit orders and cancellations," Quantitative Finance, Taylor & Francis Journals, vol. 12(9), pages 1395-1419, September.
    30. Li, Zhicheng & Chen, Xinyun & Xing, Haipeng, 2023. "A multifactor regime-switching model for inter-trade durations in the high-frequency limit order market," Economic Modelling, Elsevier, vol. 118(C).
    31. Antonio Figueiredo & Pankaj Jain & Suchismita Mishra, 2023. "The role of fleeting orders on option expiration days," Quantitative Finance, Taylor & Francis Journals, vol. 23(10), pages 1511-1529, October.
    32. Thomas A. P. de Boer & Cornelis Gardebroek & Joost M. E. Pennings & Andres Trujillo‐Barrera, 2022. "Intraday liquidity in soybean complex futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1189-1211, July.
    33. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    34. Johannes Bleher & Michael Bleher & Thomas Dimpfl, 2020. "From orders to prices: A stochastic description of the limit order book to forecast intraday returns," Papers 2004.11953, arXiv.org, revised May 2021.
    35. Alex Frino & Ognjen Kovačević & Vito Mollica, 2019. "Depths and spreads in futures markets: Relationship with order execution, submission, and cancellation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(5), pages 590-599, May.
    36. Cebiroğlu, Gökhan & Horst, Ulrich, 2015. "Optimal order display in limit order markets with liquidity competition," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 81-100.
    37. Będowska-Sójka, Barbara, 2020. "Do aggressive orders affect liquidity? An evidence from an emerging market," Research in International Business and Finance, Elsevier, vol. 54(C).
    38. Andrea Coletta & Joseph Jerome & Rahul Savani & Svitlana Vyetrenko, 2023. "Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness," Papers 2306.12806, arXiv.org.
    39. Zhicheng Li & Haipeng Xing & Xinyun Chen, 2019. "A multifactor regime-switching model for inter-trade durations in the limit order market," Papers 1912.00764, arXiv.org.
    40. Xintong Wang & Christopher Hoang & Yevgeniy Vorobeychik & Michael P. Wellman, 2021. "Spoofing the Limit Order Book: A Strategic Agent-Based Analysis," Games, MDPI, vol. 12(2), pages 1-43, May.
    41. Xinyue He & Teresa Serra & Philip Garcia, 2021. "Resilience in “Flash Events” in the Corn and Lean Hog Futures Markets," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(2), pages 743-764, March.
    42. Chen, Yuanyuan & Gao, Xuefeng & Li, Duan, 2018. "Optimal order execution using hidden orders," Journal of Economic Dynamics and Control, Elsevier, vol. 94(C), pages 89-116.
    43. Ulrich Horst & Dorte Kreher, 2015. "A weak law of large numbers for a limit order book model with fully state dependent order dynamics," Papers 1502.04359, arXiv.org, revised May 2016.
    44. Alexandre Aidov & Olesya Lobanova, 2021. "The Relation between Intraday Limit Order Book Depth and Spread," IJFS, MDPI, vol. 9(4), pages 1-13, November.
    45. Amaya, Diego & Filbien, Jean-Yves & Okou, Cédric & Roch, Alexandre F., 2018. "Distilling liquidity costs from limit order books," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 16-34.
    46. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2013. "Limit order books," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1709-1742, November.
    47. Hautsch, Nikolaus & Huang, Ruihong, 2012. "On the dark side of the market: Identifying and analyzing hidden order placements," SFB 649 Discussion Papers 2012-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    48. Mircea BAHNA & Cosmin-Octavian CEPOI & Bogdan Andrei DUMITRESCU & Virgil DAMIAN, 2018. "Estimating the Price Impact of Market Orders on the Bucharest Stock Exchange," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 120-133, December.
    49. M. Frömmel & X. Han & F. Van Gysegem, 2013. "News, Liquidity Dynamics and Intraday Jumps: Evidence from the HUF/EUR market," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/848, Ghent University, Faculty of Economics and Business Administration.
    50. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    51. Emilio Said & Ahmed Bel Hadj Ayed & Alexandre Husson & Frédéric Abergel, 2018. "Market Impact: A Systematic Study of Limit Orders," Post-Print hal-01561128, HAL.
    52. Kyle Bechler & Michael Ludkovski, 2017. "Order Flows and Limit Order Book Resiliency on the Meso-Scale," Papers 1708.02715, arXiv.org.
    53. Rama Cont & Arseniy Kukanov & Sasha Stoikov, 2010. "The Price Impact of Order Book Events," Papers 1011.6402, arXiv.org, revised Apr 2011.
    54. Forsyth, P.A. & Kennedy, J.S. & Tse, S.T. & Windcliff, H., 2012. "Optimal trade execution: A mean quadratic variation approach," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1971-1991.
    55. Neil A. Chriss, 2024. "Optimal position-building strategies in competition," Papers 2409.03586, arXiv.org, revised Nov 2024.
    56. Emilio Said & Ahmed Bel Hadj Ayed & Alexandre Husson & Fr'ed'eric Abergel, 2018. "Market Impact: A Systematic Study of Limit Orders," Papers 1802.08502, arXiv.org, revised May 2022.
    57. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 4-2015, January-A.
    58. F. Campigli & G. Bormetti & F. Lillo, 2022. "Measuring price impact and information content of trades in a time-varying setting," Papers 2212.12687, arXiv.org, revised Dec 2023.
    59. Jia Zhai & Yi Cao & Xuemei Ding, 2018. "Data analytic approach for manipulation detection in stock market," Review of Quantitative Finance and Accounting, Springer, vol. 50(3), pages 897-932, April.
    60. Pham, Manh Cuong & Anderson, Heather Margot & Duong, Huu Nhan & Lajbcygier, Paul, 2020. "The effects of trade size and market depth on immediate price impact in a limit order book market," Journal of Economic Dynamics and Control, Elsevier, vol. 120(C).
    61. Çağlayan-Gümüş, Ayşe & Karahan, Cenk C., 2024. "Information content of the limit order book: A cross-sectional analysis in Borsa Istanbul," Global Finance Journal, Elsevier, vol. 62(C).

  43. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2009. "Quantifying high-frequency market reactions to real-time news sentiment announcements," SFB 649 Discussion Papers 2009-063, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Zhi-Qiang Jiang & Wen-Jie Xie & Xiong Xiong & Wei Zhang & Yong-Jie Zhang & W. -X. Zhou, 2012. "Trading networks, abnormal motifs and stock manipulation," Papers 1301.0007, arXiv.org.

  44. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2009. "Quantifying high-frequency market reactions to real-time news sentiment announcements," SFB 649 Discussion Papers 2009-063, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Zhi-Qiang Jiang & Wen-Jie Xie & Xiong Xiong & Wei Zhang & Yong-Jie Zhang & W. -X. Zhou, 2012. "Trading networks, abnormal motifs and stock manipulation," Papers 1301.0007, arXiv.org.

  45. Hautsch, Nikolaus & Kyj, Lada M. & Oomen, Roel C.A., 2009. "A blocking and regularization approach to high dimensional realized covariance estimation," SFB 649 Discussion Papers 2009-049, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Fengler, Matthias R. & Okhrin, Ostap, 2012. "Realized copula," SFB 649 Discussion Papers 2012-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    4. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    5. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    6. Manabu Asai & Michael McAleer, 2017. "The impact of jumps and leverage in forecasting covolatility," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 638-650, October.
    7. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    8. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Papers 1910.13960, arXiv.org, revised Oct 2020.
    9. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Tinbergen Institute Discussion Papers 14-037/III, Tinbergen Institute.
    10. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    11. Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
    12. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    13. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
    14. Corsi, Fulvio & Peluso, Stefano & Audrino, Francesco, 2012. "Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation," Economics Working Paper Series 1202, University of St. Gallen, School of Economics and Political Science.
    15. Peter Reinhard Hansen & Guillaume Horel & Asger Lunde & Ilya Archakov, 2015. "A Markov Chain Estimator of Multivariate Volatility from High Frequency Data," CREATES Research Papers 2015-19, Department of Economics and Business Economics, Aarhus University.
    16. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, Department of Economics and Business Economics, Aarhus University.
    17. Roxana Halbleib & Valeri Voev, 2011. "Forecasting Covariance Matrices: A Mixed Frequency Approach," CREATES Research Papers 2011-03, Department of Economics and Business Economics, Aarhus University.
    18. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    19. Vander Elst, Harry & Veredas, David, 2014. "Disentangled jump-robust realized covariances and correlations with non-synchronous prices," DES - Working Papers. Statistics and Econometrics. WS ws142416, Universidad Carlos III de Madrid. Departamento de Estadística.
    20. Ekaterina Seregina, 2020. "A Basket Half Full: Sparse Portfolios," Papers 2011.04278, arXiv.org, revised Apr 2021.
    21. Taras Bodnar & Nikolaus Hautsch & Yarema Okhrin & Nestor Parolya, 2024. "Consistent Estimation of the High-Dimensional Efficient Frontier," Papers 2409.15103, arXiv.org.
    22. Dong Hwan Oh & Andrew J. Patton, 2021. "Dynamic Factor Copula Models with Estimated Cluster Assignments," Finance and Economics Discussion Series 2021-029r1, Board of Governors of the Federal Reserve System (U.S.), revised 06 May 2022.
    23. De Lira Salvatierra, Irving & Patton, Andrew J., 2015. "Dynamic copula models and high frequency data," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 120-135.
    24. Griffin, Jim E. & Oomen, Roel C.A., 2011. "Covariance measurement in the presence of non-synchronous trading and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 58-68, January.
    25. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
    26. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    27. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    28. Bollerslev, Tim & Meddahi, Nour & Nyawa, Serge, 2019. "High-dimensional multivariate realized volatility estimation," Journal of Econometrics, Elsevier, vol. 212(1), pages 116-136.
    29. Kim Christensen & Mikkel Slot Nielsen & Mark Podolskij, 2021. "High-dimensional estimation of quadratic variation based on penalized realized variance," Papers 2103.03237, arXiv.org.
    30. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    31. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto Calogero, 2017. "Estimation and model-based combination of causality networks," SAFE Working Paper Series 165, Leibniz Institute for Financial Research SAFE.
    32. Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combinations," Papers 2011.02077, arXiv.org, revised May 2021.
    33. Dong Hwan Oh & Andrew J. Patton, 2015. "Modelling Dependence in High Dimensions with Factor Copulas," Finance and Economics Discussion Series 2015-51, Board of Governors of the Federal Reserve System (U.S.).
    34. Jian, Zhihong & Deng, Pingjun & Zhu, Zhican, 2018. "High-dimensional covariance forecasting based on principal component analysis of high-frequency data," Economic Modelling, Elsevier, vol. 75(C), pages 422-431.
    35. Luo, Jiawen & Chen, Langnan, 2020. "Realized volatility forecast with the Bayesian random compressed multivariate HAR model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 781-799.
    36. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
    37. Kim Christensen & Mikkel Slot Nielsen & Mark Podolskij, 2023. "High-dimensional estimation of quadratic variation based on penalized realized variance," Statistical Inference for Stochastic Processes, Springer, vol. 26(2), pages 331-359, July.
    38. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
    39. Laurent A. F. Callot & Anders B. Kock & Marcelo C. Medeiros, 2014. "Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice," CREATES Research Papers 2014-42, Department of Economics and Business Economics, Aarhus University.
    40. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    41. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    42. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2021. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 309-352, September.
    43. Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
    44. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    45. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    46. Barnes, George & Ramgoolam, Sanjaye & Stephanou, Michael, 2024. "Permutation invariant Gaussian matrix models for financial correlation matrices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 651(C).
    47. Tao, Minjing & Wang, Yahzen & Yao, Qiwei & Zou, Jian, 2011. "Large volatility matrix inference via combining low-frequency and high-frequency approaches," LSE Research Online Documents on Economics 39321, London School of Economics and Political Science, LSE Library.
    48. Harry Vander Elst & David Veredas, 2017. "Smoothing it Out: Empirical and Simulation Results for Disentangled Realized Covariances," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 106-138.
    49. Grønborg, Niels S. & Lunde, Asger & Olesen, Kasper V. & Vander Elst, Harry, 2022. "Realizing correlations across asset classes," Journal of Financial Markets, Elsevier, vol. 59(PA).

  46. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2009. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," CFS Working Paper Series 2009/18, Center for Financial Studies (CFS).

    Cited by:

    1. Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," CFS Working Paper Series 2009/23, Center for Financial Studies (CFS).
    2. Härdle, Wolfgang Karl & Majer, Piotr, 2012. "Yield curve modeling and forecasting using semiparametric factor dynamics," SFB 649 Discussion Papers 2012-048, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    4. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.
    5. Hautsch, Nikolaus & Huang, Ruihong, 2011. "Limit order flow, market impact and optimal order sizes: Evidence from NASDAQ TotalView-ITCH data," SFB 649 Discussion Papers 2011-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Choroś-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2016. "A semiparametric factor model for CDO surfaces dynamics," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 151-163.
    7. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
    9. Geir H. Bjønnes & Carol L. Osler & Dagfinn Rime, 2021. "Price discovery in two‐tier markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 3109-3133, April.
    10. Hai-Chuan Xu & Wei Chen & Xiong Xiong & Wei Zhang & Wei-Xing Zhou & H Eugene Stanley, 2016. "Limit-order book resiliency after effective market orders: Spread, depth and intensity," Papers 1602.00731, arXiv.org, revised Feb 2017.
    11. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
    12. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
    13. Siikanen, Milla & Kanniainen, Juho & Luoma, Arto, 2017. "What drives the sensitivity of limit order books to company announcement arrivals?," Economics Letters, Elsevier, vol. 159(C), pages 65-68.
    14. Chen Cathy Yi-Hsuan & Härdle Wolfgang Karl, 2017. "Data science and digital society," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 11(1), pages 669-675, July.
    15. Siikanen, Milla & Kanniainen, Juho & Valli, Jaakko, 2017. "Limit order books and liquidity around scheduled and non-scheduled announcements: Empirical evidence from NASDAQ Nordic," Finance Research Letters, Elsevier, vol. 21(C), pages 264-271.
    16. Kyle Bechler & Michael Ludkovski, 2017. "Order Flows and Limit Order Book Resiliency on the Meso-Scale," Papers 1708.02715, arXiv.org.
    17. Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019. "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1473-1489, September.
    18. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2017. "Dynamic semiparametric factor model with a common break," SFB 649 Discussion Papers 2017-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Choros-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2013. "CDO surfaces dynamics," SFB 649 Discussion Papers 2013-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  47. Hautsch, Nikolaus & Ou, Yangguoyi, 2009. "Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields," CFS Working Paper Series 2009/03, Center for Financial Studies (CFS).

    Cited by:

    1. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    2. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    3. B M, Lithin & chakraborty, Suman & iyer, Vishwanathan & M N, Nikhil & ledwani, Sanket, 2022. "Modeling asymmetric sovereign bond yield volatility with univariate GARCH models: Evidence from India," MPRA Paper 117067, University Library of Munich, Germany, revised 05 Jan 2023.
    4. Recchioni, Maria Cristina & Tedeschi, Gabriele, 2017. "From bond yield to macroeconomic instability: A parsimonious affine model," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1116-1135.
    5. Kleppe, Tore Selland & Liesenfeld, Roman & Moura, Guilherme Valle & Oglend, Atle, 2022. "Analyzing Commodity Futures Using Factor State-Space Models with Wishart Stochastic Volatility," Econometrics and Statistics, Elsevier, vol. 23(C), pages 105-127.
    6. Jens H. E. Christensen & Jose A. Lopez & Glenn D. Rudebusch, 2014. "Can Spanned Term Structure Factors Drive Stochastic Yield Volatility?," Working Paper Series 2014-3, Federal Reserve Bank of San Francisco.
    7. Marius Acatrinei, 2017. "Macroeconomic fundamentals and latent factor of the EU yield curve," EIOPA Financial Stability Report - Thematic Articles 11, EIOPA, Risks and Financial Stability Department.
    8. Cem Çakmakli, 2012. "Bayesian Semiparametric Dynamic Nelson-Siegel Model," Working Paper series 59_12, Rimini Centre for Economic Analysis, revised Sep 2012.
    9. Maria Cristina Recchioni & Gabriele Tedeschi, 2016. "From bond yield to macroeconomic instability: The effect of negative interest rates," Working Papers 2016/06, Economics Department, Universitat Jaume I, Castellón (Spain).

  48. Hautsch, Nikolaus & Ou, Yangguoyi, 2009. "Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields," CFS Working Paper Series 2009/03, Center for Financial Studies (CFS).

    Cited by:

    1. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    2. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    3. B M, Lithin & chakraborty, Suman & iyer, Vishwanathan & M N, Nikhil & ledwani, Sanket, 2022. "Modeling asymmetric sovereign bond yield volatility with univariate GARCH models: Evidence from India," MPRA Paper 117067, University Library of Munich, Germany, revised 05 Jan 2023.
    4. Recchioni, Maria Cristina & Tedeschi, Gabriele, 2017. "From bond yield to macroeconomic instability: A parsimonious affine model," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1116-1135.
    5. Kleppe, Tore Selland & Liesenfeld, Roman & Moura, Guilherme Valle & Oglend, Atle, 2022. "Analyzing Commodity Futures Using Factor State-Space Models with Wishart Stochastic Volatility," Econometrics and Statistics, Elsevier, vol. 23(C), pages 105-127.
    6. Jens H. E. Christensen & Jose A. Lopez & Glenn D. Rudebusch, 2014. "Can Spanned Term Structure Factors Drive Stochastic Yield Volatility?," Working Paper Series 2014-3, Federal Reserve Bank of San Francisco.
    7. Marius Acatrinei, 2017. "Macroeconomic fundamentals and latent factor of the EU yield curve," EIOPA Financial Stability Report - Thematic Articles 11, EIOPA, Risks and Financial Stability Department.
    8. Cem Çakmakli, 2012. "Bayesian Semiparametric Dynamic Nelson-Siegel Model," Working Paper series 59_12, Rimini Centre for Economic Analysis, revised Sep 2012.
    9. Maria Cristina Recchioni & Gabriele Tedeschi, 2016. "From bond yield to macroeconomic instability: The effect of negative interest rates," Working Papers 2016/06, Economics Department, Universitat Jaume I, Castellón (Spain).

  49. Hautsch, Nikolaus & Kyj, Lada M. & Oomen, Roel C.A., 2009. "A blocking and regularization approach to high dimensional realized covariance estimation," SFB 649 Discussion Papers 2009-049, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Fengler, Matthias R. & Okhrin, Ostap, 2012. "Realized copula," SFB 649 Discussion Papers 2012-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    4. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    5. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    6. Manabu Asai & Michael McAleer, 2017. "The impact of jumps and leverage in forecasting covolatility," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 638-650, October.
    7. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    8. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Papers 1910.13960, arXiv.org, revised Oct 2020.
    9. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Tinbergen Institute Discussion Papers 14-037/III, Tinbergen Institute.
    10. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    11. Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
    12. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    13. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
    14. Corsi, Fulvio & Peluso, Stefano & Audrino, Francesco, 2012. "Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation," Economics Working Paper Series 1202, University of St. Gallen, School of Economics and Political Science.
    15. Peter Reinhard Hansen & Guillaume Horel & Asger Lunde & Ilya Archakov, 2015. "A Markov Chain Estimator of Multivariate Volatility from High Frequency Data," CREATES Research Papers 2015-19, Department of Economics and Business Economics, Aarhus University.
    16. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, Department of Economics and Business Economics, Aarhus University.
    17. Roxana Halbleib & Valeri Voev, 2011. "Forecasting Covariance Matrices: A Mixed Frequency Approach," CREATES Research Papers 2011-03, Department of Economics and Business Economics, Aarhus University.
    18. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    19. Vander Elst, Harry & Veredas, David, 2014. "Disentangled jump-robust realized covariances and correlations with non-synchronous prices," DES - Working Papers. Statistics and Econometrics. WS ws142416, Universidad Carlos III de Madrid. Departamento de Estadística.
    20. Ekaterina Seregina, 2020. "A Basket Half Full: Sparse Portfolios," Papers 2011.04278, arXiv.org, revised Apr 2021.
    21. Taras Bodnar & Nikolaus Hautsch & Yarema Okhrin & Nestor Parolya, 2024. "Consistent Estimation of the High-Dimensional Efficient Frontier," Papers 2409.15103, arXiv.org.
    22. Dong Hwan Oh & Andrew J. Patton, 2021. "Dynamic Factor Copula Models with Estimated Cluster Assignments," Finance and Economics Discussion Series 2021-029r1, Board of Governors of the Federal Reserve System (U.S.), revised 06 May 2022.
    23. De Lira Salvatierra, Irving & Patton, Andrew J., 2015. "Dynamic copula models and high frequency data," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 120-135.
    24. Griffin, Jim E. & Oomen, Roel C.A., 2011. "Covariance measurement in the presence of non-synchronous trading and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 58-68, January.
    25. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
    26. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    27. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    28. Bollerslev, Tim & Meddahi, Nour & Nyawa, Serge, 2019. "High-dimensional multivariate realized volatility estimation," Journal of Econometrics, Elsevier, vol. 212(1), pages 116-136.
    29. Kim Christensen & Mikkel Slot Nielsen & Mark Podolskij, 2021. "High-dimensional estimation of quadratic variation based on penalized realized variance," Papers 2103.03237, arXiv.org.
    30. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    31. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto Calogero, 2017. "Estimation and model-based combination of causality networks," SAFE Working Paper Series 165, Leibniz Institute for Financial Research SAFE.
    32. Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combinations," Papers 2011.02077, arXiv.org, revised May 2021.
    33. Dong Hwan Oh & Andrew J. Patton, 2015. "Modelling Dependence in High Dimensions with Factor Copulas," Finance and Economics Discussion Series 2015-51, Board of Governors of the Federal Reserve System (U.S.).
    34. Jian, Zhihong & Deng, Pingjun & Zhu, Zhican, 2018. "High-dimensional covariance forecasting based on principal component analysis of high-frequency data," Economic Modelling, Elsevier, vol. 75(C), pages 422-431.
    35. Luo, Jiawen & Chen, Langnan, 2020. "Realized volatility forecast with the Bayesian random compressed multivariate HAR model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 781-799.
    36. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
    37. Kim Christensen & Mikkel Slot Nielsen & Mark Podolskij, 2023. "High-dimensional estimation of quadratic variation based on penalized realized variance," Statistical Inference for Stochastic Processes, Springer, vol. 26(2), pages 331-359, July.
    38. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
    39. Laurent A. F. Callot & Anders B. Kock & Marcelo C. Medeiros, 2014. "Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice," CREATES Research Papers 2014-42, Department of Economics and Business Economics, Aarhus University.
    40. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    41. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    42. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2021. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 309-352, September.
    43. Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
    44. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    45. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    46. Barnes, George & Ramgoolam, Sanjaye & Stephanou, Michael, 2024. "Permutation invariant Gaussian matrix models for financial correlation matrices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 651(C).
    47. Tao, Minjing & Wang, Yahzen & Yao, Qiwei & Zou, Jian, 2011. "Large volatility matrix inference via combining low-frequency and high-frequency approaches," LSE Research Online Documents on Economics 39321, London School of Economics and Political Science, LSE Library.
    48. Harry Vander Elst & David Veredas, 2017. "Smoothing it Out: Empirical and Simulation Results for Disentangled Realized Covariances," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 106-138.
    49. Grønborg, Niels S. & Lunde, Asger & Olesen, Kasper V. & Vander Elst, Harry, 2022. "Realizing correlations across asset classes," Journal of Financial Markets, Elsevier, vol. 59(PA).

  50. Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," SFB 649 Discussion Papers 2009-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Fabrizio Pomponio & Frédéric Abergel, 2013. "Multiple-limit trades : empirical facts and application to lead-lag measures," Post-Print hal-00745317, HAL.
    2. Cebiroğlu, Gökhan & Horst, Ulrich, 2012. "Hidden liquidity: Determinants and impact," SFB 649 Discussion Papers 2012-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Fleming, Michael J. & Mizrach, Bruce & Nguyen, Giang, 2018. "The microstructure of a U.S. Treasury ECN: The BrokerTec platform," Journal of Financial Markets, Elsevier, vol. 40(C), pages 2-22.
    4. Mehdi Arzandeh & Julieta Frank, 2019. "Price Discovery in Agricultural Futures Markets: Should We Look beyond the Best Bid-Ask Spread?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(5), pages 1482-1498.
    5. Esen Onur & John S. Roberts & Tugkan Tuzun, 2017. "Trader Positions and Marketwide Liquidity Demand," Finance and Economics Discussion Series 2017-103, Board of Governors of the Federal Reserve System (U.S.).
    6. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
    7. Baruch, Shmuel & Panayides, Marios & Venkataraman, Kumar, 2017. "Informed trading and price discovery before corporate events," Journal of Financial Economics, Elsevier, vol. 125(3), pages 561-588.
    8. Timoth'ee Fabre & Vincent Ragel, 2023. "Interpretable ML for High-Frequency Execution," Papers 2307.04863, arXiv.org, revised Sep 2024.
    9. Cebiroglu, Gökhan & Hautsch, Nikolaus & Horst, Ulrich, 2014. "Order exposure and liquidity coordination: Does hidden liquidity harm price efficiency?," CFS Working Paper Series 468, Center for Financial Studies (CFS).
    10. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    11. Härdle, Wolfgang Karl & Chen, Shi & Liang, Chong & Schienle, Melanie, 2018. "Time-varying Limit Order Book Networks," IRTG 1792 Discussion Papers 2018-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Han, SeungOh, 2024. "Price clustering on cryptocurrency order books at a US-based exchange," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    13. Jose Blanchet & Xinyun Chen, 2013. "Continuous-time Modeling of Bid-Ask Spread and Price Dynamics in Limit Order Books," Papers 1310.1103, arXiv.org.
    14. Zhu, Hongyu & Yamamoto, Ryuichi, 2022. "Order submission, information asymmetry, and tick size," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    15. Hautsch, Nikolaus & Huang, Ruihong, 2011. "Limit order flow, market impact and optimal order sizes: Evidence from NASDAQ TotalView-ITCH data," SFB 649 Discussion Papers 2011-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. Nikolaus Hautsch & Mark Podolskij, 2010. "Pre-Averaging Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence," CREATES Research Papers 2010-29, Department of Economics and Business Economics, Aarhus University.
    17. Xue, Yi & Gençay, Ramazan, 2012. "Hierarchical information and the rate of information diffusion," Journal of Economic Dynamics and Control, Elsevier, vol. 36(9), pages 1372-1401.
    18. Yi Cao & Jia Zhai, 2022. "Estimating price impact via deep reinforcement learning," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3954-3970, October.
    19. Chen, Shi & Härdle, Wolfgang & Schienle, Melanie, 2021. "High-dimensional statistical learning techniques for time-varying limit order book networks," IRTG 1792 Discussion Papers 2021-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    20. Yergeau, Gabriel, 2016. "Profitability and Market Quality of High Frequency Market-makers: An Empirical Investigation," Working Papers 16-3, HEC Montreal, Canada Research Chair in Risk Management.
    21. Tejas Ramdas & Martin T. Wells, 2024. "Bellwether Trades: Characteristics of Trades influential in Predicting Future Price Movements in Markets," Papers 2409.05192, arXiv.org.
    22. Erdinc Akyildirim & Shaen Corbet & Guzhan Gulay & Duc Khuong Nguyen & Ahmet Sensoy, 2019. "Order Flow Persistence in Equity Spot and Futures Markets: Evidence from a Dynamic Emerging Market," Working Papers 2019-011, Department of Research, Ipag Business School.
    23. Comerton-Forde, Carole & Putniņš, Tālis J., 2015. "Dark trading and price discovery," Journal of Financial Economics, Elsevier, vol. 118(1), pages 70-92.
    24. Nikolaus Hautsch & Dieter Hess & David Veredas, 2010. "The impact of macroeconomic news on quote adjustments, noise and informational volatility," Working Papers ECARES 2010-004, ULB -- Universite Libre de Bruxelles.
    25. Francesco Calvori & Fabrizio Cipollini & Giampiero M. Gallo, 2014. "Go with the Flow: A GAS model for Predicting Intra-daily Volume Shares," Econometrics Working Papers Archive 2014_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    26. Fabrizio Pomponio & Frederic Abergel, 2012. "Multiple-limit trades: empirical facts and application to lead--lag measures," Quantitative Finance, Taylor & Francis Journals, vol. 13(5), pages 783-793, September.
    27. Lo, Danny K. & Hall, Anthony D., 2015. "Resiliency of the limit order book," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 222-244.
    28. Chaboud, Alain & Hjalmarsson, Erik & Zikes, Filip, 2021. "The evolution of price discovery in an electronic market," Journal of Banking & Finance, Elsevier, vol. 130(C).
    29. Zoltán Eisler & Jean-Philippe Bouchaud & Julien Kockelkoren, 2012. "The price impact of order book events: market orders, limit orders and cancellations," Quantitative Finance, Taylor & Francis Journals, vol. 12(9), pages 1395-1419, September.
    30. Li, Zhicheng & Chen, Xinyun & Xing, Haipeng, 2023. "A multifactor regime-switching model for inter-trade durations in the high-frequency limit order market," Economic Modelling, Elsevier, vol. 118(C).
    31. Antonio Figueiredo & Pankaj Jain & Suchismita Mishra, 2023. "The role of fleeting orders on option expiration days," Quantitative Finance, Taylor & Francis Journals, vol. 23(10), pages 1511-1529, October.
    32. Thomas A. P. de Boer & Cornelis Gardebroek & Joost M. E. Pennings & Andres Trujillo‐Barrera, 2022. "Intraday liquidity in soybean complex futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1189-1211, July.
    33. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    34. Johannes Bleher & Michael Bleher & Thomas Dimpfl, 2020. "From orders to prices: A stochastic description of the limit order book to forecast intraday returns," Papers 2004.11953, arXiv.org, revised May 2021.
    35. Alex Frino & Ognjen Kovačević & Vito Mollica, 2019. "Depths and spreads in futures markets: Relationship with order execution, submission, and cancellation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(5), pages 590-599, May.
    36. Cebiroğlu, Gökhan & Horst, Ulrich, 2015. "Optimal order display in limit order markets with liquidity competition," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 81-100.
    37. Będowska-Sójka, Barbara, 2020. "Do aggressive orders affect liquidity? An evidence from an emerging market," Research in International Business and Finance, Elsevier, vol. 54(C).
    38. Andrea Coletta & Joseph Jerome & Rahul Savani & Svitlana Vyetrenko, 2023. "Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness," Papers 2306.12806, arXiv.org.
    39. Zhicheng Li & Haipeng Xing & Xinyun Chen, 2019. "A multifactor regime-switching model for inter-trade durations in the limit order market," Papers 1912.00764, arXiv.org.
    40. Xintong Wang & Christopher Hoang & Yevgeniy Vorobeychik & Michael P. Wellman, 2021. "Spoofing the Limit Order Book: A Strategic Agent-Based Analysis," Games, MDPI, vol. 12(2), pages 1-43, May.
    41. Xinyue He & Teresa Serra & Philip Garcia, 2021. "Resilience in “Flash Events” in the Corn and Lean Hog Futures Markets," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(2), pages 743-764, March.
    42. Chen, Yuanyuan & Gao, Xuefeng & Li, Duan, 2018. "Optimal order execution using hidden orders," Journal of Economic Dynamics and Control, Elsevier, vol. 94(C), pages 89-116.
    43. Ulrich Horst & Dorte Kreher, 2015. "A weak law of large numbers for a limit order book model with fully state dependent order dynamics," Papers 1502.04359, arXiv.org, revised May 2016.
    44. Alexandre Aidov & Olesya Lobanova, 2021. "The Relation between Intraday Limit Order Book Depth and Spread," IJFS, MDPI, vol. 9(4), pages 1-13, November.
    45. Amaya, Diego & Filbien, Jean-Yves & Okou, Cédric & Roch, Alexandre F., 2018. "Distilling liquidity costs from limit order books," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 16-34.
    46. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2013. "Limit order books," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1709-1742, November.
    47. Hautsch, Nikolaus & Huang, Ruihong, 2012. "On the dark side of the market: Identifying and analyzing hidden order placements," SFB 649 Discussion Papers 2012-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    48. Mircea BAHNA & Cosmin-Octavian CEPOI & Bogdan Andrei DUMITRESCU & Virgil DAMIAN, 2018. "Estimating the Price Impact of Market Orders on the Bucharest Stock Exchange," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 120-133, December.
    49. M. Frömmel & X. Han & F. Van Gysegem, 2013. "News, Liquidity Dynamics and Intraday Jumps: Evidence from the HUF/EUR market," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/848, Ghent University, Faculty of Economics and Business Administration.
    50. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    51. Emilio Said & Ahmed Bel Hadj Ayed & Alexandre Husson & Frédéric Abergel, 2018. "Market Impact: A Systematic Study of Limit Orders," Post-Print hal-01561128, HAL.
    52. Kyle Bechler & Michael Ludkovski, 2017. "Order Flows and Limit Order Book Resiliency on the Meso-Scale," Papers 1708.02715, arXiv.org.
    53. Rama Cont & Arseniy Kukanov & Sasha Stoikov, 2010. "The Price Impact of Order Book Events," Papers 1011.6402, arXiv.org, revised Apr 2011.
    54. Forsyth, P.A. & Kennedy, J.S. & Tse, S.T. & Windcliff, H., 2012. "Optimal trade execution: A mean quadratic variation approach," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1971-1991.
    55. Neil A. Chriss, 2024. "Optimal position-building strategies in competition," Papers 2409.03586, arXiv.org, revised Nov 2024.
    56. Emilio Said & Ahmed Bel Hadj Ayed & Alexandre Husson & Fr'ed'eric Abergel, 2018. "Market Impact: A Systematic Study of Limit Orders," Papers 1802.08502, arXiv.org, revised May 2022.
    57. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 4-2015, January-A.
    58. F. Campigli & G. Bormetti & F. Lillo, 2022. "Measuring price impact and information content of trades in a time-varying setting," Papers 2212.12687, arXiv.org, revised Dec 2023.
    59. Jia Zhai & Yi Cao & Xuemei Ding, 2018. "Data analytic approach for manipulation detection in stock market," Review of Quantitative Finance and Accounting, Springer, vol. 50(3), pages 897-932, April.
    60. Pham, Manh Cuong & Anderson, Heather Margot & Duong, Huu Nhan & Lajbcygier, Paul, 2020. "The effects of trade size and market depth on immediate price impact in a limit order book market," Journal of Economic Dynamics and Control, Elsevier, vol. 120(C).
    61. Çağlayan-Gümüş, Ayşe & Karahan, Cenk C., 2024. "Information content of the limit order book: A cross-sectional analysis in Borsa Istanbul," Global Finance Journal, Elsevier, vol. 62(C).

  51. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Pigorsch, Uta, 2008. "Measuring and modeling risk using high-frequency data," SFB 649 Discussion Papers 2008-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Zhang, Zhengjun & Zhu, Bin, 2016. "Copula structured M4 processes with application to high-frequency financial data," Journal of Econometrics, Elsevier, vol. 194(2), pages 231-241.
    2. Weber, Enzo & Zhang, Yanqun, 2012. "Common influences, spillover and integration in Chinese stock markets," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 382-394.
    3. Dannewald, Till & Hildebrandt, Lutz, 2008. "A brand specific investigation of international cost shock threats on price and margin with a manufacturer-wholesaler-retailer model," SFB 649 Discussion Papers 2008-070, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Weber, Enzo, 2008. "Structural dynamic conditional correlation," SFB 649 Discussion Papers 2008-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  52. Hautsch, Nikolaus & Hess, Dieter E. & Müller, Christoph, 2008. "Price adjustment to news with uncertain precision," SFB 649 Discussion Papers 2008-025, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Nikolaus Hautsch & Dieter Hess & David Veredas, 2010. "The impact of macroeconomic news on quote adjustments, noise and informational volatility," Working Papers ECARES 2010-004, ULB -- Universite Libre de Bruxelles.
    2. Pervaiz Alam & Xiaoling Pu & Barry Hettler & Hai Lin, 2020. "The pricing of accruals quality in credit default swap spreads," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(3), pages 1943-1977, September.
    3. Hess, Dieter & Orbe, Sebastian, 2011. "Irrationality or efficiency of macroeconomic survey forecasts? Implications from the anchoring bias test," CFR Working Papers 11-13, University of Cologne, Centre for Financial Research (CFR).

  53. Hautsch, Nikolaus & Hess, Dieter E. & Müller, Christoph, 2008. "Price adjustment to news with uncertain precision," SFB 649 Discussion Papers 2008-025, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Nikolaus Hautsch & Dieter Hess & David Veredas, 2010. "The impact of macroeconomic news on quote adjustments, noise and informational volatility," Working Papers ECARES 2010-004, ULB -- Universite Libre de Bruxelles.
    2. Pervaiz Alam & Xiaoling Pu & Barry Hettler & Hai Lin, 2020. "The pricing of accruals quality in credit default swap spreads," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(3), pages 1943-1977, September.
    3. Hess, Dieter & Orbe, Sebastian, 2011. "Irrationality or efficiency of macroeconomic survey forecasts? Implications from the anchoring bias test," CFR Working Papers 11-13, University of Cologne, Centre for Financial Research (CFR).

  54. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Pigorsch, Uta, 2008. "Measuring and modeling risk using high-frequency data," SFB 649 Discussion Papers 2008-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Zhang, Zhengjun & Zhu, Bin, 2016. "Copula structured M4 processes with application to high-frequency financial data," Journal of Econometrics, Elsevier, vol. 194(2), pages 231-241.
    2. Weber, Enzo & Zhang, Yanqun, 2012. "Common influences, spillover and integration in Chinese stock markets," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 382-394.
    3. Dannewald, Till & Hildebrandt, Lutz, 2008. "A brand specific investigation of international cost shock threats on price and margin with a manufacturer-wholesaler-retailer model," SFB 649 Discussion Papers 2008-070, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Weber, Enzo, 2008. "Structural dynamic conditional correlation," SFB 649 Discussion Papers 2008-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  55. Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    2. Vahidin Jeleskovic & Anastasios Demertzidis, 2018. "Comparing different methods for the estimation of interbank intraday yield curves," MAGKS Papers on Economics 201839, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Chen, Shiyi & Jeong, Kiho & Härdle, Wolfgang Karl, 2008. "Recurrent support vector regression for a nonlinear ARMA model with applications to forecasting financial returns," SFB 649 Discussion Papers 2008-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Borak, Szymon & Weron, Rafał, 2008. "A semiparametric factor model for electricity forward curve dynamics," SFB 649 Discussion Papers 2008-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Markus Engler & Vahidin Jeleskovic, 2016. "Intraday volatility, trading volume and trading intensity in the interbank market e-MID," MAGKS Papers on Economics 201648, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Będowska-Sójka, Barbara & Kliber, Agata, 2019. "The causality between liquidity and volatility in the Polish stock market," Finance Research Letters, Elsevier, vol. 30(C), pages 110-115.
    7. Anastasios Demertzidis & Vahidin Jeleskovic, 2021. "Empirical Estimation of Intraday Yield Curves on the Italian Interbank Credit Market e-MID," JRFM, MDPI, vol. 14(5), pages 1-23, May.
    8. Anastasios Demertzidis, 2019. "Interbank transactions on the intraday frequency: -Different market states and the effects of the financial crisis-," MAGKS Papers on Economics 201932, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

  56. Hautsch, Nikolaus & Ou, Yangguoyi, 2008. "Discrete-time stochastic volatility models and MCMC-based statistical inference," SFB 649 Discussion Papers 2008-063, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Saranya, K. & Prasanna, P. Krishna, 2018. "Estimating stochastic volatility with jumps and asymmetry in Asian markets," Finance Research Letters, Elsevier, vol. 25(C), pages 145-153.

  57. Hautsch, Nikolaus & Ou, Yangguoyi, 2008. "Discrete-time stochastic volatility models and MCMC-based statistical inference," SFB 649 Discussion Papers 2008-063, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Saranya, K. & Prasanna, P. Krishna, 2018. "Estimating stochastic volatility with jumps and asymmetry in Asian markets," Finance Research Letters, Elsevier, vol. 25(C), pages 145-153.

  58. Hautsch, Nikolaus & Ou, Yangguoyi, 2008. "Yield curve factors, term structure volatility, and bond risk premia," SFB 649 Discussion Papers 2008-053, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hautsch, Nikolaus & Yang, Fuyu, 2010. "Bayesian inference in a stochastic volatility Nelson-Siegel Model," SFB 649 Discussion Papers 2010-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Anna Cieslak & Pavol Povala, 2016. "Information in the Term Structure of Yield Curve Volatility," Journal of Finance, American Finance Association, vol. 71(3), pages 1393-1436, June.
    3. Härdle, Wolfgang Karl & Majer, Piotr, 2012. "Yield curve modeling and forecasting using semiparametric factor dynamics," SFB 649 Discussion Papers 2012-048, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Nath, Golaka, 2012. "Estimating term structure changes using principal component analysis in Indian sovereign bond market," MPRA Paper 39229, University Library of Munich, Germany.
    5. Song, Song & Härdle, Wolfgang Karl & Ritov, Ya'acov, 2010. "High dimensional nonstationary time series modelling with generalized dynamic semiparametric factor model," SFB 649 Discussion Papers 2010-039, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  59. Hautsch, Nikolaus & Ou, Yangguoyi, 2008. "Yield curve factors, term structure volatility, and bond risk premia," SFB 649 Discussion Papers 2008-053, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hautsch, Nikolaus & Yang, Fuyu, 2010. "Bayesian inference in a stochastic volatility Nelson-Siegel Model," SFB 649 Discussion Papers 2010-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Anna Cieslak & Pavol Povala, 2016. "Information in the Term Structure of Yield Curve Volatility," Journal of Finance, American Finance Association, vol. 71(3), pages 1393-1436, June.
    3. Härdle, Wolfgang Karl & Majer, Piotr, 2012. "Yield curve modeling and forecasting using semiparametric factor dynamics," SFB 649 Discussion Papers 2012-048, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Nath, Golaka, 2012. "Estimating term structure changes using principal component analysis in Indian sovereign bond market," MPRA Paper 39229, University Library of Munich, Germany.
    5. Song, Song & Härdle, Wolfgang Karl & Ritov, Ya'acov, 2010. "High dimensional nonstationary time series modelling with generalized dynamic semiparametric factor model," SFB 649 Discussion Papers 2010-039, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  60. Hautsch, Nikolaus, 2007. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," CFS Working Paper Series 2007/25, Center for Financial Studies (CFS).

    Cited by:

    1. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Ng, F.C. & Li, W.K. & Yu, Philip L.H., 2016. "Diagnostic checking of the vector multiplicative error model," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 86-97.
    3. Karanasos, Menelaos & Xu, Yongdeng & Yfanti, Stavroula, 2017. "Constrained QML Estimation for Multivariate Asymmetric MEM with Spillovers: The Practicality of Matrix Inequalities," Cardiff Economics Working Papers E2017/14, Cardiff University, Cardiff Business School, Economics Section.
    4. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 321-340, March.
    6. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    7. Vahidin Jeleskovic, 2024. "An Empirical Analysis of Scam Tokens on Ethereum Blockchain," Papers 2402.19399, arXiv.org, revised Mar 2024.
    8. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.
    9. Nikolaus Hautsch & Dieter Hess & David Veredas, 2010. "The impact of macroeconomic news on quote adjustments, noise and informational volatility," Working Papers ECARES 2010-004, ULB -- Universite Libre de Bruxelles.
    10. Cipollini, Fabrizio & Gallo, Giampiero M., 2025. "Multiplicative Error Models: 20 years on," Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
    11. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).
    12. Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Markus Engler & Vahidin Jeleskovic, 2016. "Intraday volatility, trading volume and trading intensity in the interbank market e-MID," MAGKS Papers on Economics 201648, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    14. Luintel, Kul B & Xu, Yongdeng, 2013. "Testing weak exogeneity in multiplicative error models," Cardiff Economics Working Papers E2013/6, Cardiff University, Cardiff Business School, Economics Section.
    15. David German & Henry Schellhorn, 2012. "A No-Arbitrage Model of Liquidity in Financial Markets involving Brownian Sheets," Papers 1206.4804, arXiv.org.
    16. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    17. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    18. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    19. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula–Based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics, MDPI, vol. 5(2), pages 1-24, April.
    20. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2009. "Quantifying high-frequency market reactions to real-time news sentiment announcements," SFB 649 Discussion Papers 2009-063, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    21. Arango, Ignacio & Agudelo, Diego A., 2019. "How does information disclosure affect liquidity? Evidence from an emerging market," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    22. Sergey Lototsky & Henry Schellhorn & Ran Zhao, 2016. "A String Model of Liquidity in Financial Markets," Papers 1608.05900, arXiv.org, revised Apr 2018.
    23. Brownlees Christian T. & Vannucci Marina, 2013. "A Bayesian approach for capturing daily heterogeneity in intra-daily durations time series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 21-46, February.
    24. Ke, Rui & Lu, Wanbo & Jia, Jing, 2021. "Evaluating multiplicative error models: A residual-based approach," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).

  61. Bauwens, Luc & Hautsch, Nikolaus, 2007. "Modelling financial high frequency data using point processes," SFB 649 Discussion Papers 2007-066, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Maxime Morariu-Patrichi & Mikko S. Pakkanen, 2018. "State-dependent Hawkes processes and their application to limit order book modelling," Papers 1809.08060, arXiv.org, revised Sep 2021.
    2. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
    3. Bacry, E. & Delattre, S. & Hoffmann, M. & Muzy, J.F., 2013. "Some limit theorems for Hawkes processes and application to financial statistics," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2475-2499.
    4. Qi Guo & Bruno Remillard & Anatoliy Swishchuk, 2020. "Multivariate General Compound Point Processes in Limit Order Books," Risks, MDPI, vol. 8(3), pages 1-20, September.
    5. Pietro Fodra & Huy^en Pham, 2013. "High frequency trading and asymptotics for small risk aversion in a Markov renewal model," Papers 1310.1756, arXiv.org, revised Jan 2015.
    6. Roueff, Francois & von Sachs, Rainer & Sansonnet, Laure, 2015. "Time-frequency analysis of locally stationary Hawkes processes," LIDAM Discussion Papers ISBA 2015011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Zhang, Yaohua & Zou, Jian & Ravishanker, Nalini & Thavaneswaran, Aerambamoorthy, 2019. "Modeling financial durations using penalized estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 145-158.
    8. Alessio Sancetta, 2017. "Estimation for the Prediction of Point Processes with Many Covariates," Papers 1702.05315, arXiv.org.
    9. Brendan P.M. McCabe & Gael Martin & Keith Freeland, 2010. "A Quasi-locally Most powerful Test for Correlation in the conditional Variance of Positive Data," Monash Econometrics and Business Statistics Working Papers 2/10, Monash University, Department of Econometrics and Business Statistics.
    10. Vasileios Siakoulis & Ioannis Venetis, 2015. "On inter-arrival times of bond market extreme events. An application to seven European markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(4), pages 717-741, October.
    11. Emmanuel Bacry & Jean-Francois Muzy, 2014. "Second order statistics characterization of Hawkes processes and non-parametric estimation," Papers 1401.0903, arXiv.org, revised Feb 2015.
    12. Katarzyna Bień-Barkowska, 2014. "Capturing Order Book Dynamics in the Interbank EUR/PLN Spot Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 93-117, January.
    13. Kyungsub Lee, 2022. "Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures," Papers 2207.05939, arXiv.org, revised Sep 2024.
    14. Angelos Dassios & Xin Dong, 2014. "Stationarity of Bivariate Dynamic Contagion Processes," Papers 1405.5842, arXiv.org.
    15. Monira Essa Aloud, 2016. "Time Series Analysis Indicators under Directional Changes: The Case of Saudi Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 55-64.
    16. Ketelbuters, John John & Hainaut, Donatien, 2021. "Time-Consistent Evaluation of Credit Risk with Contagion," LIDAM Discussion Papers ISBA 2021004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    17. Gurgul Henryk & Machno Artur, 2017. "Trade Pattern on Warsaw Stock Exchange and Prediction of Number of Trades," Statistics in Transition New Series, Statistics Poland, vol. 18(1), pages 91-114, March.
    18. Alexander Saichev & Thomas Maillart & Didier Sornette, 2013. "Hierarchy of temporal responses of multivariate self-excited epidemic processes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(4), pages 1-19, April.
    19. Marcello Rambaldi & Vladimir Filimonov & Fabrizio Lillo, 2016. "Detection of intensity bursts using Hawkes processes: an application to high frequency financial data," Papers 1610.05383, arXiv.org.
    20. Anatoliy Swishchuk & Aiden Huffman, 2020. "General Compound Hawkes Processes in Limit Order Books," Risks, MDPI, vol. 8(1), pages 1-25, March.
    21. Hamza Bodor & Laurent Carlier, 2024. "A Novel Approach to Queue-Reactive Models: The Importance of Order Sizes," Papers 2405.18594, arXiv.org.
    22. Ban Zheng & François Roueff & Frédéric Abergel, 2014. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Post-Print hal-00777941, HAL.
    23. Steffen Volkenand & Günther Filler & Martin Odening, 2020. "Price Discovery and Market Reflexivity in Agricultural Futures Contracts with Different Maturities," Risks, MDPI, vol. 8(3), pages 1-17, July.
    24. Álvaro Cartea, 2013. "Derivatives pricing with marked point processes using tick-by-tick data," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 111-123, January.
    25. Aman Ullah & Mardi Dungey & Xiangdong Long & Yun Wang, 2014. "A Semiparametric Conditional Duration Model," Working Papers 201408, University of California at Riverside, Department of Economics.
    26. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    27. Donatien Hainaut, 2016. "A bivariate Hawkes process based model, for interest rates," Post-Print hal-01458162, HAL.
    28. Zhu, Lingjiong, 2013. "Moderate deviations for Hawkes processes," Statistics & Probability Letters, Elsevier, vol. 83(3), pages 885-890.
    29. Ioane Muni Toke, 2011. ""Market making" behaviour in an order book model and its impact on the bid-ask spread," Post-Print hal-01705266, HAL.
    30. Chavez-Demoulin, V. & McGill, J.A., 2012. "High-frequency financial data modeling using Hawkes processes," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3415-3426.
    31. Anatoliy Swishchuk & Aiden Huffman, 2018. "General Compound Hawkes Processes in Limit Order Books," Papers 1812.02298, arXiv.org.
    32. Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
    33. Zhicheng Li & Haipeng Xing, 2022. "High-Frequency Quote Volatility Measurement Using a Change-Point Intensity Model," Mathematics, MDPI, vol. 10(4), pages 1-24, February.
    34. Dassios, Angelos & Jang, Jiwook & Zhao, Hongbiao, 2019. "A generalised CIR process with externally-exciting and self-exciting jumps and its applications in insurance and finance," LSE Research Online Documents on Economics 102043, London School of Economics and Political Science, LSE Library.
    35. Denisa Georgiana Banulescu & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2013. "High-Frequency Risk Measures," Working Papers halshs-00859456, HAL.
    36. Pietro Fodra & Huyen Pham, 2013. "High frequency trading in a Markov renewal model," Working Papers hal-00867113, HAL.
    37. E. Bacry & K. Dayri & J. F. Muzy, 2011. "Non-parametric kernel estimation for symmetric Hawkes processes. Application to high frequency financial data," Papers 1112.1838, arXiv.org.
    38. Wang, Haixu, 2022. "Limit theorems for a discrete-time marked Hawkes process," Statistics & Probability Letters, Elsevier, vol. 184(C).
    39. Ioane Muni Toke, 2010. ""Market making" behaviour in an order book model and its impact on the bid-ask spread," Papers 1003.3796, arXiv.org, revised Jun 2010.
    40. Ye, Wuyi & Xia, Wenjing & Wu, Bin & Chen, Pengzhan, 2022. "Using implied volatility jumps for realized volatility forecasting: Evidence from the Chinese market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    41. Volodymyr Korniichuk, 2012. "Forecasting extreme electricity spot prices," Cologne Graduate School Working Paper Series 03-14, Cologne Graduate School in Management, Economics and Social Sciences.
    42. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2015. "Modelling systemic price cojumps with Hawkes factor models," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1137-1156, July.
    43. Anatoliy Swishchuk, 2017. "General Compound Hawkes Processes in Limit Order Books," Papers 1706.07459, arXiv.org, revised Jun 2017.
    44. Wei Sun & Svetlozar Rachev & Frank Fabozzi & Petko Kalev, 2008. "Fractals in trade duration: capturing long-range dependence and heavy tailedness in modeling trade duration," Annals of Finance, Springer, vol. 4(2), pages 217-241, March.
    45. Wheatley, Spencer & Filimonov, Vladimir & Sornette, Didier, 2016. "The Hawkes process with renewal immigration & its estimation with an EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 120-135.
    46. Anatoliy Swishchuk & Bruno Remillard & Robert Elliott & Jonathan Chavez-Casillas, 2017. "Compound Hawkes Processes in Limit Order Books," Papers 1712.03106, arXiv.org.
    47. Marcello Rambaldi & Emmanuel Bacry & Fabrizio Lillo, 2016. "The role of volume in order book dynamics: a multivariate Hawkes process analysis," Papers 1602.07663, arXiv.org.
    48. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    49. E. Bacry & J. F Muzy, 2013. "Hawkes model for price and trades high-frequency dynamics," Papers 1301.1135, arXiv.org.
    50. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2013. "Modelling systemic price cojumps with Hawkes factor models," Papers 1301.6141, arXiv.org, revised Mar 2013.
    51. Herrera, Rodrigo & Schipp, Bernhard, 2013. "Value at risk forecasts by extreme value models in a conditional duration framework," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 33-47.
    52. Dungey, Mardi & Henry, Olan & McKenzie, Michael, 2010. "From Trade-to-Trade in US Treasuries," Working Papers 10446, University of Tasmania, Tasmanian School of Business and Economics, revised 01 May 2010.
    53. Clements, A.E. & Herrera, R. & Hurn, A.S., 2015. "Modelling interregional links in electricity price spikes," Energy Economics, Elsevier, vol. 51(C), pages 383-393.
    54. Giada Adelfio & Arianna Agosto & Marcello Chiodi & Paolo Giudici, 2021. "Financial contagion through space-time point processes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 665-688, June.
    55. Angelos Dassios & Jiwook Jang & Hongbiao Zhao, 2019. "A Generalised CIR Process with Externally-Exciting and Self-Exciting Jumps and Its Applications in Insurance and Finance," Risks, MDPI, vol. 7(4), pages 1-18, October.
    56. Hainaut, Donatien, 2016. "Impact of volatility clustering on equity indexed annuities," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 367-381.
    57. Fan, Lina & Yang, Hao & Zhai, Jia & Zhang, Xiaotao, 2023. "Forecasting stock volatility during the stock market crash period: The role of Hawkes process," Finance Research Letters, Elsevier, vol. 55(PA).
    58. E. Bacry & S. Delattre & M. Hoffmann & J. F. Muzy, 2011. "Modeling microstructure noise with mutually exciting point processes," Papers 1101.3422, arXiv.org.
    59. D’Amico, Guglielmo & Petroni, Filippo, 2018. "Copula based multivariate semi-Markov models with applications in high-frequency finance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 765-777.
    60. Li, Jie & Li, Guangzhong & Zhou, Yinggang, 2015. "Do securitized real estate markets jump? International evidence," Pacific-Basin Finance Journal, Elsevier, vol. 31(C), pages 13-35.
    61. Lee, Kyungsub & Seo, Byoung Ki, 2017. "Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 154-183.
    62. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    63. Cavaliere, Giuseppe & Lu, Ye & Rahbek, Anders & Stærk-Østergaard, Jacob, 2023. "Bootstrap inference for Hawkes and general point processes," Journal of Econometrics, Elsevier, vol. 235(1), pages 133-165.
    64. Donatien Hainaut, 2016. "A model for interest rates with clustering effects," Post-Print hal-01393994, HAL.
    65. Hainaut, Donatien, 2020. "Fractional Hawkes processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    66. A. Saichev & D. Sornette, 2011. "Generating functions and stability study of multivariate self-excited epidemic processes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 83(2), pages 271-282, September.
    67. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    68. Jan Beran & Yuanhua Feng & Sucharita Ghosh, 2015. "Modelling long-range dependence and trends in duration series: an approach based on EFARIMA and ESEMIFAR models," Statistical Papers, Springer, vol. 56(2), pages 431-451, May.
    69. Monteiro, André A., 2009. "The econometrics of randomly spaced financial data: a survey," DES - Working Papers. Statistics and Econometrics. WS ws097924, Universidad Carlos III de Madrid. Departamento de Estadística.
    70. Adam E Clements & Yin Liao, 2013. "Modeling and forecasting realized volatility: getting the most out of the jump component," NCER Working Paper Series 93, National Centre for Econometric Research.
    71. Anatoliy Swishchuk, 2021. "Modelling of Limit Order Books by General Compound Hawkes Processes with Implementations," Methodology and Computing in Applied Probability, Springer, vol. 23(1), pages 399-428, March.
    72. Ban Zheng & Franc{c}ois Roueff & Fr'ed'eric Abergel, 2013. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Papers 1301.5007, arXiv.org, revised Feb 2014.
    73. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, September.
    74. V. Filimonov & D. Sornette, 2015. "Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1293-1314, August.
    75. Siakoulis, Vasilios, 2015. "Modeling bank default intensity in the USA using autoregressive duration models," MPRA Paper 64526, University Library of Munich, Germany.
    76. Hainaut, Donatien, 2016. "A bivariate Hawkes process for interest rate modeling," Economic Modelling, Elsevier, vol. 57(C), pages 180-196.
    77. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    78. Jiqian Wang & Feng Ma & M.I.M. Wahab & Dengshi Huang, 2021. "Forecasting China's Crude Oil Futures Volatility: The Role of the Jump, Jumps Intensity, and Leverage Effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 921-941, August.
    79. Emmanuel Bacry & Iacopo Mastromatteo & Jean-Franc{c}ois Muzy, 2015. "Hawkes processes in finance," Papers 1502.04592, arXiv.org, revised May 2015.
    80. Jang, Jiwook & Dassios, Angelos, 2013. "A bivariate shot noise self-exciting process for insurance," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 524-532.
    81. Liu, Chenguang, 2020. "Statistical inference for a partially observed interacting system of Hawkes processes," Stochastic Processes and their Applications, Elsevier, vol. 130(9), pages 5636-5694.
    82. Dalderop, Jeroen, 2020. "Nonparametric filtering of conditional state-price densities," Journal of Econometrics, Elsevier, vol. 214(2), pages 295-325.
    83. Jiwook Jang & Rosy Oh, 2020. "A Bivariate Compound Dynamic Contagion Process for Cyber Insurance," Papers 2007.04758, arXiv.org.
    84. Giuseppe Arbia & Michele Di Marcantonio, 2015. "Forecasting Interest Rates Using Geostatistical Techniques," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    85. Samuel N. Cohen & Robert J. Elliott, 2013. "Filters and smoothers for self-exciting Markov modulated counting processes," Papers 1311.6257, arXiv.org.
    86. Herrera, Rodrigo & Schipp, Bernhard, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers 2011-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    87. Maxime Morariu-Patrichi & Mikko Pakkanen, 2018. "State-dependent Hawkes processes and their application to limit order book modelling," CREATES Research Papers 2018-26, Department of Economics and Business Economics, Aarhus University.
    88. Qi Guo & Bruno Remillard & Anatoliy Swishchuk, 2020. "Multivariate General Compound Point Processes in Limit Order Books," Papers 2008.00124, arXiv.org.
    89. Roueff, François & von Sachs, Rainer & Sansonnet, Laure, 2016. "Locally stationary Hawkes processes," Stochastic Processes and their Applications, Elsevier, vol. 126(6), pages 1710-1743.
    90. Hainaut, Donatien, 2019. "Fractional Hawkes processes," LIDAM Discussion Papers ISBA 2019016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    91. Lucio Maria Calcagnile & Giacomo Bormetti & Michele Treccani & Stefano Marmi & Fabrizio Lillo, 2015. "Collective synchronization and high frequency systemic instabilities in financial markets," Papers 1505.00704, arXiv.org.
    92. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    93. Adam Clements & Yin Liao, 2013. "The dynamics of co-jumps, volatility and correlation," NCER Working Paper Series 91, National Centre for Econometric Research.
    94. Vladimir Filimonov & David Bicchetti & Nicolas Maystre, 2013. "Quantification of the High Level of Endogeneity and of Structural Regime Shifts in Commodity Markets," UNCTAD Discussion Papers 212, United Nations Conference on Trade and Development.

  62. Hautsch, Nikolaus, 2007. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," SFB 649 Discussion Papers 2007-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Ng, F.C. & Li, W.K. & Yu, Philip L.H., 2016. "Diagnostic checking of the vector multiplicative error model," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 86-97.
    3. Karanasos, Menelaos & Xu, Yongdeng & Yfanti, Stavroula, 2017. "Constrained QML Estimation for Multivariate Asymmetric MEM with Spillovers: The Practicality of Matrix Inequalities," Cardiff Economics Working Papers E2017/14, Cardiff University, Cardiff Business School, Economics Section.
    4. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 321-340, March.
    6. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    7. Vahidin Jeleskovic, 2024. "An Empirical Analysis of Scam Tokens on Ethereum Blockchain," Papers 2402.19399, arXiv.org, revised Mar 2024.
    8. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.
    9. Nikolaus Hautsch & Dieter Hess & David Veredas, 2010. "The impact of macroeconomic news on quote adjustments, noise and informational volatility," Working Papers ECARES 2010-004, ULB -- Universite Libre de Bruxelles.
    10. Cipollini, Fabrizio & Gallo, Giampiero M., 2025. "Multiplicative Error Models: 20 years on," Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
    11. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).
    12. Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Markus Engler & Vahidin Jeleskovic, 2016. "Intraday volatility, trading volume and trading intensity in the interbank market e-MID," MAGKS Papers on Economics 201648, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    14. Luintel, Kul B & Xu, Yongdeng, 2013. "Testing weak exogeneity in multiplicative error models," Cardiff Economics Working Papers E2013/6, Cardiff University, Cardiff Business School, Economics Section.
    15. David German & Henry Schellhorn, 2012. "A No-Arbitrage Model of Liquidity in Financial Markets involving Brownian Sheets," Papers 1206.4804, arXiv.org.
    16. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    17. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    18. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    19. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula–Based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics, MDPI, vol. 5(2), pages 1-24, April.
    20. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2009. "Quantifying high-frequency market reactions to real-time news sentiment announcements," SFB 649 Discussion Papers 2009-063, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    21. Arango, Ignacio & Agudelo, Diego A., 2019. "How does information disclosure affect liquidity? Evidence from an emerging market," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    22. Sergey Lototsky & Henry Schellhorn & Ran Zhao, 2016. "A String Model of Liquidity in Financial Markets," Papers 1608.05900, arXiv.org, revised Apr 2018.
    23. Brownlees Christian T. & Vannucci Marina, 2013. "A Bayesian approach for capturing daily heterogeneity in intra-daily durations time series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 21-46, February.
    24. Ke, Rui & Lu, Wanbo & Jia, Jing, 2021. "Evaluating multiplicative error models: A residual-based approach," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).

  63. Frank Gerhard & Nikolaus Hautsch, 2006. "A Dynamic Semiparametric Proportional Hazard Model," FRU Working Papers 2006/05, University of Copenhagen. Department of Economics. Finance Research Unit.

    Cited by:

    1. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    2. COSMA, Antonio & GALLI, Fausto, 2006. "A nonparametric ACD model," LIDAM Discussion Papers CORE 2006067, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  64. Nikolaus Hautsch, 2006. "Testing the Conditional Mean Function of Autoregressive Conditional Duration Models," FRU Working Papers 2006/06, University of Copenhagen. Department of Economics. Finance Research Unit.

    Cited by:

    1. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. BAUWENS, Luc & HAUTSCH, Nikolaus, 2003. "Dynamic latent factor models for intensity processes," LIDAM Discussion Papers CORE 2003103, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Indeewara Perera & Javier Hidalgo & Mervyn J. Silvapulle, 2016. "A Goodness-of-Fit Test for a Class of Autoregressive Conditional Duration Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1111-1141, June.
    4. Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
    5. Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Dungey, Mardi & Jeyasreedharan, Nagaratnam & Li, Tuo, 2010. "Modelling the Time Between Trades in the After-Hours Electronic Equity Futures Market," Working Papers 10451, University of Tasmania, Tasmanian School of Business and Economics, revised 30 May 2012.
    7. Dungey, Mardi & Henry, Olan & McKenzie, Michael, 2010. "From Trade-to-Trade in US Treasuries," Working Papers 10446, University of Tasmania, Tasmanian School of Business and Economics, revised 01 May 2010.
    8. Yongmiao Hong & Yoon-Jin Lee, 2007. "Detecting Misspecifications in Autoregressive Conditional Duration Models," CAEPR Working Papers 2007-019, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    9. Allen, David & Chan, Felix & McAleer, Michael & Peiris, Shelton, 2008. "Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks," Journal of Econometrics, Elsevier, vol. 147(1), pages 163-185, November.

  65. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Florian Heiss, 2008. "Sequential numerical integration in nonlinear state space models for microeconometric panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 373-389.
    2. Katarzyna Bień-Barkowska, 2014. "“Every move you make, every step you take, I’ll be watching you” – the quest for hidden orders in the interbank FX spot market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(3), pages 197-224.
    3. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    4. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    5. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
    7. Marco Minozzo & Silvia Centanni, 2012. "Monte Carlo likelihood inference for marked doubly stochastic Poisson processes with intensity driven by marked point processes," Working Papers 11/2012, University of Verona, Department of Economics.
    8. Wu, Zhengxiao, 2012. "On the intraday periodicity duration adjustment of high-frequency data," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 282-291.
    9. Deniz Erer, 2023. "The Impact of News Related Covid-19 on Exchange Rate Volatility:A New Evidence From Generalized Autoregressive Score Model," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(38), pages 105-126, June.
    10. Katarzyna Bień-Barkowska, 2014. "Capturing Order Book Dynamics in the Interbank EUR/PLN Spot Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 93-117, January.
    11. Nolte, Ingmar & Voev, Valeri, 2007. "Panel intensity models with latent factors: An application to the trading dynamics on the foreign exchange market," CoFE Discussion Papers 07/02, University of Konstanz, Center of Finance and Econometrics (CoFE).
    12. Herrera, Rodrigo, 2013. "Energy risk management through self-exciting marked point process," Energy Economics, Elsevier, vol. 38(C), pages 64-76.
    13. Szabolcs Blazsek & Alvaro Escribano, 2010. "Knowledge spillovers in U.S. patents: A dynamic patent intensity model with secret common innovation factors," Post-Print hal-00732533, HAL.
    14. Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 19 May 2021.
    15. Jean-Francois Richard, 2007. "Efficient High-Dimensional Importance Sampling," Working Paper 321, Department of Economics, University of Pittsburgh, revised Jan 2007.
    16. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society.
    17. Richard, Jean-Francois & Zhang, Wei, 2007. "Efficient high-dimensional importance sampling," Journal of Econometrics, Elsevier, vol. 141(2), pages 1385-1411, December.
    18. Aneta Hryckiewicz & Piotr Mielus & Karolina Skorulska & Malgorzata Snarska, 2018. "Does a bank levy increase frictions on the interbank market?," KAE Working Papers 2018-033, Warsaw School of Economics, Collegium of Economic Analysis.
    19. Lange, Rutger-Jan, 2024. "Bellman filtering and smoothing for state–space models," Journal of Econometrics, Elsevier, vol. 238(2).
    20. Kohler, Alexander & von Wyss, Rico, 2012. "Where does Information Processing in a Fragmented Market Take Place? – Evidence from the Swiss Stock Market after MiFID," Working Papers on Finance 1209, University of St. Gallen, School of Finance.
    21. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
    22. Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
    23. Zhicheng Li & Haipeng Xing, 2022. "High-Frequency Quote Volatility Measurement Using a Change-Point Intensity Model," Mathematics, MDPI, vol. 10(4), pages 1-24, February.
    24. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2011. "Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models," Tinbergen Institute Discussion Papers 11-057/4, Tinbergen Institute, revised 27 Jan 2012.
    25. André A. Monteiro, 2008. "Parameter Driven Multi-state Duration Models: Simulated vs. Approximate Maximum Likelihood Estimation," Tinbergen Institute Discussion Papers 08-021/2, Tinbergen Institute.
    26. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos & Touche, Nassim, 2019. "Integer-valued stochastic volatility," MPRA Paper 91962, University Library of Munich, Germany, revised 04 Feb 2019.
    27. Djennad, Abdelmajid & Rigby, Robert & Stasinopoulos, Dimitrios & Voudouris, Vlasios & Eilers, Paul, 2015. "Beyond location and dispersion models: The Generalized Structural Time Series Model with Applications," MPRA Paper 62807, University Library of Munich, Germany.
    28. Yogo Purwono & Irwan Adi Ekaputra & Zaäfri Ananto Husodo, 2018. "Estimation of Dynamic Mixed Hitting Time Model Using Characteristic Function Based Moments," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 295-321, February.
    29. Drew Creal & Siem Jan Koopman & André Lucas, 2008. "A General Framework for Observation Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 08-108/4, Tinbergen Institute.
    30. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
    31. Liesenfeld, Roman & Richard, Jean-François, 2008. "Improving MCMC, using efficient importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 272-288, December.
    32. Zhang, Xuan & Kim, Minjoo & Yan, Cheng & Zhao, Yang, 2024. "Default dependence in the insurance and banking sectors: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    33. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    34. Monteiro, André A., 2009. "The econometrics of randomly spaced financial data: a survey," DES - Working Papers. Statistics and Econometrics. WS ws097924, Universidad Carlos III de Madrid. Departamento de Estadística.
    35. Giampaoli, Iacopo & Ng, Wing Lon & Constantinou, Nick, 2009. "Analysis of ultra-high-frequency financial data using advanced Fourier transforms," Finance Research Letters, Elsevier, vol. 6(1), pages 47-53, March.
    36. Blazsek, Szabolcs, 2012. "Patents, secret innovations and firm's rate of return : differential effects of the innovation leader," UC3M Working papers. Economics we1202, Universidad Carlos III de Madrid. Departamento de Economía.
    37. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
    38. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society.
    39. Giuseppe Arbia & Michele Di Marcantonio, 2015. "Forecasting Interest Rates Using Geostatistical Techniques," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    40. Herrera, Rodrigo & Schipp, Bernhard, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers 2011-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    41. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54841, University Library of Munich, Germany.
    42. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Patent propensity, R&D and market competition: Dynamic spillovers of innovation leaders and followers," Journal of Econometrics, Elsevier, vol. 191(1), pages 145-163.
    43. Ouyang, Ruolan & Zhang, Xuan, 2020. "Financialization of agricultural commodities: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 381-389.
    44. Renault, Eric & van der Heijden, Thijs & Werker, Bas J.M., 2014. "The dynamic mixed hitting-time model for multiple transaction prices and times," Journal of Econometrics, Elsevier, vol. 180(2), pages 233-250.
    45. Kehrle, Kerstin & Peter, Franziska J., 2013. "Who moves first? An intensity-based measure for information flows across stock exchanges," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1629-1642.
    46. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2024. "Volatility models versus intensity models: analogy and differences," MPRA Paper 122528, University Library of Munich, Germany.
    47. Blazsek, Szabolcs, 2014. "Propensity to patent, R&D and market competition : dynamic spillovers of innovation leaders and followers," UC3M Working papers. Economics we1412, Universidad Carlos III de Madrid. Departamento de Economía.

  66. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Modelling financial high frequency data using point processes," LIDAM Discussion Papers CORE 2006080, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Maxime Morariu-Patrichi & Mikko S. Pakkanen, 2018. "State-dependent Hawkes processes and their application to limit order book modelling," Papers 1809.08060, arXiv.org, revised Sep 2021.
    2. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
    3. Bacry, E. & Delattre, S. & Hoffmann, M. & Muzy, J.F., 2013. "Some limit theorems for Hawkes processes and application to financial statistics," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2475-2499.
    4. Qi Guo & Bruno Remillard & Anatoliy Swishchuk, 2020. "Multivariate General Compound Point Processes in Limit Order Books," Risks, MDPI, vol. 8(3), pages 1-20, September.
    5. Pietro Fodra & Huy^en Pham, 2013. "High frequency trading and asymptotics for small risk aversion in a Markov renewal model," Papers 1310.1756, arXiv.org, revised Jan 2015.
    6. Roueff, Francois & von Sachs, Rainer & Sansonnet, Laure, 2015. "Time-frequency analysis of locally stationary Hawkes processes," LIDAM Discussion Papers ISBA 2015011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Zhang, Yaohua & Zou, Jian & Ravishanker, Nalini & Thavaneswaran, Aerambamoorthy, 2019. "Modeling financial durations using penalized estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 145-158.
    8. Alessio Sancetta, 2017. "Estimation for the Prediction of Point Processes with Many Covariates," Papers 1702.05315, arXiv.org.
    9. Brendan P.M. McCabe & Gael Martin & Keith Freeland, 2010. "A Quasi-locally Most powerful Test for Correlation in the conditional Variance of Positive Data," Monash Econometrics and Business Statistics Working Papers 2/10, Monash University, Department of Econometrics and Business Statistics.
    10. Vasileios Siakoulis & Ioannis Venetis, 2015. "On inter-arrival times of bond market extreme events. An application to seven European markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(4), pages 717-741, October.
    11. Emmanuel Bacry & Jean-Francois Muzy, 2014. "Second order statistics characterization of Hawkes processes and non-parametric estimation," Papers 1401.0903, arXiv.org, revised Feb 2015.
    12. Katarzyna Bień-Barkowska, 2014. "Capturing Order Book Dynamics in the Interbank EUR/PLN Spot Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 93-117, January.
    13. Kyungsub Lee, 2022. "Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures," Papers 2207.05939, arXiv.org, revised Sep 2024.
    14. Angelos Dassios & Xin Dong, 2014. "Stationarity of Bivariate Dynamic Contagion Processes," Papers 1405.5842, arXiv.org.
    15. Monira Essa Aloud, 2016. "Time Series Analysis Indicators under Directional Changes: The Case of Saudi Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 55-64.
    16. Ketelbuters, John John & Hainaut, Donatien, 2021. "Time-Consistent Evaluation of Credit Risk with Contagion," LIDAM Discussion Papers ISBA 2021004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    17. Gurgul Henryk & Machno Artur, 2017. "Trade Pattern on Warsaw Stock Exchange and Prediction of Number of Trades," Statistics in Transition New Series, Statistics Poland, vol. 18(1), pages 91-114, March.
    18. Alexander Saichev & Thomas Maillart & Didier Sornette, 2013. "Hierarchy of temporal responses of multivariate self-excited epidemic processes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(4), pages 1-19, April.
    19. Marcello Rambaldi & Vladimir Filimonov & Fabrizio Lillo, 2016. "Detection of intensity bursts using Hawkes processes: an application to high frequency financial data," Papers 1610.05383, arXiv.org.
    20. Anatoliy Swishchuk & Aiden Huffman, 2020. "General Compound Hawkes Processes in Limit Order Books," Risks, MDPI, vol. 8(1), pages 1-25, March.
    21. Hamza Bodor & Laurent Carlier, 2024. "A Novel Approach to Queue-Reactive Models: The Importance of Order Sizes," Papers 2405.18594, arXiv.org.
    22. Ban Zheng & François Roueff & Frédéric Abergel, 2014. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Post-Print hal-00777941, HAL.
    23. Steffen Volkenand & Günther Filler & Martin Odening, 2020. "Price Discovery and Market Reflexivity in Agricultural Futures Contracts with Different Maturities," Risks, MDPI, vol. 8(3), pages 1-17, July.
    24. Álvaro Cartea, 2013. "Derivatives pricing with marked point processes using tick-by-tick data," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 111-123, January.
    25. Aman Ullah & Mardi Dungey & Xiangdong Long & Yun Wang, 2014. "A Semiparametric Conditional Duration Model," Working Papers 201408, University of California at Riverside, Department of Economics.
    26. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    27. Donatien Hainaut, 2016. "A bivariate Hawkes process based model, for interest rates," Post-Print hal-01458162, HAL.
    28. Zhu, Lingjiong, 2013. "Moderate deviations for Hawkes processes," Statistics & Probability Letters, Elsevier, vol. 83(3), pages 885-890.
    29. Ioane Muni Toke, 2011. ""Market making" behaviour in an order book model and its impact on the bid-ask spread," Post-Print hal-01705266, HAL.
    30. Chavez-Demoulin, V. & McGill, J.A., 2012. "High-frequency financial data modeling using Hawkes processes," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3415-3426.
    31. Anatoliy Swishchuk & Aiden Huffman, 2018. "General Compound Hawkes Processes in Limit Order Books," Papers 1812.02298, arXiv.org.
    32. Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
    33. Zhicheng Li & Haipeng Xing, 2022. "High-Frequency Quote Volatility Measurement Using a Change-Point Intensity Model," Mathematics, MDPI, vol. 10(4), pages 1-24, February.
    34. Dassios, Angelos & Jang, Jiwook & Zhao, Hongbiao, 2019. "A generalised CIR process with externally-exciting and self-exciting jumps and its applications in insurance and finance," LSE Research Online Documents on Economics 102043, London School of Economics and Political Science, LSE Library.
    35. Denisa Georgiana Banulescu & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2013. "High-Frequency Risk Measures," Working Papers halshs-00859456, HAL.
    36. Pietro Fodra & Huyen Pham, 2013. "High frequency trading in a Markov renewal model," Working Papers hal-00867113, HAL.
    37. E. Bacry & K. Dayri & J. F. Muzy, 2011. "Non-parametric kernel estimation for symmetric Hawkes processes. Application to high frequency financial data," Papers 1112.1838, arXiv.org.
    38. Wang, Haixu, 2022. "Limit theorems for a discrete-time marked Hawkes process," Statistics & Probability Letters, Elsevier, vol. 184(C).
    39. Ioane Muni Toke, 2010. ""Market making" behaviour in an order book model and its impact on the bid-ask spread," Papers 1003.3796, arXiv.org, revised Jun 2010.
    40. Ye, Wuyi & Xia, Wenjing & Wu, Bin & Chen, Pengzhan, 2022. "Using implied volatility jumps for realized volatility forecasting: Evidence from the Chinese market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    41. Volodymyr Korniichuk, 2012. "Forecasting extreme electricity spot prices," Cologne Graduate School Working Paper Series 03-14, Cologne Graduate School in Management, Economics and Social Sciences.
    42. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2015. "Modelling systemic price cojumps with Hawkes factor models," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1137-1156, July.
    43. Anatoliy Swishchuk, 2017. "General Compound Hawkes Processes in Limit Order Books," Papers 1706.07459, arXiv.org, revised Jun 2017.
    44. Wei Sun & Svetlozar Rachev & Frank Fabozzi & Petko Kalev, 2008. "Fractals in trade duration: capturing long-range dependence and heavy tailedness in modeling trade duration," Annals of Finance, Springer, vol. 4(2), pages 217-241, March.
    45. Wheatley, Spencer & Filimonov, Vladimir & Sornette, Didier, 2016. "The Hawkes process with renewal immigration & its estimation with an EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 120-135.
    46. Anatoliy Swishchuk & Bruno Remillard & Robert Elliott & Jonathan Chavez-Casillas, 2017. "Compound Hawkes Processes in Limit Order Books," Papers 1712.03106, arXiv.org.
    47. Marcello Rambaldi & Emmanuel Bacry & Fabrizio Lillo, 2016. "The role of volume in order book dynamics: a multivariate Hawkes process analysis," Papers 1602.07663, arXiv.org.
    48. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    49. E. Bacry & J. F Muzy, 2013. "Hawkes model for price and trades high-frequency dynamics," Papers 1301.1135, arXiv.org.
    50. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2013. "Modelling systemic price cojumps with Hawkes factor models," Papers 1301.6141, arXiv.org, revised Mar 2013.
    51. Herrera, Rodrigo & Schipp, Bernhard, 2013. "Value at risk forecasts by extreme value models in a conditional duration framework," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 33-47.
    52. Dungey, Mardi & Henry, Olan & McKenzie, Michael, 2010. "From Trade-to-Trade in US Treasuries," Working Papers 10446, University of Tasmania, Tasmanian School of Business and Economics, revised 01 May 2010.
    53. Clements, A.E. & Herrera, R. & Hurn, A.S., 2015. "Modelling interregional links in electricity price spikes," Energy Economics, Elsevier, vol. 51(C), pages 383-393.
    54. Giada Adelfio & Arianna Agosto & Marcello Chiodi & Paolo Giudici, 2021. "Financial contagion through space-time point processes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 665-688, June.
    55. Angelos Dassios & Jiwook Jang & Hongbiao Zhao, 2019. "A Generalised CIR Process with Externally-Exciting and Self-Exciting Jumps and Its Applications in Insurance and Finance," Risks, MDPI, vol. 7(4), pages 1-18, October.
    56. Hainaut, Donatien, 2016. "Impact of volatility clustering on equity indexed annuities," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 367-381.
    57. Fan, Lina & Yang, Hao & Zhai, Jia & Zhang, Xiaotao, 2023. "Forecasting stock volatility during the stock market crash period: The role of Hawkes process," Finance Research Letters, Elsevier, vol. 55(PA).
    58. E. Bacry & S. Delattre & M. Hoffmann & J. F. Muzy, 2011. "Modeling microstructure noise with mutually exciting point processes," Papers 1101.3422, arXiv.org.
    59. D’Amico, Guglielmo & Petroni, Filippo, 2018. "Copula based multivariate semi-Markov models with applications in high-frequency finance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 765-777.
    60. Li, Jie & Li, Guangzhong & Zhou, Yinggang, 2015. "Do securitized real estate markets jump? International evidence," Pacific-Basin Finance Journal, Elsevier, vol. 31(C), pages 13-35.
    61. Lee, Kyungsub & Seo, Byoung Ki, 2017. "Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 154-183.
    62. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    63. Cavaliere, Giuseppe & Lu, Ye & Rahbek, Anders & Stærk-Østergaard, Jacob, 2023. "Bootstrap inference for Hawkes and general point processes," Journal of Econometrics, Elsevier, vol. 235(1), pages 133-165.
    64. Donatien Hainaut, 2016. "A model for interest rates with clustering effects," Post-Print hal-01393994, HAL.
    65. Hainaut, Donatien, 2020. "Fractional Hawkes processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    66. A. Saichev & D. Sornette, 2011. "Generating functions and stability study of multivariate self-excited epidemic processes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 83(2), pages 271-282, September.
    67. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    68. Jan Beran & Yuanhua Feng & Sucharita Ghosh, 2015. "Modelling long-range dependence and trends in duration series: an approach based on EFARIMA and ESEMIFAR models," Statistical Papers, Springer, vol. 56(2), pages 431-451, May.
    69. Monteiro, André A., 2009. "The econometrics of randomly spaced financial data: a survey," DES - Working Papers. Statistics and Econometrics. WS ws097924, Universidad Carlos III de Madrid. Departamento de Estadística.
    70. Adam E Clements & Yin Liao, 2013. "Modeling and forecasting realized volatility: getting the most out of the jump component," NCER Working Paper Series 93, National Centre for Econometric Research.
    71. Anatoliy Swishchuk, 2021. "Modelling of Limit Order Books by General Compound Hawkes Processes with Implementations," Methodology and Computing in Applied Probability, Springer, vol. 23(1), pages 399-428, March.
    72. Ban Zheng & Franc{c}ois Roueff & Fr'ed'eric Abergel, 2013. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Papers 1301.5007, arXiv.org, revised Feb 2014.
    73. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, September.
    74. V. Filimonov & D. Sornette, 2015. "Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1293-1314, August.
    75. Siakoulis, Vasilios, 2015. "Modeling bank default intensity in the USA using autoregressive duration models," MPRA Paper 64526, University Library of Munich, Germany.
    76. Hainaut, Donatien, 2016. "A bivariate Hawkes process for interest rate modeling," Economic Modelling, Elsevier, vol. 57(C), pages 180-196.
    77. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    78. Jiqian Wang & Feng Ma & M.I.M. Wahab & Dengshi Huang, 2021. "Forecasting China's Crude Oil Futures Volatility: The Role of the Jump, Jumps Intensity, and Leverage Effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 921-941, August.
    79. Emmanuel Bacry & Iacopo Mastromatteo & Jean-Franc{c}ois Muzy, 2015. "Hawkes processes in finance," Papers 1502.04592, arXiv.org, revised May 2015.
    80. Jang, Jiwook & Dassios, Angelos, 2013. "A bivariate shot noise self-exciting process for insurance," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 524-532.
    81. Liu, Chenguang, 2020. "Statistical inference for a partially observed interacting system of Hawkes processes," Stochastic Processes and their Applications, Elsevier, vol. 130(9), pages 5636-5694.
    82. Dalderop, Jeroen, 2020. "Nonparametric filtering of conditional state-price densities," Journal of Econometrics, Elsevier, vol. 214(2), pages 295-325.
    83. Jiwook Jang & Rosy Oh, 2020. "A Bivariate Compound Dynamic Contagion Process for Cyber Insurance," Papers 2007.04758, arXiv.org.
    84. Giuseppe Arbia & Michele Di Marcantonio, 2015. "Forecasting Interest Rates Using Geostatistical Techniques," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    85. Samuel N. Cohen & Robert J. Elliott, 2013. "Filters and smoothers for self-exciting Markov modulated counting processes," Papers 1311.6257, arXiv.org.
    86. Herrera, Rodrigo & Schipp, Bernhard, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers 2011-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    87. Maxime Morariu-Patrichi & Mikko Pakkanen, 2018. "State-dependent Hawkes processes and their application to limit order book modelling," CREATES Research Papers 2018-26, Department of Economics and Business Economics, Aarhus University.
    88. Qi Guo & Bruno Remillard & Anatoliy Swishchuk, 2020. "Multivariate General Compound Point Processes in Limit Order Books," Papers 2008.00124, arXiv.org.
    89. Roueff, François & von Sachs, Rainer & Sansonnet, Laure, 2016. "Locally stationary Hawkes processes," Stochastic Processes and their Applications, Elsevier, vol. 126(6), pages 1710-1743.
    90. Hainaut, Donatien, 2019. "Fractional Hawkes processes," LIDAM Discussion Papers ISBA 2019016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    91. Lucio Maria Calcagnile & Giacomo Bormetti & Michele Treccani & Stefano Marmi & Fabrizio Lillo, 2015. "Collective synchronization and high frequency systemic instabilities in financial markets," Papers 1505.00704, arXiv.org.
    92. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    93. Adam Clements & Yin Liao, 2013. "The dynamics of co-jumps, volatility and correlation," NCER Working Paper Series 91, National Centre for Econometric Research.
    94. Vladimir Filimonov & David Bicchetti & Nicolas Maystre, 2013. "Quantification of the High Level of Endogeneity and of Structural Regime Shifts in Commodity Markets," UNCTAD Discussion Papers 212, United Nations Conference on Trade and Development.

  67. Nikolaus Hautsch, 2005. "The latent factor VAR model: Testing for a common component in the intraday trading process," FRU Working Papers 2005/03, University of Copenhagen. Department of Economics. Finance Research Unit.

    Cited by:

    1. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  68. Nikolaus Hautsch & Dieter Hess, 2004. "Bayesian Learning in Financial Markets: Testing for the Relevance of Information Precision in Price Discovery," Discussion Papers 04-17, University of Copenhagen. Department of Economics.

    Cited by:

    1. Markku Lanne, 2009. "Properties of Market-Based and Survey Macroeconomic Forecasts for Different Data Releases," Economics Bulletin, AccessEcon, vol. 29(3), pages 2231-2240.
    2. Carlos Madeira & João Madeira, 2019. "The Effect of FOMC Votes on Financial Markets," The Review of Economics and Statistics, MIT Press, vol. 101(5), pages 921-932, December.
    3. Maryam Ahmadi & Niaz Bashiri Behmiri & Matteo Manera, 2020. "The theory of storage in the crude oil futures market, the role of financial conditions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1160-1175, July.
    4. Menkhoff, Lukas & Schmeling, Maik, 2010. "Whose trades convey information? Evidence from a cross-section of traders," Journal of Financial Markets, Elsevier, vol. 13(1), pages 101-128, February.
    5. Nikolaus Hautsch & Dieter Hess & Christoph Müller, 2008. "Price Adjustment to News with Uncertain Precision," FRU Working Papers 2008/01, University of Copenhagen. Department of Economics. Finance Research Unit.
    6. Gilbert, Thomas, 2011. "Information aggregation around macroeconomic announcements: Revisions matter," Journal of Financial Economics, Elsevier, vol. 101(1), pages 114-131, July.
    7. Thomas Gilbert & Chiara Scotti & Georg Strasser & Clara Vega, 2015. "Is the Intrinsic Value of Macroeconomic News Announcements Related to their Asset Price Impact?," Finance and Economics Discussion Series 2015-46, Board of Governors of the Federal Reserve System (U.S.).
    8. Isengildina-Massa, Olga & Irwin, Scott H. & Good, Darrel L., 2010. "Quantile Regression Estimates of Confidence Intervals for WASDE Price Forecasts," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 35(3), pages 1-23, December.
    9. Withanawasam, R.M. & Whigham, P.A. & Crack, T.F., 2013. "Characterising trader manipulation in a limit-order driven market," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 43-52.
    10. Marcello Pericoli & Giovanni Veronese, 2015. "Forecaster heterogeneity, surprises and financial markets," Temi di discussione (Economic working papers) 1020, Bank of Italy, Economic Research and International Relations Area.
    11. Grothe, Magdalena, 2010. "Price and trading response to public information," Working Paper Series 1177, European Central Bank.
    12. Nikolaus Hautsch & Dieter Hess & David Veredas, 2010. "The impact of macroeconomic news on quote adjustments, noise and informational volatility," Working Papers ECARES 2010-004, ULB -- Universite Libre de Bruxelles.
    13. Niessen-Ruenzi, Alexandra, 2007. "Media coverage and macroeconomic information processing," SFB 649 Discussion Papers 2007-011, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Hess, Dieter & Niessen, Alexandra, 2007. "The early news catches the attention: On the relative price impact of similar economic indicators," CFR Working Papers 07-03, University of Cologne, Centre for Financial Research (CFR).
    15. Peter Tillmann, 2020. "Macroeconomic Surprises and the Demand for Information about Monetary Policy," MAGKS Papers on Economics 202007, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    16. Laivi Laidroo & Zana Grigaliuniene, 2012. "Testing for asymmetries in price reactions to quarterly earnings announcements on Tallinn, Riga and Vilnius Stock Exchanges during 2000-2009," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 12(1), pages 61-86, July.
    17. Peter Tillmann, 2023. "Macroeconomic Surprises and the Demand for Information about Monetary Policy," International Journal of Central Banking, International Journal of Central Banking, vol. 19(2), pages 351-388, June.
    18. Tsionas, Mike G., 2023. "Bayesian learning in performance. Is there any?," European Journal of Operational Research, Elsevier, vol. 311(1), pages 263-282.
    19. Tillmann, Peter, 2020. "Macroeconomic Surprises and the Demand for Information about Monetary Policy," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224545, Verein für Socialpolitik / German Economic Association.
    20. A. A. Brown & L. C. G. Rogers, 2009. "Heterogeneous Beliefs with Finite-Lived Agents," Papers 0907.4953, arXiv.org.
    21. Park, Cyn-Young & Mercado, Rogelio & Choi, Jaehun & Lim, Hosung, 2015. "Price Discovery and Foreign Participation in the Republic of Korea’s Government Bond Cash and Futures Markets," ADB Economics Working Paper Series 427, Asian Development Bank.
    22. Huotari, Jarkko, 2015. "Measuring financial stress – A country specific stress index for Finland," Bank of Finland Research Discussion Papers 7/2015, Bank of Finland.
    23. Fricke, Christoph & Menkhoff, Lukas, 2010. "Does the "Bund" dominate price discovery in Euro bond futures? Examining information shares," Hannover Economic Papers (HEP) dp-449, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    24. Linda S. Goldberg & Christian Grisse, 2013. "Time variation in asset price responses to macro announcements," Working Papers 2013-11, Swiss National Bank.
    25. Laakkonen, Helinä & Lanne, Markku, 2009. "The Relevance of Accuracy for the Impact of Macroeconomic News on Volatility," MPRA Paper 23718, University Library of Munich, Germany.
    26. Cedric Mbanga & Ali F. Darrat & Jung Chul Park, 2019. "Investor sentiment and aggregate stock returns: the role of investor attention," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 397-428, August.
    27. Pervaiz Alam & Xiaoling Pu & Barry Hettler & Hai Lin, 2020. "The pricing of accruals quality in credit default swap spreads," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(3), pages 1943-1977, September.
    28. Hess, Dieter & Orbe, Sebastian, 2011. "Irrationality or efficiency of macroeconomic survey forecasts? Implications from the anchoring bias test," CFR Working Papers 11-13, University of Cologne, Centre for Financial Research (CFR).

  69. Anthony D. Hall & Nikolaus Hautsch, 2004. "Order Aggressiveness and Order Book Dynamics," FRU Working Papers 2005/04, University of Copenhagen. Department of Economics. Finance Research Unit.

    Cited by:

    1. Katarzyna Bień-Barkowska, 2014. "“Every move you make, every step you take, I’ll be watching you” – the quest for hidden orders in the interbank FX spot market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(3), pages 197-224.
    2. Ellul, Andrew & Holden, Craig W. & Jain, Pankaj & Jennings, Robert, 2007. "Order dynamics: Recent evidence from the NYSE," Journal of Empirical Finance, Elsevier, vol. 14(5), pages 636-661, December.
    3. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Duong, Huu Nhan & Kalev, Petko S., 2013. "Anonymity and order submissions," Pacific-Basin Finance Journal, Elsevier, vol. 25(C), pages 101-118.
    5. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
    6. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical distributions of Chinese stock returns at different microscopic timescales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 495-502.
    7. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Cebiroglu, Gökhan & Hautsch, Nikolaus & Horst, Ulrich, 2014. "Order exposure and liquidity coordination: Does hidden liquidity harm price efficiency?," CFS Working Paper Series 468, Center for Financial Studies (CFS).
    9. Yamamoto, Ryuichi, 2014. "An empirical analysis of non-execution and picking-off risks on the Tokyo Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 369-383.
    10. Katarzyna Bień-Barkowska, 2014. "Capturing Order Book Dynamics in the Interbank EUR/PLN Spot Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 93-117, January.
    11. Ryuichi Yamamoto, 2015. "Dynamic predictor selection and order splitting in a limit order market," Working Papers 1514, Waseda University, Faculty of Political Science and Economics.
    12. Song Song & Wolfgang K. Härdle & Ya'acov Ritov, 2014. "Generalized dynamic semi‐parametric factor models for high‐dimensional non‐stationary time series," Econometrics Journal, Royal Economic Society, vol. 17(2), pages 101-131, June.
    13. Alexis Stenfors & Masayuki Susai, 2017. "Liquidity Withdrawal in the FX Spot Market: A Cross-Country Study Using High-Frequency Data," Working Papers in Economics & Finance 2017-06, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    14. Hamza Bodor & Laurent Carlier, 2024. "A Novel Approach to Queue-Reactive Models: The Importance of Order Sizes," Papers 2405.18594, arXiv.org.
    15. Herrera, Rodrigo & González, Sergio & Clements, Adam, 2018. "Mutual excitation between OECD stock and oil markets: A conditional intensity extreme value approach," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 70-88.
    16. Valenzuela, Marcela & Zer, Ilknur, 2013. "Competition, signaling and non-walking through the book: Effects on order choice," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5421-5435.
    17. Kohler, Alexander & von Wyss, Rico, 2012. "Where does Information Processing in a Fragmented Market Take Place? – Evidence from the Swiss Stock Market after MiFID," Working Papers on Finance 1209, University of St. Gallen, School of Finance.
    18. Anh Tu Le & Thai-Ha Le & Wai-Man Liu & Kingsley Y. Fong, 2021. "Dynamic limit order placement strategies: survival analysis with a multiple-spell duration model," Annals of Operations Research, Springer, vol. 297(1), pages 241-275, February.
    19. Grammig, Joachim G. & Theissen, Erik & Wünsche, Oliver, 2011. "Time and the price impact of a trade: A structural approach," CFS Working Paper Series 2011/08, Center for Financial Studies (CFS).
    20. Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    21. Wei Cui & Anthony Brabazon & Michael O'Neill, 2011. "Dynamic trade execution: a grammatical evolution approach," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 2(1/2), pages 4-31.
    22. Duong, Huu Nhan & Kalev, Petko S. & Krishnamurti, Chandrasekhar, 2009. "Order aggressiveness of institutional and individual investors," Pacific-Basin Finance Journal, Elsevier, vol. 17(5), pages 533-546, November.
    23. Charles Cao & Oliver Hansch & Xiaoxin Wang, 2008. "Order Placement Strategies In A Pure Limit Order Book Market," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 31(2), pages 113-140, June.
    24. Adam Clements & Joanne Fuller & Vasilios Papalexiou, 2015. "Public news flow in intraday component models for trading activity and volatility," NCER Working Paper Series 106, National Centre for Econometric Research.
    25. Adam Ponzi & Fabrizio Lillo & Rosario N. Mantegna, 2006. "Market reaction to temporary liquidity crises and the permanent market impact," Papers physics/0608032, arXiv.org.
    26. Katarzyna Bień-Barkowska, 2011. "Multistate asymmetric ACD model: an application to order dynamics in the EUR/PLN spot market," NBP Working Papers 104, Narodowy Bank Polski.
    27. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    28. Johannes Prix & Otto Loistl & Michael Huetl, 2007. "Algorithmic Trading Patterns in Xetra Orders," The European Journal of Finance, Taylor & Francis Journals, vol. 13(8), pages 717-739.
    29. Yamamoto, Ryuichi, 2011. "Order aggressiveness, pre-trade transparency, and long memory in an order-driven market," Journal of Economic Dynamics and Control, Elsevier, vol. 35(11), pages 1938-1963.
    30. Z. Sun & P. A. Hamill & Y. Li & Y. C. Yang & S. A. Vigne, 2019. "Did long-memory of liquidity signal the European sovereign debt crisis?," Annals of Operations Research, Springer, vol. 282(1), pages 355-377, November.
    31. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
    32. Chou, Robin K. & Wang, Yun-Yi, 2011. "A test of the different implications of the overconfidence and disposition hypotheses," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 2037-2046, August.
    33. Lien, Donald & Hung, Pi-Hsia & Lo, Hsiang-Yu, 2022. "Order Choices: An Intraday Analysis of the Taiwan Stock Exchange," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    34. Comerton-Forde, Carole & Tang, Kar Mei, 2009. "Anonymity, liquidity and fragmentation," Journal of Financial Markets, Elsevier, vol. 12(3), pages 337-367, August.
    35. Smales, Lee A., 2016. "Order aggressiveness of different broker-types in response to monetary policy news," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 367-383.
    36. Yamamoto, Ryuichi, 2020. "Limit order submission risks, order choice, and tick size," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
    37. Hall, Anthony D. & Hautsch, Nikolaus, 2007. "Modelling the buy and sell intensity in a limit order book market," Journal of Financial Markets, Elsevier, vol. 10(3), pages 249-286, August.
    38. Giampaoli, Iacopo & Ng, Wing Lon & Constantinou, Nick, 2009. "Analysis of ultra-high-frequency financial data using advanced Fourier transforms," Finance Research Letters, Elsevier, vol. 6(1), pages 47-53, March.
    39. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2013. "Limit order books," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1709-1742, November.
    40. Hautsch, Nikolaus & Huang, Ruihong, 2012. "On the dark side of the market: Identifying and analyzing hidden order placements," SFB 649 Discussion Papers 2012-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    41. Ingrid Lo & Stephen Sapp, 2011. "Belief Dispersion and Order Submission Strategies in the Foreign Exchange Market," Staff Working Papers 11-8, Bank of Canada.
    42. Lo, Ingrid & Sapp, Stephen G., 2010. "Order aggressiveness and quantity: How are they determined in a limit order market?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(3), pages 213-237, July.
    43. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    44. Ming-Chang Wang & Lon-Ping Zu & Chau-Jung Kuo, 2010. "Risk aversion, order strategy and price formation," Applied Economics, Taylor & Francis Journals, vol. 42(5), pages 627-640.
    45. Alexis Stenfors & Masayuki Susai, 2017. "Algorithmic Trading Behaviour and High-Frequency Liquidity Withdrawal in the FX Spot Market," Working Papers in Economics & Finance 2017-04, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    46. Sperl, Miriam, 2008. "Quantifying the efficiency of the Xetra LOB market: Detailed recipe," CFS Working Paper Series 2008/21, Center for Financial Studies (CFS).
    47. Song, Song & Härdle, Wolfgang Karl & Ritov, Ya'acov, 2010. "High dimensional nonstationary time series modelling with generalized dynamic semiparametric factor model," SFB 649 Discussion Papers 2010-039, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    48. Wing Lon Ng, 2010. "Dynamic Order Submission And Herding Behavior In Electronic Trading," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(1), pages 27-43, March.
    49. Kehrle, Kerstin & Peter, Franziska J., 2013. "Who moves first? An intensity-based measure for information flows across stock exchanges," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1629-1642.
    50. Cumhur Ekinci, 2005. "Limit Order Book Reconstruction And Beyond: An Application To Istanbul Stock Exchange," Finance 0510025, University Library of Munich, Germany, revised 24 Oct 2005.

  70. Anthony D. Hall & Nikolaus Hautsch, 2004. "A Continuous-Time Measurement of the Buy-Sell Pressure in a Limit Order Book Market," Discussion Papers 04-07, University of Copenhagen. Department of Economics.

    Cited by:

    1. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    2. Anthony D. Hall & Nikolaus Hautsch, 2004. "Order Aggressiveness and Order Book Dynamics," FRU Working Papers 2005/04, University of Copenhagen. Department of Economics. Finance Research Unit.
    3. Asani Sarkar & Robert A. Schwartz, 2007. "Market sidedness: insights into motives for trade initiation," Staff Reports 292, Federal Reserve Bank of New York.
    4. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Asani Sarkar & Robert A. Schwartz, 2006. "Two-sided markets and intertemporal trade clustering: insights into trading motives," Staff Reports 246, Federal Reserve Bank of New York.
    6. Andrea Consiglio & Valerio Lacagnina & Annalisa Russino, 2005. "A simulation analysis of the microstructure of an order driven financial market with multiple securities and portfolio choices," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 71-87.
    7. Charles Cao & Oliver Hansch & Xiaoxin Wang, 2008. "Order Placement Strategies In A Pure Limit Order Book Market," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 31(2), pages 113-140, June.
    8. Wing Lon Ng, 2010. "Dynamic Order Submission And Herding Behavior In Electronic Trading," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(1), pages 27-43, March.
    9. Voev, Valeri, 2006. "A trade-by-trade surprise measure and its relation to observed spreads on the NYSE," CoFE Discussion Papers 06/03, University of Konstanz, Center of Finance and Econometrics (CoFE).

  71. BAUWENS, Luc & HAUTSCH, Nikolaus, 2003. "Dynamic latent factor models for intensity processes," LIDAM Discussion Papers CORE 2003103, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Siem Jan Koopman & André Lucas & André Monteiro, 2005. "The Multi-State Latent Factor Intensity Model for Credit Rating Transitions," Tinbergen Institute Discussion Papers 05-071/4, Tinbergen Institute, revised 04 Jul 2005.
    2. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    3. Anthony D. Hall & Nikolaus Hautsch, 2004. "Order Aggressiveness and Order Book Dynamics," FRU Working Papers 2005/04, University of Copenhagen. Department of Economics. Finance Research Unit.
    4. Omar Euch & Masaaki Fukasawa & Mathieu Rosenbaum, 2018. "The microstructural foundations of leverage effect and rough volatility," Finance and Stochastics, Springer, vol. 22(2), pages 241-280, April.
    5. Liesenfeld, Roman & Richard, Jean-François, 2004. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Economics Working Papers 2004-12, Christian-Albrechts-University of Kiel, Department of Economics.
    6. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Simonsen, Ola, 2005. "An Empirical Model for Durations in Stocks," Umeå Economic Studies 657, Umeå University, Department of Economics.
    8. Ban Zheng & François Roueff & Frédéric Abergel, 2014. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Post-Print hal-00777941, HAL.
    9. GRAMMIG, Joachim & HEINEN, Andréas & RENGIFO, Erick, 2004. "Trading activity and liquidity supply in a pure limit order book market," LIDAM Discussion Papers CORE 2004058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Gilles Zumbach, 2015. "Cross-sectional universalities in financial time series," Quantitative Finance, Taylor & Francis Journals, vol. 15(12), pages 1901-1912, December.
    11. Large, Jeremy, 2007. "Measuring the resiliency of an electronic limit order book," Journal of Financial Markets, Elsevier, vol. 10(1), pages 1-25, February.
    12. Liesenfeld, Roman & Richard, Jean-François, 2008. "Improving MCMC, using efficient importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 272-288, December.
    13. Jean-Francois Richard & Roman Liesenfeld, 2007. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Working Paper 322, Department of Economics, University of Pittsburgh, revised Jan 2004.
    14. Ban Zheng & Franc{c}ois Roueff & Fr'ed'eric Abergel, 2013. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Papers 1301.5007, arXiv.org, revised Feb 2014.
    15. Grammig, Joachin & Heinen, Andreas & Rengifo, Erick, 2004. "Trading activity and liquidity supply in a pure limit order book market: An empirical analysis using a multivariate count data model," MPRA Paper 8115, University Library of Munich, Germany.

  72. Hautsch, Nikolaus & Hess, Dieter, 2002. "The processing of non-anticipated information in financial markets: Analyzing the impact of surprises in the employment report," CoFE Discussion Papers 02/06, University of Konstanz, Center of Finance and Econometrics (CoFE).

    Cited by:

    1. Entorf, Horst & Steiner, Christian, 2006. "Makroökonomische Nachrichten und die Reaktion des 15-Sekunden-DAX: Eine Ereignisstudie zur Wirkung der ZEW-Konjunkturprognose," ZEW Discussion Papers 06-008, ZEW - Leibniz Centre for European Economic Research.
    2. Nikolaus Hautsch & Dieter Hess & Christoph Müller, 2008. "Price Adjustment to News with Uncertain Precision," FRU Working Papers 2008/01, University of Copenhagen. Department of Economics. Finance Research Unit.
    3. Gropp, Reint E. & Kadareja, Arjan, 2007. "Stale information, shocks and volatility," ZEW Discussion Papers 07-012, ZEW - Leibniz Centre for European Economic Research.
    4. Coffinet Jèrôme & Gouteron Sylvain, 2010. "Euro-Area Yield Curve Reaction to Monetary News," German Economic Review, De Gruyter, vol. 11(2), pages 208-224, May.
    5. Grothe, Magdalena, 2010. "Price and trading response to public information," Working Paper Series 1177, European Central Bank.
    6. Ferdinand Graf, 2011. "Mechanically Extracted Company Signals and their Impact on Stock and Credit Markets," Working Paper Series of the Department of Economics, University of Konstanz 2011-18, Department of Economics, University of Konstanz.
    7. Nikolaus Hautsch & Dieter Hess & David Veredas, 2010. "The impact of macroeconomic news on quote adjustments, noise and informational volatility," Working Papers ECARES 2010-004, ULB -- Universite Libre de Bruxelles.
    8. Mondria, Jordi & Wang, Xin & Wu, Thomas, 2021. "Familiarity and Surprises in International Financial Markets: Bad news travels like wildfire; good news travels slow," Journal of International Money and Finance, Elsevier, vol. 115(C).
    9. Sylwia Nowak, 2008. "How Do Public Announcements Affect The Frequency Of Trading In U.S. Airline Stocks?," CAMA Working Papers 2008-38, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Chiou-Wei, Song-Zan & Linn, Scott C. & Zhu, Zhen, 2014. "The response of U.S. natural gas futures and spot prices to storage change surprises: Fundamental information and the effect of escalating physical gas production," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 156-173.
    11. Cecilia Frale & David Veredas, 2008. "A Monthly Volatility Index for the US Economy," Working Papers ECARES 2008-008, ULB -- Universite Libre de Bruxelles.
    12. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2009. "Quantifying high-frequency market reactions to real-time news sentiment announcements," SFB 649 Discussion Papers 2009-063, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Jordi Mondria & Thomas Wu, 2012. "Familiarity and Surprises in International Financial Markets: Bad news travels like wildfire, good news travels slow," 2012 Meeting Papers 50, Society for Economic Dynamics.
    14. Nikolaus Hautsch & Dieter Hess, 2004. "Bayesian Learning in Financial Markets – Testing for the Relevance of Information Precision in Price Discovery," FRU Working Papers 2004/06, University of Copenhagen. Department of Economics. Finance Research Unit.
    15. Steiner, Christian & Groß, Anne & Entorf, Horst, 2009. "Return and Volatility Reactions to Monthly Announcements of Business Cycle Forecasts: An Event Study Based on High-Frequency Data," ZEW Discussion Papers 09-010, ZEW - Leibniz Centre for European Economic Research.
    16. Entorf Horst & Steiner Christian, 2007. "Makroökonomische Nachrichten und die Reaktion des 15-Sekunden-DAX: Eine Ereignisstudie zur Wirkung der ZEW-Konjunkturprognose / Announcement of Business Cycle Forecasts and the Reaction of the German ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 227(1), pages 3-26, February.
    17. Neeraj J. Gupta & Vitaliy Strohush & Reilly White, 2019. "Investor reaction to simultaneous news releases: unemployment vs. earnings," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(4), pages 735-749, October.
    18. Chiou-Wei, Song-Zan & Chen, Sheng-Hung & Zhu, Zhen, 2020. "Natural gas price, market fundamentals and hedging effectiveness," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 321-337.

  73. Hautsch, Nikolaus, 2002. "Modelling Intraday Trading Activity Using Box-Cox-ACD Models," CoFE Discussion Papers 02/05, University of Konstanz, Center of Finance and Econometrics (CoFE).

    Cited by:

    1. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 125, Paderborn University, CIE Center for International Economics.
    2. Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
    3. Roman Huptas, 2016. "The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 1-20, March.
    4. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 122, Paderborn University, CIE Center for International Economics.
    5. Roman Huptas, 2014. "Bayesian Estimation and Prediction for ACD Models in the Analysis of Trade Durations from the Polish Stock Market," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(4), pages 237-273, December.
    6. Wing Lon Ng, 2010. "Dynamic Order Submission And Herding Behavior In Electronic Trading," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(1), pages 27-43, March.

  74. Hautsch, Nikolaus & Hess, Dieter E., 2001. "A mean variance king? Creation and resolution of uncertainty under the employment report's reign," ZEW Discussion Papers 01-60, ZEW - Leibniz Centre for European Economic Research.

    Cited by:

    1. Savaser, Tanseli, 2011. "Exchange rate response to macronews: Through the lens of microstructure," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 107-126, February.
    2. Tanseli Savaser, 2007. "Exchange Rate Response to Macro News: Through the Lens of Microstructure," Department of Economics Working Papers 2007-02, Department of Economics, Williams College.

  75. Hautsch, Nikolaus & Klotz, Stefan, 2001. "Estimating the Neighborhood Influence on Decision Makers: Theory and an Application on the Analysis of Innovation Decisions," CoFE Discussion Papers 01/04, University of Konstanz, Center of Finance and Econometrics (CoFE).

    Cited by:

    1. Fedorets, Alexandra & Stops, Michael & Lottmann, Franziska, 2017. "Job matching on connected regional and occupational labor markets," IAB-Discussion Paper 201735, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Johannes Rincke, 2006. "Policy innovation in local jurisdictions: Testing for neighborhood influence in school choice policies," Public Choice, Springer, vol. 129(1), pages 189-200, October.
    3. Konno, Tomohiko & Ioannides, Yannis M., 2019. "The exact solution of spatial logit response games," Mathematical Social Sciences, Elsevier, vol. 97(C), pages 1-10.
    4. Johannes Rincke, 2005. "Policy Innovation in Local Jurisdictions: Testing the Neighborhood Influence Against the Free-Riding Hypothesis," Public Economics 0511009, University Library of Munich, Germany.
    5. Edoardo Di Porto & Federico Revelli, 2009. "Central command, local hazard and the race to the top," Working Papers 2009/26, Institut d'Economia de Barcelona (IEB).
    6. Elzbieta Antczak & Ewa Galecka-Burdziak & Robert Pater, 2016. "Spatial labour market matching," KAE Working Papers 2016-009, Warsaw School of Economics, Collegium of Economic Analysis.
    7. Johannes Rincke, 2005. "Policy Innovation in Local Jurisdictions: Testing the Neighborhood Influence Against the Free-Riding Hypothesis," Public Economics 0511017, University Library of Munich, Germany.
    8. Kihiu, Evelyne Nyathira, 2016. "Basic capability effect: Collective management of pastoral resources in southwestern Kenya," Ecological Economics, Elsevier, vol. 123(C), pages 23-34.
    9. Rincke, Johannes, 2005. "Neighborhood Influence and Political Change: Evidence from US School Districts," ZEW Discussion Papers 05-16, ZEW - Leibniz Centre for European Economic Research.
    10. Johannes Rincke, 2005. "Neighborhood Influence and Political Change: Evidence from US School Districts," Public Economics 0511011, University Library of Munich, Germany.
    11. Schaffer, Axel & Düvelmeyer, Claudia, 2016. "Regional drivers of on-farm energy production in Bavaria," Energy Policy, Elsevier, vol. 95(C), pages 361-369.
    12. Zhu, Fengxia & Zou, Shaoming & Xu, Hui, 2017. "Launching reverse-innovated product from emerging markets to MNC’s home market: A theoretical framework for MNC’s decisions," International Business Review, Elsevier, vol. 26(1), pages 156-163.
    13. Buettner, Thiess & von Schwerin, Axel, 2016. "Yardstick competition and partial coordination: Exploring the empirical distribution of local business tax rates," Journal of Economic Behavior & Organization, Elsevier, vol. 124(C), pages 178-201.
    14. Rincke, Johannes, 2005. "Policy Innovation in Local Jurisdictions: Testing the Neighborhood Influence Against the Free-Riding Hypothesis," ZEW Discussion Papers 05-08, ZEW - Leibniz Centre for European Economic Research.

  76. Hautsch, Nikolaus & Lehmann, Erik & Warning, Susanne & Frick, Bernd, 2001. "Shirking or mismatch? Coach-team separation in German professional soccer," Discussion Papers, Series I 313, University of Konstanz, Department of Economics.

    Cited by:

    1. Bernd Frick, 2007. "The Football Players' Labor Market: Empirical Evidence From The Major European Leagues," Scottish Journal of Political Economy, Scottish Economic Society, vol. 54(3), pages 422-446, July.
    2. B Frick & R Simmons, 2005. "The impact of managerial quality on organizational performance: evidence from German soccer," Working Papers 566927, Lancaster University Management School, Economics Department.
    3. Claudio Lucifora & Rob Simmons, 2003. "Superstar Effects in Sport," Journal of Sports Economics, , vol. 4(1), pages 35-55, February.

  77. Gerhard, Frank & Hautsch, Nikolaus, 2000. "Determinants of Inter-Trade Durations and Hazard Rates Using Proportional Hazard ARMA Model," CoFE Discussion Papers 00/20, University of Konstanz, Center of Finance and Econometrics (CoFE).

    Cited by:

    1. Iordanis Kalaitzoglou & Boulis Maher Ibrahim, 2010. "Does Order Flow in the European Carbon Allowances Market Reveal Information?," CFI Discussion Papers 1003, Centre for Finance and Investment, Heriot Watt University.
    2. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.
    3. Kalaitzoglou, Iordanis & Ibrahim, Boulis M., 2013. "Does order flow in the European Carbon Futures Market reveal information?," Journal of Financial Markets, Elsevier, vol. 16(3), pages 604-635.

  78. Frank Gerhard & Nikolaus Hautsch, 2000. "Determinants of Inter-Trade Durations Using Proportional Hazard ARMA Models," Econometric Society World Congress 2000 Contributed Papers 1082, Econometric Society.

    Cited by:

    1. Iordanis Kalaitzoglou & Boulis Maher Ibrahim, 2010. "Does Order Flow in the European Carbon Allowances Market Reveal Information?," CFI Discussion Papers 1003, Centre for Finance and Investment, Heriot Watt University.
    2. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.
    3. Kalaitzoglou, Iordanis & Ibrahim, Boulis M., 2013. "Does order flow in the European Carbon Futures Market reveal information?," Journal of Financial Markets, Elsevier, vol. 16(3), pages 604-635.

  79. Nikolaus Hautsch, 1999. "Analyzing the Time between Trades with a Gamma Compounded Hazard Model. An Application to LIFFE Bund Future Transactions," Finance 9904002, University Library of Munich, Germany.

    Cited by:

    1. Bidisha Chakrabarty & Zhaohui Han & Konstantin Tyurin & Xiaoyong Zheng, 2006. "A Competing Risk Analysis of Executions and Cancellations in a Limit Order Market," CAEPR Working Papers 2006-015, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    2. Gerhard, Frank & Hautsch, Nikolaus, 1999. "Volatility Estimation on the Basis of Price Intensities," CoFE Discussion Papers 99/19, University of Konstanz, Center of Finance and Econometrics (CoFE).
    3. Hautsch, Nikolaus, 2002. "Modelling Intraday Trading Activity Using Box-Cox-ACD Models," CoFE Discussion Papers 02/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
    4. Gerhard, Frank & Hautsch, Nikolaus, 2000. "Determinants of Inter-Trade Durations and Hazard Rates Using Proportional Hazard ARMA Model," CoFE Discussion Papers 00/20, University of Konstanz, Center of Finance and Econometrics (CoFE).
    5. Patrick Gagliardini & Christian Gourieroux, 2002. "Duration Time Series Models with Proportional Hazard," Working Papers 2002-21, Center for Research in Economics and Statistics.

  80. Gerhard, Frank & Hautsch, Nikolaus, 1999. "Volatility Estimation on the Basis of Price Intensities," CoFE Discussion Papers 99/19, University of Konstanz, Center of Finance and Econometrics (CoFE).

    Cited by:

    1. Veredas, David & Rodríguez Poo, Juan M., 2001. "On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach," DES - Working Papers. Statistics and Econometrics. WS ws013321, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Maillet, Bertrand & Michel, Thierry, 2002. "How deep was the September 2001 stock market crisis?: putting recent events on the American and French markets into perspective with an index of market shocks," LSE Research Online Documents on Economics 24936, London School of Economics and Political Science, LSE Library.
    4. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Giot, Pierre & Laurent, Sebastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
    6. Skander Slim & Ibrahim Tabche & Yosra Koubaa & Mohamed Osman & Andreas Karathanasopoulos, 2023. "Forecasting realized volatility of Bitcoin: The informative role of price duration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1909-1929, November.
    7. Chen, Kim Heng & Jandhyala, Venkata K. & Fotopoulos, Stergios B., 2005. "Nonlinear Properties of Multifactor Financial Models," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 1(2), pages 1-27.
    8. Vinicius Ratton Brandi, 2020. "Short-Term Predictability of Stock Market Indexes following Large Drawdowns and Drawups," Working Papers Series 529, Central Bank of Brazil, Research Department.
    9. Zhicheng Li & Haipeng Xing, 2022. "High-Frequency Quote Volatility Measurement Using a Change-Point Intensity Model," Mathematics, MDPI, vol. 10(4), pages 1-24, February.
    10. Denisa Georgiana Banulescu & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2013. "High-Frequency Risk Measures," Working Papers halshs-00859456, HAL.
    11. Fotopoulos, Stergios B. & Jandhyala, Venkata K. & Chen, Kim-Heng, 2007. "Non-linear properties of conditional returns under scale mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3041-3056, March.
    12. Fei Wang & Wei Chao, 2018. "A New Perspective on Improving Hospital Energy Administration Based on Recurrence Interval Analysis," Energies, MDPI, vol. 11(5), pages 1-18, May.
    13. Song, Shijia & Li, Handong, 2023. "Is a co-jump in prices a sparse jump?," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    14. Thierry Chauveau & Sylvain Friederich & Jérôme Héricourt & Emmanuel Jurczenko & Catherine Lubochinsky & Bertrand Maillet & Christophe Moussu & Bogdan Négréa & Hélène Raymond Feingold, 2004. "La volatilité des marchés augmente-elle ?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00308982, HAL.
    15. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, September.

  81. Frank Gerhard & Nikolaus Hautsch, "undated". "Semiparametric autoregressive conditional proportional hazard models," Economics Papers 2002-W2, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Monteiro, André A., 2009. "The econometrics of randomly spaced financial data: a survey," DES - Working Papers. Statistics and Econometrics. WS ws097924, Universidad Carlos III de Madrid. Departamento de Estadística.

Articles

  1. Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad‐Díaz & Menachem (Meni) Abudy , 2024. "Nonstandard Errors," Journal of Finance, American Finance Association, vol. 79(3), pages 2339-2390, June.
    • Utz Weitzel & Michael Razen & Sebastian Neussüs & Michael Kirchler & Magnus Johannesson & Juergen Huber & Felix Holzmeister & Anna Dreber & Albert J. Menkveld & Javier Gil-Bazo, 2021. "Non-Standard Errors," Working Papers 1303, Barcelona School of Economics.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," IWH Discussion Papers 11/2021, Halle Institute for Economic Research (IWH).
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian T. Brownlees & Javier Gil-Baz, 2021. "Non-standard errors," Economics Working Papers 1807, Department of Economics and Business, Universitat Pompeu Fabra.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Mena, 2021. "Non-Standard Errors," Working Papers 2021:17, Lund University, Department of Economics.
    • Albert J. et al. Menkveld, 2021. "Non-Standard Errors," CESifo Working Paper Series 9453, CESifo.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Post-Print halshs-03500882, HAL.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Edwin Baidoo & Michael Frömmel & et al, 2021. "Non-Standard Errors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1032, Ghent University, Faculty of Economics and Business Administration.
    • Francesco Franzoni & Roxana Mihet & Markus Leippold & Per Ostberg & Olivier Scaillet & Norman Schürhoff & Oksana Bashchenko & Nicola Mano & Michele Pelli, 2022. "Non-Standard Errors," Swiss Finance Institute Research Paper Series 22-09, Swiss Finance Institute.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Cambridge Working Papers in Economics 2182, Faculty of Economics, University of Cambridge.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Hasse, Jean-Baptiste & e.a.,, 2023. "Non-Standard Errors," LIDAM Reprints LFIN 2023002, Université catholique de Louvain, Louvain Finance (LFIN).
    • Moinas, Sophie & Declerck, Fany & Menkveld, Albert J. & Dreber, Anna, 2023. "Non-Standard Errors," TSE Working Papers 23-1451, Toulouse School of Economics (TSE).
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüß, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Menac, 2024. "Nonstandard errors," LSE Research Online Documents on Economics 123002, London School of Economics and Political Science, LSE Library.
    • Albert Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad-Díaz & Tobias Adrian & Yacine Ai, 2024. "Nonstandard Errors," Post-Print hal-04676112, HAL.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," SAFE Working Paper Series 327, Leibniz Institute for Financial Research SAFE.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Dí­az & Menachem Abudy & Tobi, 2021. "Non-Standard Errors," Working Papers 2021-31, Faculty of Economics and Statistics, Universität Innsbruck.
    • Ferrara, Gerardo & Jurkatis, Simon, 2021. "Non-standard errors," Bank of England working papers 955, Bank of England.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03500882, HAL.
    • Ciril Bosch-Rosa & Bernhard Kassner, 2023. "Non-Standard Errors," Rationality and Competition Discussion Paper Series 385, CRC TRR 190 Rationality and Competition.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Janeway Institute Working Papers 2112, Faculty of Economics, University of Cambridge.
    • Wolff, Christian & Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüess, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-Standard Errors," CEPR Discussion Papers 16751, C.E.P.R. Discussion Papers.
    • Albert J. Menkveld & Anna Dreber & Félix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard, 2021. "Non-Standard Errors," Documents de travail du Centre d'Economie de la Sorbonne 21033, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    See citations under working paper version above.
  2. Nikolaus Hautsch & Christoph Scheu & Stefan Voigt, 2024. "Building trust takes time: limits to arbitrage for blockchain-based assets," Review of Finance, European Finance Association, vol. 28(4), pages 1345-1381.
    See citations under working paper version above.
  3. Nikolaus Hautsch & Ostap Okhrin & Alexander Ristig, 2023. "Maximum-Likelihood Estimation Using the Zig-Zag Algorithm," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1346-1375.

    Cited by:

    1. Gianluca Cubadda, 2024. "VAR models with an index structure: A survey with new results," Papers 2412.11278, arXiv.org.

  4. Andersen, Torben G. & Archakov, Ilya & Cebiroglu, Gökhan & Hautsch, Nikolaus, 2022. "Local mispricing and microstructural noise: A parametric perspective," Journal of Econometrics, Elsevier, vol. 230(2), pages 510-534.

    Cited by:

    1. Gustavo Fruet Dias & Karsten Schweiker, 2024. "Integrated Variance Estimation for Assets Traded in Multiple Venues," University of East Anglia School of Economics Working Paper Series 2024-04, School of Economics, University of East Anglia, Norwich, UK..
    2. Queiroz, R.G.S. & Kristoufek, L. & David, S.A., 2024. "A combined framework to explore cryptocurrency volatility and dependence using multivariate GARCH and Copula modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 652(C).
    3. Markus Bibinger & Nikolaus Hautsch & Alexander Ristig, 2024. "Jump detection in high-frequency order prices," Papers 2403.00819, arXiv.org.

  5. Torben Andersen & Ilya Archakov & Leon Grund & Nikolaus Hautsch & Yifan Li & Sergey Nasekin & Ingmar Nolte & Manh Cuong Pham & Stephen Taylor & Viktor Todorov, 2021. "A Descriptive Study of High-Frequency Trade and Quote Option Data [Stealth Trading in Options Markets]," Journal of Financial Econometrics, Oxford University Press, vol. 19(1), pages 128-177.

    Cited by:

    1. Matthias Fengler & Winfried Koeniger & Stephan Minger, 2024. "The Transmission of Monetary Policy to the Cost of Hedging," CESifo Working Paper Series 11556, CESifo.
    2. Amir Ahmad Dar & Mohammad Shahfaraz Khan & Imran Azad & Amit Kumar Pathak & Gopu Jayaraman, 2024. "Literature review: options and its applications," SN Business & Economics, Springer, vol. 4(8), pages 1-26, August.
    3. Li, Yifan & Nolte, Ingmar & Pham, Manh Cuong, 2024. "Parametric risk-neutral density estimation via finite lognormal-Weibull mixtures," Journal of Econometrics, Elsevier, vol. 241(2).
    4. Fengler, Matthias & Koeniger, Winfried & Minger, Stephan, 2025. "The Transmission of Monetary Policy to the Cost of Hedging," Economics Working Paper Series 2501, University of St. Gallen, School of Economics and Political Science.
    5. Kanne, Stefan & Korn, Olaf & Uhrig-Homburg, Marliese, 2023. "Stock illiquidity and option returns," Journal of Financial Markets, Elsevier, vol. 63(C).
    6. Fengler, Matthias & Koeniger, Winfried & Minger, Stephan, 2024. "The transmission of monetary policy to the cost of hedging," CFS Working Paper Series 726, Center for Financial Studies (CFS).

  6. Nikolaus Hautsch & Rodrigo Herrera, 2020. "Multivariate dynamic intensity peaks‐over‐threshold models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 248-272, March.
    See citations under working paper version above.
  7. Markus Bibinger & Nikolaus Hautsch & Peter Malec & Markus Reiss, 2019. "Estimating the Spot Covariation of Asset Prices—Statistical Theory and Empirical Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 419-435, July.
    See citations under working paper version above.
  8. Hautsch, Nikolaus & Horvath, Akos, 2019. "How effective are trading pauses?," Journal of Financial Economics, Elsevier, vol. 131(2), pages 378-403.
    See citations under working paper version above.
  9. Hautsch, Nikolaus & Voigt, Stefan, 2019. "Large-scale portfolio allocation under transaction costs and model uncertainty," Journal of Econometrics, Elsevier, vol. 212(1), pages 221-240.
    See citations under working paper version above.
  10. Betz, Frank & Hautsch, Nikolaus & Peltonen, Tuomas A. & Schienle, Melanie, 2016. "Systemic risk spillovers in the European banking and sovereign network," Journal of Financial Stability, Elsevier, vol. 25(C), pages 206-224.
    See citations under working paper version above.
  11. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.

    Cited by:

    1. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Michael Curran & Patrick O'Sullivan & Ryan Zalla, 2020. "Can Volatility Solve the Naive Portfolio Puzzle?," Papers 2005.03204, arXiv.org, revised Feb 2022.
    3. Cipollini, Fabrizio & Gallo, Giampiero M., 2025. "Multiplicative Error Models: 20 years on," Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
    4. Nikolaus Hautsch & Ostap Okhrin & Alexander Ristig, 2023. "Maximum-Likelihood Estimation Using the Zig-Zag Algorithm," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1346-1375.
    5. Gu, Huaying & Liu, Zhixue & Weng, Yingliang, 2017. "Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 460-472.
    6. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula–Based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics, MDPI, vol. 5(2), pages 1-24, April.

  12. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    See citations under working paper version above.
  13. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2015. "Do High‐Frequency Data Improve High‐Dimensional Portfolio Allocations?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 263-290, March.
    See citations under working paper version above.
  14. Wolfgang K. Härdle & Nikolaus Hautsch & Andrija Mihoci, 2015. "Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 529-550, June.
    See citations under working paper version above.
  15. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2014. "Forecasting systemic impact in financial networks," International Journal of Forecasting, Elsevier, vol. 30(3), pages 781-794.
    See citations under working paper version above.
  16. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    See citations under working paper version above.
  17. Axel Groß‐KlußMann & Nikolaus Hautsch, 2013. "Predicting Bid–Ask Spreads Using Long‐Memory Autoregressive Conditional Poisson Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(8), pages 724-742, December.
    See citations under working paper version above.
  18. Nikolaus Hautsch & Mark Podolskij, 2013. "Preaveraging-Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 165-183, April.
    See citations under working paper version above.
  19. Hautsch, Nikolaus & Hess, Dieter & Müller, Christoph, 2012. "Price adjustment to news with uncertain precision," Journal of International Money and Finance, Elsevier, vol. 31(2), pages 337-355.
    See citations under working paper version above.
  20. Nikolaus Hautsch & Lada M. Kyj & Roel C. A. Oomen, 2012. "A blocking and regularization approach to high‐dimensional realized covariance estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(4), pages 625-645, June.
    See citations under working paper version above.
  21. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
    See citations under working paper version above.
  22. Hautsch, Nikolaus & Ou, Yangguoyi, 2012. "Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 2988-3007.
    See citations under working paper version above.
  23. Hautsch, Nikolaus & Yang, Fuyu, 2012. "Bayesian inference in a Stochastic Volatility Nelson–Siegel model," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3774-3792.
    See citations under working paper version above.
  24. Hautsch, Nikolaus & Huang, Ruihong, 2012. "The market impact of a limit order," Journal of Economic Dynamics and Control, Elsevier, vol. 36(4), pages 501-522.
    See citations under working paper version above.
  25. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 321-340, March.

    Cited by:

    1. Adam Clements & Neda Todorova, 2014. "The impact of information flow and trading activity on gold and oil futures volatility," NCER Working Paper Series 102, National Centre for Econometric Research.
    2. Bastian von Beschwitz & Donald B Keim & Massimo Massa, 2020. "First to “Read” the News: News Analytics and Algorithmic Trading," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(1), pages 122-178.
    3. Allen, D.E. & McAleer, M.J. & Singh, A.K., 2015. "Daily Market News Sentiment and Stock Prices," Econometric Institute Research Papers EI2015-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Yen-Ju Hsu & Yang-Cheng Lu & J. Jimmy Yang, 2021. "News sentiment and stock market volatility," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 1093-1122, October.
    5. Junni L. Zhang & Wolfgang Karl Hardle & Cathy Y. Chen & Elisabeth Bommes, 2020. "Distillation of News Flow into Analysis of Stock Reactions," Papers 2009.10392, arXiv.org.
    6. Carlini, Federico & Farina, Vincenzo & Gufler, Ivan & Previtali, Daniele, 2024. "Do stress and overstatement in the news affect the stock market? Evidence from COVID-19 news in The Wall Street Journal," International Review of Financial Analysis, Elsevier, vol. 93(C).
    7. Fabrizio Lillo & Salvatore Miccich`e & Michele Tumminello & Jyrki Piilo & Rosario Nunzio Mantegna, 2012. "How news affect the trading behavior of different categories of investors in a financial market," Papers 1207.3300, arXiv.org.
    8. Ignacio Arango & Diego A. Agudelo, 2017. "How does information disclosure affect liquidity?Evidence from an Emerging Market," Documentos de Trabajo de Valor Público 16990, Universidad EAFIT.
    9. Chinmoy Ghosh & Cristian Pinto‐Gutiérrez & Jaideep Shenoy, 2024. "Does negative news disclosure induce better decision‐making? Evidence from acquisitions," The Financial Review, Eastern Finance Association, vol. 59(2), pages 325-372, May.
    10. Li, Cong-Cong & Xu, Hai-Chuan & Zhou, Wei-Xing, 2020. "News coverage and portfolio returns: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    11. Maslyuk-Escobedo, Svetlana & Rotaru, Kristian & Dokumentov, Alexander, 2017. "News sentiment and jumps in energy spot and futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 186-210.
    12. Ballinari, Daniele & Audrino, Francesco & Sigrist, Fabio, 2022. "When does attention matter? The effect of investor attention on stock market volatility around news releases," International Review of Financial Analysis, Elsevier, vol. 82(C).
    13. D Aromi & A Clements, 2018. "Media attention and crude oil volatility: Is there any 'new' news in the newspaper?," NCER Working Paper Series 118, National Centre for Econometric Research.
    14. Ammann, Manuel & Frey, Roman & Verhofen, Michael, 2012. "Do Newspaper Articles Predict Aggregate Stock Returns?," Working Papers on Finance 1204, University of St. Gallen, School of Finance.
    15. Jacob Boudoukh & Ronen Feldman & Shimon Kogan & Matthew Richardson, 2013. "Which News Moves Stock Prices? A Textual Analysis," NBER Working Papers 18725, National Bureau of Economic Research, Inc.
    16. Weng, Futian & Zhang, Hongwei & Yang, Cai, 2021. "Volatility forecasting of crude oil futures based on a genetic algorithm regularization online extreme learning machine with a forgetting factor: The role of news during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 73(C).
    17. Füss, Roland & Grabellus, Markus & Mager, Ferdinand & Stein, Michael, 2018. "Something in the air: Information density, news surprises, and price jumps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 50-75.
    18. Kohonen, Anssi, 2012. "On detection of volatility spillovers in simultaneously open stock markets," MPRA Paper 37504, University Library of Munich, Germany.
    19. Akihiro Omura & Neda Todorova, 2019. "The quantile dependence of commodity futures markets on news sentiment," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 818-837, July.
    20. Rognone, Lavinia & Hyde, Stuart & Zhang, S. Sarah, 2020. "News sentiment in the cryptocurrency market: An empirical comparison with Forex," International Review of Financial Analysis, Elsevier, vol. 69(C).
    21. Wei, Yu-Chen & Lu, Yang-Cheng & Chen, Jen-Nan & Hsu, Yen-Ju, 2017. "Informativeness of the market news sentiment in the Taiwan stock market," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 158-181.
    22. David E. Allen & Michael McAleer & Abhay K. Singh, 2016. "An entropy based analysis of the relationship between the DOW JONES Index and the TRNA Sentiment series," Documentos de Trabajo del ICAE 2017-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    23. Gabriele Ranco & Ilaria Bordino & Giacomo Bormetti & Guido Caldarelli & Fabrizio Lillo & Michele Treccani, 2014. "Coupling news sentiment with web browsing data improves prediction of intra-day price dynamics," Papers 1412.3948, arXiv.org, revised Dec 2015.
    24. Gabriele Ranco & Ilaria Bordino & Giacomo Bormetti & Guido Caldarelli & Fabrizio Lillo & Michele Treccani, 2016. "Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-14, January.
    25. Marcelo Bianconi & Xiaxin Hua & Chih Ming Tan, 2013. "Determinants of Systemic Risk and Information Dissemination," Working Paper series 67_13, Rimini Centre for Economic Analysis.
    26. Robert F. Engle & Martin Klint Hansen & Asger Lunde, 2012. "And Now, The Rest of the News: Volatility and Firm Specific News Arrival," CREATES Research Papers 2012-56, Department of Economics and Business Economics, Aarhus University.
    27. Jianfei Zhang & Mathieu Rosenbaum, 2023. "Towards systematic intraday news screening: a liquidity-focused approach," Papers 2304.05115, arXiv.org.
    28. Monika Bolek & Cezary Bolek, 2024. "Covid-19 Data Manipulation and Reaction of Stock Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(1), pages 137-164, March.
    29. Apergis, Nicholas, 2015. "Forecasting Credit Default Swaps (CDSs) spreads with newswire messages: Evidence from European countries under financial distress," Economics Letters, Elsevier, vol. 136(C), pages 92-94.
    30. Ferdinand Graf, 2011. "Mechanically Extracted Company Signals and their Impact on Stock and Credit Markets," Working Paper Series of the Department of Economics, University of Konstanz 2011-18, Department of Economics, University of Konstanz.
    31. Stefan Feuerriegel & Helmut Prendinger, 2018. "News-based trading strategies," Papers 1807.06824, arXiv.org.
    32. Anese, Gianluca & Corazza, Marco & Costola, Michele & Pelizzon, Loriana, 2021. "Impact of public news sentiment on stock market index return and volatility," SAFE Working Paper Series 322, Leibniz Institute for Financial Research SAFE.
    33. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    34. Adam Clements & Yin Liao, "undated". "News and network structures in equity market volatility," NCER Working Paper Series 110, National Centre for Econometric Research.
    35. Yuna Hao & Behrang Vand & Benjamin Manrique Delgado & Simone Baldi, 2023. "Market Manipulation in Stock and Power Markets: A Study of Indicator-Based Monitoring and Regulatory Challenges," Energies, MDPI, vol. 16(4), pages 1-28, February.
    36. Lee A. Smales, 2016. "Time-varying relationship of news sentiment, implied volatility and stock returns," Applied Economics, Taylor & Francis Journals, vol. 48(51), pages 4942-4960, November.
    37. Adam E. Clements & Neda Todorova, 2016. "Information Flow, Trading Activity and Commodity Futures Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(1), pages 88-104, January.
    38. Haroon, Omair & Rizvi, Syed Aun R., 2020. "COVID-19: Media coverage and financial markets behavior—A sectoral inquiry," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    39. Fengler, Matthias & Polivka, Jeannine, 2021. "Proxy-identification of a structural MGARCH model for asset returns," Economics Working Paper Series 2103, University of St. Gallen, School of Economics and Political Science, revised Oct 2024.
    40. Smales, Lee A., 2014. "News sentiment and the investor fear gauge," Finance Research Letters, Elsevier, vol. 11(2), pages 122-130.
    41. Ersan, Oguz & Simsir, Serif Aziz & Simsek, Koray D. & Hasan, Afan, 2021. "The speed of stock price adjustment to corporate announcements: Insights from Turkey," Emerging Markets Review, Elsevier, vol. 47(C).
    42. Gillam, Robert A. & Guerard, John B. & Cahan, Rochester, 2015. "News volume information: Beyond earnings forecasting in a global stock selection model," International Journal of Forecasting, Elsevier, vol. 31(2), pages 575-581.
    43. Khurshid Ahmad & JingGuang Han & Elaine Hutson & Colm Kearney & Sha Liu, 2016. "Media-expressed negative tone and firm-level stock returns," Open Access publications 10197/8208, Research Repository, University College Dublin.
    44. Adam Clements & Joanne Fuller & Vasilios Papalexiou, 2015. "Public news flow in intraday component models for trading activity and volatility," NCER Working Paper Series 106, National Centre for Econometric Research.
    45. Tom Marty & Bruce Vanstone & Tobias Hahn, 2020. "News media analytics in finance: a survey," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(2), pages 1385-1434, June.
    46. Fengler, Matthias & Polivka, Jeanine, 2022. "Identifying Structural Shocks to Volatility through a Proxy-MGARCH Model," VfS Annual Conference 2022 (Basel): Big Data in Economics 264010, Verein für Socialpolitik / German Economic Association.
    47. Rui Fan & Oleksandr Talavera & Vu Tran, 2020. "Social media bots and stock markets," European Financial Management, European Financial Management Association, vol. 26(3), pages 753-777, June.
    48. David E. Allen & Michael McAleer & Abhay K. Singh, 2014. "Machine news and volatility: The Dow Jones Industrial Average and the TRNA sentiment series," Working Papers in Economics 14/04, University of Canterbury, Department of Economics and Finance.
    49. Liu, Jun & Wu, Kai & Zhou, Ming, 2023. "News tone, investor sentiment, and liquidity premium," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 167-181.
    50. Zhu (Drew) Zhang & Jie Yuan & Amulya Gupta, 2024. "Let the Laser Beam Connect the Dots: Forecasting and Narrating Stock Market Volatility," INFORMS Journal on Computing, INFORMS, vol. 36(6), pages 1400-1416, December.
    51. Massa, Massimo & von Beschwitz, Bastian & Keim, Donald B, 2015. "First to ?Read? the News: News Analytics and Institutional Trading," CEPR Discussion Papers 10534, C.E.P.R. Discussion Papers.
    52. Gupta, Kartick & Banerjee, Rajabrata, 2019. "Does OPEC news sentiment influence stock returns of energy firms in the United States?," Energy Economics, Elsevier, vol. 77(C), pages 34-45.
    53. Daniel Martin Katz & Michael J Bommarito II & Tyler Soellinger & James Ming Chen, 2015. "Law on the Market? Abnormal Stock Returns and Supreme Court Decision-Making," Papers 1508.05751, arXiv.org, revised May 2017.
    54. Smales, Lee A., 2014. "Non-scheduled news arrival and high-frequency stock market dynamics," Research in International Business and Finance, Elsevier, vol. 32(C), pages 122-138.
    55. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
    56. Smales, Lee A., 2016. "News sentiment and bank credit risk," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 37-61.
    57. Wang, Yuchen & Wang, Xiaoming, 2023. "Economic policy uncertainty and information intermediary: The case of short seller," Economic Modelling, Elsevier, vol. 120(C).
    58. Donald B. Keim & Massimo Massa & Bastian von Beschwitz, 2018. "First to \"Read\" the News: New Analytics and Algorithmic Trading," International Finance Discussion Papers 1233, Board of Governors of the Federal Reserve System (U.S.).
    59. Khuu, Joyce & Durand, Robert B. & Smales, Lee A., 2016. "Melancholia and Japanese stock returns – 2003 to 2012," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 424-437.
    60. Yang, Ann Shawing, 2020. "Misinformation corrections of corporate news: Corporate clarification announcements," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    61. Dugast, J., 2013. "Limited attention and news arrival in limit order markets," Working papers 449, Banque de France.
    62. Diego A. Agudelo & Ignacio Arango, 2017. "How does information disclosure affect liquidity? Evidence from an Emerging Market," Documentos de Trabajo de Valor Público 16944, Universidad EAFIT.
    63. Andrew Todd & James Bowden & Yashar Moshfeghi, 2024. "Text‐based sentiment analysis in finance: Synthesising the existing literature and exploring future directions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(1), March.
    64. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2015. "Novel and topical business news and their impact on stock market activities," Papers 1507.06477, arXiv.org.
    65. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2015. "Novel and topical business news and their impact on stock market activities," CARF F-Series CARF-F-366, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    66. Apergis, Nicholas, 2015. "Newswire messages and sovereign credit ratings: Evidence from European countries under austerity reform programmes," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 54-62.
    67. Svetlana Borovkova & Diego Mahakena, 2015. "News, volatility and jumps: the case of natural gas futures," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1217-1242, July.
    68. Arango, Ignacio & Agudelo, Diego A., 2019. "How does information disclosure affect liquidity? Evidence from an emerging market," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    69. Joel Hasbrouck, 2021. "Rejoinder on: Price Discovery in High Resolution," Journal of Financial Econometrics, Oxford University Press, vol. 19(3), pages 465-471.
    70. Clements, A.E. & Hurn, A.S. & Volkov, V.V., 2016. "Common trends in global volatility," Journal of International Money and Finance, Elsevier, vol. 67(C), pages 194-214.
    71. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
    72. Alexander Koch & Toan Luu Duc Huynh & Mei Wang, 2024. "News sentiment and international equity markets during BREXIT period: A textual and connectedness analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 5-34, January.
    73. Justina Deveikyte & Helyette Geman & Carlo Piccari & Alessandro Provetti, 2020. "A Sentiment Analysis Approach to the Prediction of Market Volatility," Papers 2012.05906, arXiv.org.
    74. Gao, Yang & Wang, Yaojun & Wang, Chao & Liu, Chao, 2018. "Internet attention and information asymmetry: Evidence from Qihoo 360 search data on the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 802-811.
    75. Siikanen, Milla & Kanniainen, Juho & Valli, Jaakko, 2017. "Limit order books and liquidity around scheduled and non-scheduled announcements: Empirical evidence from NASDAQ Nordic," Finance Research Letters, Elsevier, vol. 21(C), pages 264-271.
    76. Nicholas Apergis & Ioannis Pragidis, 2019. "Stock Price Reactions to Wire News from the European Central Bank: Evidence from Changes in the Sentiment Tone and International Market Indexes," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 91-112, February.
    77. Kohonen, Anssi, 2013. "On detection of volatility spillovers in overlapping stock markets," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 140-158.
    78. Francisco Jareño & Ana Escribano & Zaghum Umar, 2023. "The impact of the COVID-19 outbreak on the connectedness of the BRICS’s term structure," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    79. Danilo Vassallo & Giacomo Bormetti & Fabrizio Lillo, 2019. "A tale of two sentiment scales: Disentangling short-run and long-run components in multivariate sentiment dynamics," Papers 1910.01407, arXiv.org, revised Sep 2020.
    80. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2015. "Novel and topical business news and their impact on stock market activities," UTokyo Price Project Working Paper Series 055, University of Tokyo, Graduate School of Economics.
    81. Andreas Storkenmaier & Martin Wagener & Christof Weinhardt, 2012. "Public information in fragmented markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(2), pages 179-215, June.
    82. Akhtaruzzaman, Md & Boubaker, Sabri & Umar, Zaghum, 2022. "COVID–19 media coverage and ESG leader indices," Finance Research Letters, Elsevier, vol. 45(C).
    83. Gabriele Ranco & Darko Aleksovski & Guido Caldarelli & Miha Grčar & Igor Mozetič, 2015. "The Effects of Twitter Sentiment on Stock Price Returns," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-21, September.
    84. Durand, Robert B. & Khuu, Joyce & Smales, Lee A., 2023. "Lost in translation. When sentiment metrics for one market are derived from two different languages," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    85. Smales, Lee A., 2015. "Time-variation in the impact of news sentiment," International Review of Financial Analysis, Elsevier, vol. 37(C), pages 40-50.
    86. Clements, A.E. & Liao, Y., 2020. "Firm-specific information and systemic risk," Economic Modelling, Elsevier, vol. 90(C), pages 480-493.
    87. Smales, Lee A., 2015. "Asymmetric volatility response to news sentiment in gold futures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 161-172.
    88. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.
    89. Smales, Lee A., 2014. "News sentiment in the gold futures market," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 275-286.
    90. Rühl, Tobias R. & Stein, Michael, 2015. "The impact of ECB macro-announcements on bid–ask spreads of European blue chips," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 54-71.
    91. Zhang, Junru & Zhang, Zhaoyong, 2021. "CSR, Media and Stock Illiquidity: Evidence from Chinese Listed Financial Firms," Finance Research Letters, Elsevier, vol. 41(C).
    92. Katherine B. Ensor & Yu Han & Barbara Ostdiek & Stuart M. Turnbull, 2020. "Dynamic jump intensities and news arrival in oil futures markets," Journal of Asset Management, Palgrave Macmillan, vol. 21(4), pages 292-325, July.
    93. Zhang, Junni L. & Härdle, Wolfgang Karl & Chen, Cathy Y. & Bommes, Elisabeth, 2015. "Distillation of news flow into analysis of stock reactions," SFB 649 Discussion Papers 2015-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    94. Riordan, Ryan & Storkenmaier, Andreas & Wagener, Martin & Sarah Zhang, S., 2013. "Public information arrival: Price discovery and liquidity in electronic limit order markets," Journal of Banking & Finance, Elsevier, vol. 37(4), pages 1148-1159.

  26. Hautsch, Nikolaus & Hess, Dieter & Veredas, David, 2011. "The impact of macroeconomic news on quote adjustments, noise, and informational volatility," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2733-2746, October.
    See citations under working paper version above.
  27. Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
    See citations under working paper version above.
  28. Hautsch, Nikolaus & Hess, Dieter, 2007. "Bayesian Learning in Financial Markets: Testing for the Relevance of Information Precision in Price Discovery," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(1), pages 189-208, March.
    See citations under working paper version above.
  29. Hall, Anthony D. & Hautsch, Nikolaus, 2007. "Modelling the buy and sell intensity in a limit order book market," Journal of Financial Markets, Elsevier, vol. 10(3), pages 249-286, August.

    Cited by:

    1. Bastian Felix & Oliver Woll & Christoph Weber, 2009. "Gas Storage Valuation Under Limited Market Liquidity: An Application In Germany," EWL Working Papers 0903, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Oct 2009.
    2. Katarzyna Bień-Barkowska, 2014. "“Every move you make, every step you take, I’ll be watching you” – the quest for hidden orders in the interbank FX spot market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(3), pages 197-224.
    3. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    4. Roberto Pascual & David Veredas, 2009. "Does the open limit order book matter in explaining informational volatility?," ULB Institutional Repository 2013/183777, ULB -- Universite Libre de Bruxelles.
    5. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Alessio Sancetta, 2017. "Estimation for the Prediction of Point Processes with Many Covariates," Papers 1702.05315, arXiv.org.
    7. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
    8. Matthew C. Chang & Rebecca Chung-Fern Wu, 2013. "Informativeness and Influence of Limit Order Books on Order Submissions in Electronic Continuous Auction Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S3), pages 70-97, July.
    9. Henk Berkman & Carole Comerton‐Forde, 2011. "Market microstructure: A review from down under," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 51(1), pages 50-78, March.
    10. Katarzyna Bień-Barkowska, 2014. "Capturing Order Book Dynamics in the Interbank EUR/PLN Spot Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 93-117, January.
    11. Tsung-Yu Hsieh, 2015. "Information disclosure and price manipulation during the pre-closing session: evidence from an order-driven market," Applied Economics, Taylor & Francis Journals, vol. 47(43), pages 4670-4684, September.
    12. Alexis Stenfors & Masayuki Susai, 2017. "Liquidity Withdrawal in the FX Spot Market: A Cross-Country Study Using High-Frequency Data," Working Papers in Economics & Finance 2017-06, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    13. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    14. Thierry Foucault & Ohad Kadan & Eugene Kandel, 2013. "Liquidity Cycles and Make/Take Fees in Electronic Markets," Post-Print hal-00789263, HAL.
    15. Hautsch, Nikolaus & Herrera, Rodrigo, 2015. "Multivariate dynamic intensity peaks-over-threshold models," CFS Working Paper Series 516, Center for Financial Studies (CFS).
    16. Ladley, Dan & Schenk-Hoppé, Klaus Reiner, 2009. "Do stylised facts of order book markets need strategic behaviour?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 817-831, April.
    17. Kohler, Alexander & von Wyss, Rico, 2012. "Where does Information Processing in a Fragmented Market Take Place? – Evidence from the Swiss Stock Market after MiFID," Working Papers on Finance 1209, University of St. Gallen, School of Finance.
    18. Ioane Muni Toke, 2011. ""Market making" behaviour in an order book model and its impact on the bid-ask spread," Post-Print hal-01705266, HAL.
    19. Zhicheng Li & Haipeng Xing, 2022. "High-Frequency Quote Volatility Measurement Using a Change-Point Intensity Model," Mathematics, MDPI, vol. 10(4), pages 1-24, February.
    20. Ioane Muni Toke, 2010. ""Market making" behaviour in an order book model and its impact on the bid-ask spread," Papers 1003.3796, arXiv.org, revised Jun 2010.
    21. Moshirian, Fariborz & Nguyen, Huong Giang (Lily) & Pham, Peter Kien, 2012. "Overnight public information, order placement, and price discovery during the pre-opening period," Journal of Banking & Finance, Elsevier, vol. 36(10), pages 2837-2851.
    22. Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    23. Miquel Montero, 2021. "Predator–prey model for stock market fluctuations," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(1), pages 29-57, January.
    24. Adam Clements & Joanne Fuller & Vasilios Papalexiou, 2015. "Public news flow in intraday component models for trading activity and volatility," NCER Working Paper Series 106, National Centre for Econometric Research.
    25. Jón Daníelsson & Richard Payne, 2012. "Liquidity determination in an order-driven market," The European Journal of Finance, Taylor & Francis Journals, vol. 18(9), pages 799-821, October.
    26. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
    27. Będowska-Sójka, Barbara, 2020. "Do aggressive orders affect liquidity? An evidence from an emerging market," Research in International Business and Finance, Elsevier, vol. 54(C).
    28. Luca Mucciante & Alessio Sancetta, 2023. "Estimation of an Order Book Dependent Hawkes Process for Large Datasets," Papers 2307.09077, arXiv.org.
    29. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    30. Yensen Ni & Yulu Liao & Paoyu Huang, 2017. "Foreign Institutional Investors, Shareholding Change, and Corporate Governance," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(4), pages 764-775, April.
    31. Ingrid Lo & Stephen Sapp, 2011. "Belief Dispersion and Order Submission Strategies in the Foreign Exchange Market," Staff Working Papers 11-8, Bank of Canada.
    32. Lo, Ingrid & Sapp, Stephen G., 2010. "Order aggressiveness and quantity: How are they determined in a limit order market?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(3), pages 213-237, July.
    33. Anagnostidis, Panagiotis & Kanas, Angelos & Papachristou, George, 2015. "Information revelation in the Greek exchange opening call: Daily and intraday evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 167-184.
    34. Liu, Hsing & Liao, Chi-Yo & Ko, Jing-Yuan & Lih, Jiann-Shing, 2017. "Anchoring effect on first passage process in Taiwan financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 114-127.
    35. Alexis Stenfors & Masayuki Susai, 2017. "Algorithmic Trading Behaviour and High-Frequency Liquidity Withdrawal in the FX Spot Market," Working Papers in Economics & Finance 2017-04, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    36. Roberto Pascual & David Veredas, 2009. "What pieces of limit order book information matter in explaining order choice by patient and impatient traders?," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 527-545.
    37. Masashi Ieda, 2015. "A dynamic optimal execution strategy under stochastic price recovery," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-24, December.
    38. Hugh L. Christensen & Richard E. Turner & Simon I. Hill & Simon J. Godsill, 2013. "Rebuilding the limit order book: sequential Bayesian inference on hidden states," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1779-1799, November.
    39. Miquel Montero, 2008. "Predator-Prey Model for Stock Market Fluctuations," Papers 0810.4844, arXiv.org, revised Jul 2009.
    40. Masashi Ieda, 2015. "A dynamic optimal execution strategy under stochastic price recovery," Papers 1502.04521, arXiv.org.

  30. Gerhard Frank & Hautsch Nikolaus, 2007. "A Dynamic Semiparametric Proportional Hazard Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(2), pages 1-42, May.
    See citations under working paper version above.
  31. Luc Bauwens & Nikolaus Hautsch, 2006. "Stochastic Conditional Intensity Processes," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 450-493.
    See citations under working paper version above.
  32. Anthony Hall & Nikolaus Hautsch, 2006. "Order aggressiveness and order book dynamics," Empirical Economics, Springer, vol. 30(4), pages 973-1005, January.
    See citations under working paper version above.
  33. Hautsch, Nikolaus & Klotz, Stefan, 2003. "Estimating the neighborhood influence on decision makers: theory and an application on the analysis of innovation decisions," Journal of Economic Behavior & Organization, Elsevier, vol. 52(1), pages 97-113, September.
    See citations under working paper version above.
  34. Nikolaus Hautsch, 2003. "Assessing the Risk of Liquidity Suppliers on the Basis of Excess Demand Intensities," Journal of Financial Econometrics, Oxford University Press, vol. 1(2), pages 189-215.

    Cited by:

    1. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," MPRA Paper 93802, University Library of Munich, Germany.
    3. Yiing Fei Tan & Kok Haur Ng & You Beng Koh & Shelton Peiris, 2022. "Modelling Trade Durations Using Dynamic Logarithmic Component ACD Model with Extended Generalised Inverse Gaussian Distribution," Mathematics, MDPI, vol. 10(10), pages 1-20, May.
    4. Renault, Eric & Werker, Bas J.M., 2011. "Causality effects in return volatility measures with random times," Journal of Econometrics, Elsevier, vol. 160(1), pages 272-279, January.
    5. Aneta Hryckiewicz & Piotr Mielus & Karolina Skorulska & Malgorzata Snarska, 2018. "Does a bank levy increase frictions on the interbank market?," KAE Working Papers 2018-033, Warsaw School of Economics, Collegium of Economic Analysis.
    6. Petra Tomanová & Vladimír Holý, 2021. "Clustering of arrivals in queueing systems: autoregressive conditional duration approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(3), pages 859-874, September.
    7. Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    9. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
    10. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    11. Yongmiao Hong & Yoon-Jin Lee, 2007. "Detecting Misspecifications in Autoregressive Conditional Duration Models," CAEPR Working Papers 2007-019, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.

  35. Nikolaus Hautsch & Joachim Inkmann, 2003. "Optimal hedging of the currency exchange risk exposure of dynamically balanced strategic asset allocations," Journal of Asset Management, Palgrave Macmillan, vol. 4(3), pages 173-198, September.

    Cited by:

    1. Mohini GUPTA & Purwa SRIVASTAVA & Amritkant MISHRA & Malayaranjan SAHOO, 2021. "Time-varying volatility spillover of foreign exchange rate in three Asian markets: Based on DCC-GARCH approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(629), W), pages 105-120, Winter.

  36. Nikolaus Hautsch & Dieter Hess, 2002. "The Processing of Non-Anticipated Information in Financial Markets: Analyzing the Impact of Surprises in the Employment Report," Review of Finance, European Finance Association, vol. 6(2), pages 133-161.
    See citations under working paper version above.
  37. Gerhard, Frank & Hautsch, Nikolaus, 2002. "Volatility estimation on the basis of price intensities," Journal of Empirical Finance, Elsevier, vol. 9(1), pages 57-89, January.
    See citations under working paper version above.

Chapters

  1. Anthony D. Hall & Nikolaus Hautsch, 2008. "Order aggressiveness and order book dynamics," Studies in Empirical Economics, in: Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), High Frequency Financial Econometrics, pages 133-165, Springer.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

Books

  1. Nikolaus Hautsch, 2012. "Econometrics of Financial High-Frequency Data," Springer Books, Springer, number 978-3-642-21925-2, March.

    Cited by:

    1. Giuseppe Cavaliere & Thomas Mikosch & Anders Rahbek & Frederik Vilandt, 2022. "The Econometrics of Financial Duration Modeling," Papers 2208.02098, arXiv.org, revised Dec 2022.
    2. Hiroyuki Kawakatsu, 2019. "Jointly Modeling Autoregressive Conditional Mean and Variance of Non-Negative Valued Time Series," Econometrics, MDPI, vol. 7(4), pages 1-19, December.
    3. Herrera, Rodrigo & González, Nicolás, 2014. "The modeling and forecasting of extreme events in electricity spot markets," International Journal of Forecasting, Elsevier, vol. 30(3), pages 477-490.
    4. Wen Cao & Clifford Hurvich & Philippe Soulier, 2012. "Drift in Transaction-Level Asset Price Models," Working Papers hal-00756372, HAL.
    5. Virgil DAMIAN & Cosmin – Octavian CEPOI, 2016. "Volatility Estimators With High-Frequency Data From Bucharest Stock Exchange," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 247-264.
    6. Kara Karpman & Sumanta Basu & David Easley, 2022. "Learning Financial Networks with High-frequency Trade Data," Papers 2208.03568, arXiv.org.
    7. Richard Y. Chen & Per A. Mykland, 2015. "Model-Free Approaches to Discern Non-Stationary Microstructure Noise and Time-Varying Liquidity in High-Frequency Data," Papers 1512.06159, arXiv.org, revised Oct 2018.
    8. Vasileios Siakoulis & Ioannis Venetis, 2015. "On inter-arrival times of bond market extreme events. An application to seven European markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(4), pages 717-741, October.
    9. Yiing Fei Tan & Kok Haur Ng & You Beng Koh & Shelton Peiris, 2022. "Modelling Trade Durations Using Dynamic Logarithmic Component ACD Model with Extended Generalised Inverse Gaussian Distribution," Mathematics, MDPI, vol. 10(10), pages 1-20, May.
    10. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
    11. Davide La Vecchia & Alban Moor & O. Scaillet, 2020. "A Higher-Order Correct Fast Moving-Average Bootstrap for Dependent Data," Swiss Finance Institute Research Paper Series 20-01, Swiss Finance Institute.
    12. Yuanhua Feng & Sarah Forstinger & Christian Peitz, 2013. "On the iterative plug-in algorithm for estimating diurnal patterns of financial trade durations," Working Papers CIE 66, Paderborn University, CIE Center for International Economics.
    13. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    14. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2021. "Autoregressive conditional proportion: A multiplicative-error model for (0,1)-valued time series," MPRA Paper 110954, University Library of Munich, Germany, revised 06 Dec 2021.
    15. Abdelhakim Aknouche & Christian Francq, 2022. "Stationarity and ergodicity of Markov switching positive conditional mean models," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 436-459, May.
    16. Zhang, Shulin & Okhrin, Ostap & Zhou, Qian M. & Song, Peter X.-K., 2016. "Goodness-of-fit test for specification of semiparametric copula dependence models," Journal of Econometrics, Elsevier, vol. 193(1), pages 215-233.
    17. Piotr Fiszeder & Grzegorz Perczak, 2013. "A new look at variance estimation based on low, high and closing prices taking into account the drift," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(4), pages 456-481, November.
    18. Daniel W. Richards & Janette Rutterford & Devendra Kodwani & Mark Fenton-O'Creevy, 2017. "Stock market investors' use of stop losses and the disposition effect," The European Journal of Finance, Taylor & Francis Journals, vol. 23(2), pages 130-152, January.
    19. Simona ADASCALI?EI, 2014. "High Frequency Trading – A Revolutionary Concept On Financial Markets," THE YEARBOOK OF THE "GH. ZANE" INSTITUTE OF ECONOMIC RESEARCHES, Gheorghe Zane Institute for Economic and Social Research ( from THE ROMANIAN ACADEMY, JASSY BRANCH), vol. 23(1), pages 27-34.
    20. Hautsch, Nikolaus & Okhrin, Ostap & Ristig, Alexander, 2012. "Modeling time-varying dependencies between positive-valued high-frequency time series," SFB 649 Discussion Papers 2012-054, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    21. Pan, Beier, 2023. "The asymmetric dynamics of stock–bond liquidity correlation in China: The role of macro-financial determinants," Economic Modelling, Elsevier, vol. 124(C).
    22. Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
    23. Roman Huptas, 2016. "The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 1-20, March.
    24. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    25. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    26. N. Balakrishna & H. L. Koul & M. Ossiander & L. Sakhanenko, 2019. "Fitting a pth Order Parametric Generalized Linear Autoregressive Multiplicative Error Model," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 103-122, September.
    27. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
    28. José Da Fonseca & Riadh Zaatour, 2017. "Correlation and Lead–Lag Relationships in a Hawkes Microstructure Model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(3), pages 260-285, March.
    29. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
    30. Hira L. Koul & Indeewara Perera & Narayana Balakrishna, 2023. "A class of Minimum Distance Estimators in Markovian Multiplicative Error Models," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 87-115, May.
    31. Jan Beran & Yuanhua Feng & Sucharita Ghosh, 2015. "Modelling long-range dependence and trends in duration series: an approach based on EFARIMA and ESEMIFAR models," Statistical Papers, Springer, vol. 56(2), pages 431-451, May.
    32. Erindi Allaj, 2017. "Implicit Transaction Costs And The Fundamental Theorems Of Asset Pricing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-39, June.
    33. Aknouche, Abdelhakim & Almohaimeed, Bader & Dimitrakopoulos, Stefanos, 2020. "Periodic autoregressive conditional duration," MPRA Paper 101696, University Library of Munich, Germany, revised 08 Jul 2020.
    34. Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna, 2020. "Bias corrections for exponentially transformed forecasts: Are they worth the effort?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 761-780.
    35. Samuel Gingras & William J. McCausland, 2020. "A Flexible Stochastic Conditional Duration Model," Papers 2005.09166, arXiv.org.
    36. Cavaliere, Giuseppe & Mikosch, Thomas & Rahbek, Anders & Vilandt, Frederik, 2024. "Tail behavior of ACD models and consequences for likelihood-based estimation," Journal of Econometrics, Elsevier, vol. 238(2).
    37. Siakoulis, Vasilios, 2015. "Modeling bank default intensity in the USA using autoregressive duration models," MPRA Paper 64526, University Library of Munich, Germany.
    38. Roman Huptas, 2014. "Bayesian Estimation and Prediction for ACD Models in the Analysis of Trade Durations from the Polish Stock Market," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(4), pages 237-273, December.
    39. Yuta Koike, 2017. "Time endogeneity and an optimal weight function in pre-averaging covariance estimation," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 15-56, April.
    40. Alexandre de Carvalho & Alberto Sanyuan Suen & Felippe Gallo, 2016. "Market Efficiency in Brazil: some evidence from high-frequency data," Working Papers Series 431, Central Bank of Brazil, Research Department.
    41. Brownlees Christian T. & Vannucci Marina, 2013. "A Bayesian approach for capturing daily heterogeneity in intra-daily durations time series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 21-46, February.
    42. Gerardo-Giorda, Luca & Germano, Guido & Scalas, Enrico, 2015. "Large scale simulation of synthetic markets," LSE Research Online Documents on Economics 67563, London School of Economics and Political Science, LSE Library.
    43. Giuseppe Arbia & Michele Di Marcantonio, 2015. "Forecasting Interest Rates Using Geostatistical Techniques," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    44. Curato, Imma Valentina, 2019. "Estimation of the stochastic leverage effect using the Fourier transform method," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3207-3238.
    45. Lock, Eduardo & Winkelried, Diego, 2015. "Flujos de órdenes en el mercado cambiario y el valor intrínseco del Nuevo Sol," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 29, pages 33-54.
    46. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2024. "Volatility models versus intensity models: analogy and differences," MPRA Paper 122528, University Library of Munich, Germany.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.