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Massimiliano Caporin

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.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Massimiliano Caporin & Michael McAleer, 2009. "A Scientific Classification of Volatility Models," Documentos de Trabajo del ICAE 2009-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

    Mentioned in:

    1. > Schools of Economic Thought, Epistemology of Economics > Heterodox Approaches > Thermoeconomics > The economy system as a living organism

Working papers

  1. Caporin, Massimiliano & Fontini, Fulvio & Panzica, Roberto, 2022. "The systemic risk of US oil and natural gas companies," Working Papers 2022-11, Joint Research Centre, European Commission.

    Cited by:

    1. 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).
    2. Huszár, Zsuzsa R. & Kotró, Balázs B. & Tan, Ruth S.K., 2023. "Dynamic volatility transfer in the European oil and gas industry," Energy Economics, Elsevier, vol. 127(PA).

  2. Giovanni Bonaccolto & Massimiliano Caporin & Bertrand Maillet, 2022. "Dynamic Large Financial Networks via Conditional Expected Shortfalls," Post-Print hal-03287947, HAL.

    Cited by:

    1. Tang, Qihe & Tong, Zhiwei & Xun, Li, 2022. "Insurance risk analysis of financial networks vulnerable to a shock," European Journal of Operational Research, Elsevier, vol. 301(2), pages 756-771.
    2. Ling, Aifan & Li, Jinlong & Zhang, Yugui, 2023. "Can firms with higher ESG ratings bear higher bank systemic tail risk spillover?—Evidence from Chinese A-share market," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    3. Gong, Qingbin & Diao, Xundi, 2023. "The impacts of investor network and herd behavior on market stability: Social learning, network structure, and heterogeneity," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1388-1398.
    4. Alexandre, Michel & Silva, Thiago Christiano & Michalak, Krzysztof & Rodrigues, Francisco Aparecido, 2023. "Does the default pecking order impact systemic risk? Evidence from Brazilian data," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1379-1391.
    5. Caporin, Massimiliano & Costola, Michele & Garibal, Jean-Charles & Maillet, Bertrand, 2022. "Systemic risk and severe economic downturns: A targeted and sparse analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    6. Yfanti, Stavroula & Karanasos, Menelaos & Zopounidis, Constantin & Christopoulos, Apostolos, 2023. "Corporate credit risk counter-cyclical interdependence: A systematic analysis of cross-border and cross-sector correlation dynamics," European Journal of Operational Research, Elsevier, vol. 304(2), pages 813-831.
    7. Lazar, Emese & Wang, Shixuan & Xue, Xiaohan, 2023. "Loss function-based change point detection in risk measures," European Journal of Operational Research, Elsevier, vol. 310(1), pages 415-431.

  3. Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Díaz & Menachem Abudy & To, 2021. "Non-Standard Errors," Working Paper Series, Social and Economic Sciences 2021-11, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    • 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.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian Brownlees & 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.
    • 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. 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.
    3. Christoph Huber & Christian König-Kersting, 2022. "Experimenting with Financial Professionals," Working Papers 2022-07, Faculty of Economics and Statistics, Universität Innsbruck.
    4. Dreber, Anna & Johannesson, Magnus, 2023. "A framework for evaluating reproducibility and replicability in economics," I4R Discussion Paper Series 38, The Institute for Replication (I4R).
    5. Müller, Isabella & Noth, Felix & Tonzer, Lena, 2022. "A note on the use of syndicated loan data," IWH Discussion Papers 17/2022, Halle Institute for Economic Research (IWH).
    6. 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.
    7. 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.
    8. 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.

  4. Cinzia Bonaldo & Massimiliano Caporin & Fulvio Fontini, 2021. "The relationship between day-ahead and futures prices in the electricity markets: an empirical analysis on Italy, France, Germany and Switzerland," "Marco Fanno" Working Papers 0272, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Bonaldo, Cinzia & Fontini, Fulvio & Moretto, Michele, 2022. "The Energy Transition and the Value of Capacity Remuneration Mechanisms," FEEM Working Papers 321985, Fondazione Eni Enrico Mattei (FEEM).
    2. Falbo, Paolo & Ruiz, Carlos, 2023. "Joint optimization of sales-mix and generation plan for a large electricity producer," Energy Economics, Elsevier, vol. 120(C).

  5. Massimiliano Caporin & Zahra Mohammadi Nikpour & Paola Valbonesi, 2020. "Oil Price Uncertainty and Conflicts: Evidence from the Middle East and North Africa," "Marco Fanno" Working Papers 0250, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Dawud Ansari & Mariza Montes de Oca Leon & Helen Schlüter, 2021. "What Drives Saudi Airstrikes in Yemen? An Empirical Analysis of the Dynamics of Coalition Airstrikes, Houthi Attacks, and the Oil Market," Discussion Papers of DIW Berlin 1959, DIW Berlin, German Institute for Economic Research.

  6. Caporin, Massimiliano & Pelizzon, Loriana & Plazzi, Alberto, 2020. "Does monetary policy impact international market co-movements?," SAFE Working Paper Series 276, Leibniz Institute for Financial Research SAFE.

    Cited by:

    1. Berardi, Andrea & Plazzi, Alberto, 2022. "Dissecting the yield curve: The international evidence," Journal of Banking & Finance, Elsevier, vol. 134(C).
    2. Karau, Sören, 2021. "Monetary policy and Bitcoin," Discussion Papers 41/2021, Deutsche Bundesbank.
    3. Karau, Sören, 2023. "Monetary policy and Bitcoin," Journal of International Money and Finance, Elsevier, vol. 137(C).

  7. Massimiliano Caporin & Rangan Gupta & Francesco Ravazzolo, 2019. "Contagion between Real Estate and Financial Markets: A Bayesian Quantile-on-Quantile Approach," BEMPS - Bozen Economics & Management Paper Series BEMPS61, Faculty of Economics and Management at the Free University of Bozen.

    Cited by:

    1. Kola Ijasan & Peterson Owusu Junior & George Tweneboah & Tunbosun Oyedokun & Anokye M. Adam, 2021. "Analysing the relationship between global REITs and exchange rates: Fresh evidence from frequency-based quantile regressions," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(3), pages 58-91, September.
    2. Wang, Peiwan & Zong, Lu, 2020. "Contagion effects and risk transmission channels in the housing, stock, interest rate and currency markets: An Empirical Study in China and the U.S," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    3. Asima Siddique & Ghulam Mujtaba Kayani & Saira Ashfaq, 2021. "Does Heterogeneity in COVID-19 News Affect Asset Market? Monte-Carlo Simulation Based Wavelet Transform," JRFM, MDPI, vol. 14(10), pages 1-16, October.
    4. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org.
    5. Walid Mensi & Zhuhua Jiang & Xuan Vinh Vo & Seong‐Min Yoon, 2023. "Asymmetric volatility transmission and hedging strategies among REIT, stock, and oil markets," Australian Economic Papers, Wiley Blackwell, vol. 62(4), pages 597-615, December.
    6. David Gabauer & Rangan Gupta & Sayar Karmakar & Joshua Nielsen, 2022. "Stock Market Bubbles and the Forecastability of Gold Returns (and Volatility)," Working Papers 202228, University of Pretoria, Department of Economics.
    7. Zheng Zheng Li & Chi-Wei Su, 2023. "How does real estate market react to the iron ore boom in Australian capital cities?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 71(2), pages 517-537, October.
    8. Wen Chang, Hao & Chang, Tsangyao, 2023. "How oil price and exchange rate affect stock price in China using Bayesian Quantile_on_Quantile with GARCH approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    9. Fasanya, Ismail O. & Oyewole, Oluwatomisin J., 2023. "On the connection between international REITs and oil markets: The role of economic policy uncertainty," Resources Policy, Elsevier, vol. 81(C).
    10. Goodness C. Aye & Christina Christou & Rangan Gupta & Christis Hassapis, 2021. "High-Frequency Contagion between Aggregate and Regional Housing Markets of the United States with Financial Assets: Evidence from Multichannel Tests," Working Papers 202159, University of Pretoria, Department of Economics.

  8. Carlos Vladimir Rodríguez-Caballero & Massimiliano Caporin, 2018. "A multilevel factor approach for the analysis of CDS commonality and risk contribution," CREATES Research Papers 2018-33, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Rodríguez-Caballero, Carlos Vladimir, 2022. "Energy consumption and GDP: a panel data analysis with multi-level cross-sectional dependence," Econometrics and Statistics, Elsevier, vol. 23(C), pages 128-146.
    2. Ergemen, Yunus Emre & Rodríguez Caballero, Carlos Vladimir, 2017. "Estimation of a Dynamic Multilevel Factor Model with possible long-range dependence," DES - Working Papers. Statistics and Econometrics. WS 24614, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021. "Expecting the unexpected: economic growth under stress," Working Papers 202106, University of California at Riverside, Department of Economics.

  9. Massimiliano Caporin & Michele Costola & Gregory Jannin & Bertrand Maillet, 2018. "“On the (Ab)use of Omega?”," Post-Print hal-02312145, HAL.

    Cited by:

    1. Hamidi, Benjamin & Maillet, Bertrand & Prigent, Jean-Luc, 2014. "A dynamic autoregressive expectile for time-invariant portfolio protection strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 46(C), pages 1-29.
    2. Balbás, Alejandro & Serna, Gregorio, 2024. "Selling options to beat the market: Further empirical evidence," Research in International Business and Finance, Elsevier, vol. 67(PB).
    3. Niu, Cuizhen & Wong, Wing-Keung & Zhu, Lixing, 2017. "Farinelli and Tibiletti ratio and Stochastic Dominance," MPRA Paper 82737, University Library of Munich, Germany.
    4. Carole Bernard & Massimiliano Caporin & Bertrand Maillet & Xiang Zhang, 2023. "Omega Compatibility: A Meta-analysis," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 493-526, August.
    5. Balder, Sven & Schweizer, Nikolaus, 2017. "Risk aversion vs. the Omega ratio: Consistency results," Finance Research Letters, Elsevier, vol. 21(C), pages 78-84.
    6. Taylor, James W., 2022. "Forecasting Value at Risk and expected shortfall using a model with a dynamic omega ratio," Journal of Banking & Finance, Elsevier, vol. 140(C).
    7. Eric Benhamou & Beatrice Guez & Nicolas Paris1, 2019. "Omega and Sharpe ratio," Papers 1911.10254, arXiv.org.
    8. Monica Billio & Bertrand Maillet & Loriana Pelizzon, 2021. "A meta-measure of performance related to both investors and investments characteristics," Post-Print hal-03543398, HAL.
    9. Bernard, Carole & Vanduffel, Steven & Ye, Jiang, 2019. "Optimal strategies under Omega ratio," European Journal of Operational Research, Elsevier, vol. 275(2), pages 755-767.
    10. Sehgal, Ruchika & Sharma, Amita & Mansini, Renata, 2023. "Worst-case analysis of Omega-VaR ratio optimization model," Omega, Elsevier, vol. 114(C).
    11. Xu Guo & Xuejun Jiang & Wing-Keung Wong, 2017. "Stochastic Dominance and Omega Ratio: Measures to Examine Market Efficiency, Arbitrage Opportunity, and Anomaly," Economies, MDPI, vol. 5(4), pages 1-16, October.
    12. Balter, Anne G. & Chau, Ki Wai & Schweizer, Nikolaus, 2024. "Comparative risk aversion vs. threshold choice in the Omega ratio," Omega, Elsevier, vol. 123(C).
    13. Yu, Jing-Rung & Paul Chiou, Wan-Jiun & Hsin, Yi-Ting & Sheu, Her-Jiun, 2022. "Omega portfolio models with floating return threshold," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 743-758.

  10. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto Calogero & Pelizzon, Loriana, 2017. "The impact of network connectivity on factor exposures, asset pricing and portfolio diversification," SAFE Working Paper Series 166, Leibniz Institute for Financial Research SAFE.

    Cited by:

    1. Murat Tiniç & Ahmet Sensoy & Muge Demir & Duc Khuong Nguyen, 2021. "Broker Network Connectivity and the Cross-Section of Expected Stock Returns," Working Papers 2021-002, Department of Research, Ipag Business School.
    2. Giovanni Bonaccolto & Massimiliano Caporin & Bertrand Maillet, 2022. "Dynamic Large Financial Networks via Conditional Expected Shortfalls," Post-Print hal-03287947, HAL.
    3. Billio, Monica & Caporin, Massimiliano & Frattarolo, Lorenzo & Pelizzon, Loriana, 2018. "Networks in risk spillovers: A multivariate GARCH perspective," SAFE Working Paper Series 225, Leibniz Institute for Financial Research SAFE.
    4. Michele Costola & Matteo Iacopini & Casper Wichers, 2023. "Bayesian SAR model with stochastic volatility and multiple time-varying weights," Papers 2310.17473, arXiv.org.
    5. Liu, Shaowen & Caporin, Massimiliano & Paterlini, Sandra, 2021. "Dynamic network analysis of North American financial institutions," Finance Research Letters, Elsevier, vol. 42(C).
    6. 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.
    7. Costola, Michele & Iacopini, Matteo & Wichers, Casper, 2023. "Bayesian SAR model with stochastic volatility and multiple time-varying weights," SAFE Working Paper Series 407, Leibniz Institute for Financial Research SAFE.

  11. Massimiliano Caporin & Gisle J. Natvik & Francesco Ravazzolo & Paolo Santucci de Magistris, 2017. "The Bank-Sovereign Nexus: Evidence from a non-Bailout Episode," CREATES Research Papers 2017-25, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Nicolas Soenen & Rudi Vander Vennet, 2020. "ECB Monetary Policy and Bank Default Risk," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 20/997, Ghent University, Faculty of Economics and Business Administration.
    2. Velliscig, Giulio & Floreani, Josanco & Polato, Maurizio, 2022. "How do bail-in amendments in Directive (EU) 2017/2399 affect the subordinated bond yields of EU G-SIBs?," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 173-189.
    3. Soenen, Nicolas & Vander Vennet, Rudi, 2022. "ECB monetary policy and bank default risk☆," Journal of International Money and Finance, Elsevier, vol. 122(C).

  12. Khalifa, Ahmed & Caporin, Massimiliano & Costola, Michele & Hammoudeh, Shawkat, 2017. "Systemic risk for financial institutions of major petroleum-based economies: The role of oil," SAFE Working Paper Series 172, Leibniz Institute for Financial Research SAFE, revised 2017.

    Cited by:

    1. Caporin, Massimiliano & Fontini, Fulvio & Panzica, Roberto, 2022. "The systemic risk of US oil and natural gas companies," Working Papers 2022-11, Joint Research Centre, European Commission.
    2. Saif Sallam Alhakimi & Hussein Hamood Sharaf-Addin, 2022. "Investigating the Impact of Oil Prices Changes on Financial Market Efficiency in Saudi Arabia for the Period (1980-2018): ARDL Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 12(1), pages 420-426.

  13. Monica Billio & Massimiliano Caporin & Lorenzo Frattarolo & Loriana Pelizzon, 2016. "Networks in risk spillovers: a multivariate GARCH perspective," Working Papers 2016:03, Department of Economics, University of Venice "Ca' Foscari".

    Cited by:

    1. Laleh Tafakori & Armin Pourkhanali & Riccardo Rastelli, 2022. "Measuring systemic risk and contagion in the European financial network," Empirical Economics, Springer, vol. 63(1), pages 345-389, July.
    2. 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.
    3. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2021. "Systemic-systematic risk in financial system: A dynamic ranking based on expectiles," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 330-365.
    4. Bernardi, Mauro & Costola, Michele, 2019. "High-dimensional sparse financial networks through a regularised regression model," SAFE Working Paper Series 244, Leibniz Institute for Financial Research SAFE.
    5. Francesco Giuseppe Caloia & Andrea Cipollini & Silvia Muzzioli, 2016. "A note on normalization schemes:The case of generalized forecast error variance decompositions," Department of Economics 0092, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    6. Caloia, Francesco Giuseppe & Cipollini, Andrea & Muzzioli, Silvia, 2019. "How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study," Energy Economics, Elsevier, vol. 84(C).
    7. 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.
    8. Karatetskaya Efrosiniya & Lakshina Valeriya, 2018. "Volatility Spillovers With Spatial Effects On The Oil And Gas Market," HSE Working papers WP BRP 72/FE/2018, National Research University Higher School of Economics.
    9. Francesco Caloia & Andrea Cipollini & Silvia Muzzioli, 2018. "On the financial connectedness of the commodity market: a replication of the Diebold and Yilmaz (2012) study," Department of Economics 0131, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    10. 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.
    11. Xiurong Chen & Aimin Hao & Yali Li, 2020. "The impact of financial contagion on real economy-An empirical research based on combination of complex network technology and spatial econometrics model," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.

  14. Caporin, Massimiliano & Kolokolov, Alexey & Renò, Roberto, 2016. "Systemic co-jumps," SAFE Working Paper Series 149, Leibniz Institute for Financial Research SAFE.

    Cited by:

    1. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.

  15. Caporin, M. & Chang, C-L. & McAleer, M.J., 2016. "Are the S&P 500 Index and Crude Oil, Natural Gas and Ethanol Futures Related for Intra-Day Data?," Econometric Institute Research Papers EI2016-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Ngo Thai Hung, 2020. "Identifying the Dynamic Connectedness between Propane and Oil Prices: Evidence from Wavelet Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 315-326.
    2. Bonaccolto, G. & Caporin, M. & Gupta, R., 2018. "The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 446-469.
    3. Fredj Jawadi & Waël Louhichi & Hachmi Ben Ameur & Abdoulkarim Idi Cheffou, 2017. "On Oil-US Exchange Rate Volatility Relationships: an Intradaily Analysis," EconomiX Working Papers 2017-11, University of Paris Nanterre, EconomiX.
    4. Jiang, Ping & Liu, Zhenkun & Wang, Jianzhou & Zhang, Lifang, 2021. "Decomposition-selection-ensemble forecasting system for energy futures price forecasting based on multi-objective version of chaos game optimization algorithm," Resources Policy, Elsevier, vol. 73(C).
    5. Salisu, Afees A. & Raheem, Ibrahim D. & Ndako, Umar B., 2019. "A sectoral analysis of asymmetric nexus between oil price and stock returns," International Review of Economics & Finance, Elsevier, vol. 61(C), pages 241-259.
    6. Abdelkader Derbali & Tarek Chebbi, 2018. "Dynamic Equicorrelation between S&P500 Index and S&P GSCI," Working Papers hal-01695995, HAL.
    7. Jiaying Peng & Zhenghui Li & Benjamin M. Drakeford, 2020. "Dynamic Characteristics of Crude Oil Price Fluctuation—From the Perspective of Crude Oil Price Influence Mechanism," Energies, MDPI, vol. 13(17), pages 1-19, August.
    8. Chang, Chia-Lin & McAleer, Michael & Wang, Yu-Ann, 2020. "Herding behaviour in energy stock markets during the Global Financial Crisis, SARS, and ongoing COVID-19," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).

  16. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. 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).

  17. Massimiliano Caporin & Fulvio Fontini, 2015. "The Long-Run Oil-Natural Gas Price Relationship And The Shale Gas Revolution," "Marco Fanno" Working Papers 0198, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Pick Schen Yip & Robert Brooks & Hung Xuan Do & Duc Khuong Nguyen, 2019. "Dynamic Volatility Spillover Effect between Oil and Agricultural Products," Working Papers 2019-009, Department of Research, Ipag Business School.
    2. Scarcioffolo, Alexandre R. & Etienne, Xiaoli L., 2021. "Regime-switching energy price volatility: The role of economic policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 336-356.
    3. Chang, C-L. & McAleer, M.J. & Wang, Y., 2016. "Testing Co-Volatility Spillovers for Natural Gas Spot, Futures and ETF Spot using Dynamic Conditional Covariances," Econometric Institute Research Papers EI2016-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Wei, Zhaohao & Chai, Jian & Dong, Jichang & Lu, Quanying, 2022. "Understanding the linkage-dependence structure between oil and gas markets: A new perspective," Energy, Elsevier, vol. 257(C).
    5. Bouri, Elie & Lei, Xiaojie & Xu, Yahua & Zhang, Hongwei, 2023. "Connectedness in implied higher-order moments of precious metals and energy markets," Energy, Elsevier, vol. 263(PB).
    6. Tiwari, Aviral Kumar & Mukherjee, Zinnia & Gupta, Rangan & Balcilar, Mehmet, 2019. "A wavelet analysis of the relationship between oil and natural gas prices," Resources Policy, Elsevier, vol. 60(C), pages 118-124.
    7. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2018. "Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model," Ecological Economics, Elsevier, vol. 150(C), pages 315-339.
    8. Ivan Aleksandrovich Kopytin & Alexander Oskarovich Maslennikov & Stanislav Vyacheslavovich Zhukov, 2022. "Europe in World Natural Gas Market: International Transmission of European Price Shocks," International Journal of Energy Economics and Policy, Econjournals, vol. 12(3), pages 8-15, May.
    9. Nikitopoulos, Christina Sklibosios & Thomas, Alice Carole & Wang, Jianxin, 2023. "The economic impact of daily volatility persistence on energy markets," Journal of Commodity Markets, Elsevier, vol. 30(C).
    10. Lyócsa, Štefan & Molnár, Peter, 2018. "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, vol. 155(C), pages 462-473.
    11. Hafezi, Reza & Wood, David A. & Akhavan, Amir Naser & Pakseresht, Saeed, 2020. "Iran in the emerging global natural gas market: A scenario-based competitive analysis and policy assessment," Resources Policy, Elsevier, vol. 68(C).
    12. Yang, Haijun & Han, Xin & Wang, Li, 2021. "Is there a bubble in the shale gas market?," Energy, Elsevier, vol. 215(PA).
    13. Michael Weylandt & Yu Han & Katherine B. Ensor, 2019. "Multivariate Modeling of Natural Gas Spot Trading Hubs Incorporating Futures Market Realized Volatility," Papers 1907.10152, arXiv.org.
    14. Feng, Gen-Fu & Wang, Quan-Jing & Chu, Yin & Wen, Jun & Chang, Chun-Ping, 2021. "Does the shale gas boom change the natural gas price-production relationship? Evidence from the U.S. market," Energy Economics, Elsevier, vol. 93(C).
    15. Roberts, Gavin, 2019. "Revisiting the Drivers of Natural Gas Prices. A replication study of Brown & Yücel (The Energy Journal, 2008)," International Journal for Re-Views in Empirical Economics (IREE), ZBW - Leibniz Information Centre for Economics, vol. 3(2019-2), pages 1-24.
    16. Hou, Chenghan & Nguyen, Bao H., 2018. "Understanding the US natural gas market: A Markov switching VAR approach," Energy Economics, Elsevier, vol. 75(C), pages 42-53.
    17. Pablo Cansado-Bravo & Carlos Rodríguez-Monroy, 2018. "Persistence of Oil Prices in Gas Import Prices and the Resilience of the Oil-Indexation Mechanism. The Case of Spanish Gas Import Prices," Energies, MDPI, vol. 11(12), pages 1-17, December.
    18. Wang, Tiantian & Zhang, Dayong & Ji, Qiang & Shi, Xunpeng, 2020. "Market reforms and determinants of import natural gas prices in China," Energy, Elsevier, vol. 196(C).
    19. Mangirdas Morkunas & Gintaras Cernius & Gintare Giriuniene, 2019. "Assessing Business Risks of Natural Gas Trading Companies: Evidence from GET Baltic," Energies, MDPI, vol. 12(14), pages 1-14, July.
    20. Roberto Antonietti & Fulvio Fontini, 2018. "Does energy price affect energy efficiency? Cross-country panel evidence," SEEDS Working Papers 1218, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Oct 2018.
    21. Zhang, Dayong & Ji, Qiang, 2018. "Further evidence on the debate of oil-gas price decoupling: A long memory approach," Energy Policy, Elsevier, vol. 113(C), pages 68-75.
    22. Petre Caraiani & Adrian Cantemir Călin, 2019. "Monetary Policy Effects on Energy Sector Bubbles," Energies, MDPI, vol. 12(3), pages 1-13, February.
    23. Li, Boying & Zheng, Mingbo & Zhao, Xinxin & Chang, Chun-Ping, 2021. "An assessment of the effect of partisan ideology on shale gas production and the implications for environmental regulations," Economic Systems, Elsevier, vol. 45(3).
    24. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2021. "Forecasting natural gas prices using highly flexible time-varying parameter models," Economic Modelling, Elsevier, vol. 105(C).
    25. Hailemariam, Abebe & Smyth, Russell, 2019. "What drives volatility in natural gas prices?," Energy Economics, Elsevier, vol. 80(C), pages 731-742.
    26. Feng, Qianqian & Qiu, Nansheng & Borjigin, Tenger & Wu, Hang & Zhang, Jiatang & Shen, Baojian & Wang, Jiangshan, 2022. "Tectonic evolution revealed by thermo-kinematic and its effect on shale gas preservation," Energy, Elsevier, vol. 240(C).
    27. Zhang, Dayong & Shi, Min & Shi, Xunpeng, 2018. "Oil indexation, market fundamentals, and natural gas prices: An investigation of the Asian premium in natural gas trade," Energy Economics, Elsevier, vol. 69(C), pages 33-41.
    28. Miao, Xiaoyu & Wang, Qunwei & Dai, Xingyu, 2022. "Is oil-gas price decoupling happening in China? A multi-scale quantile-on-quantile approach," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 450-470.
    29. Zhang, Dayong & Wang, Tiantian & Shi, Xunpeng & Liu, Jia, 2018. "Is hub-based pricing a better choice than oil indexation for natural gas? Evidence from a multiple bubble test," Energy Economics, Elsevier, vol. 76(C), pages 495-503.
    30. Li, Raymond & Woo, Chi-Keung & Tishler, Asher & Zarnikau, Jay, 2022. "Price responsiveness of commercial demand for natural gas in the US," Energy, Elsevier, vol. 256(C).
    31. Solarin, Sakiru Adebola & Gil-Alana, Luis A. & Lafuente, Carmen, 2020. "An investigation of long range reliance on shale oil and shale gas production in the U.S. market," Energy, Elsevier, vol. 195(C).
    32. Kirat, Yassine, 2021. "The US shale gas revolution: An opportunity for the US manufacturing sector?," International Economics, Elsevier, vol. 167(C), pages 59-77.
    33. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2020. "Forecasting natural gas prices using highly flexible time-varying parameter models," Working Papers 2020-01, University of Tasmania, Tasmanian School of Business and Economics.
    34. Lee, Sunghoon & Kim, Jin-Kuk, 2020. "Process-integrated design of a sub-ambient membrane process for CO2 removal from natural gas power plants," Applied Energy, Elsevier, vol. 260(C).
    35. Yassine Kirat, 2021. "The US shale gas revolution: An opportunity for the US manufacturing sector?," Post-Print hal-03676616, HAL.
    36. Shi, Xunpeng & Shen, Yifan, 2021. "Macroeconomic uncertainty and natural gas prices: Revisiting the Asian Premium," Energy Economics, Elsevier, vol. 94(C).
    37. Salim Hamza Ringim & Abdulkareem Alhassan & Hasan Güngör & Festus Victor Bekun, 2022. "Economic Policy Uncertainty and Energy Prices: Empirical Evidence from Multivariate DCC-GARCH Models," Energies, MDPI, vol. 15(10), pages 1-18, May.
    38. Rubaszek, Michał & Uddin, Gazi Salah, 2020. "The role of underground storage in the dynamics of the US natural gas market: A threshold model analysis," Energy Economics, Elsevier, vol. 87(C).
    39. Ribeiro Scarcioffolo, Alexandre & Etienne, Xiaoli L., 2018. "Does Economic Policy Uncertainty Affect Energy Market Volatility and Vice-Versa?," 2018 Annual Meeting, August 5-7, Washington, D.C. 273976, Agricultural and Applied Economics Association.
    40. Li, Raymond & Woo, Chi-Keung & Tishler, Asher & Zarnikau, Jay, 2022. "How price responsive is industrial demand for natural gas in the United States?," Utilities Policy, Elsevier, vol. 74(C).

  18. Giovanni Bonaccolto & Massimiliano Caporin & Sandra Paterlini, 2015. "Asset Allocation Strategies Based on Penalized Quantile Regression," Papers 1507.00250, arXiv.org.

    Cited by:

    1. Michele Costola & Bertrand Maillet & Zhining Yuan & Xiang Zhang, 2024. "Mean-Variance Efficient Large Portfolios : A Simple Machine Learning Heuristic Technique based on the Two-Fund Separation Theorem," Post-Print hal-04514343, HAL.
    2. Giovanni Bonaccolto, 2021. "Quantile– based portfolios: post– model– selection estimation with alternative specifications," Computational Management Science, Springer, vol. 18(3), pages 355-383, July.
    3. Giovanni Bonaccolto, 2019. "Critical Decisions for Asset Allocation via Penalized Quantile Regression," Papers 1908.04697, arXiv.org.
    4. Sungchul Hong & Jong-June Jeon, 2023. "Uniform Pessimistic Risk and its Optimal Portfolio," Papers 2303.07158, arXiv.org, revised May 2024.
    5. Taras Bodnar & Mathias Lindholm & Erik Thorsén & Joanna Tyrcha, 2021. "Quantile-based optimal portfolio selection," Computational Management Science, Springer, vol. 18(3), pages 299-324, July.
    6. Taras Bodnar & Dmytro Ivasiuk & Nestor Parolya & Wolfgang Schmid, 2023. "Multi-period power utility optimization under stock return predictability," Computational Management Science, Springer, vol. 20(1), pages 1-27, December.
    7. De Gooijer Jan G. & Zerom Dawit, 2020. "Penalized Averaging of Parametric and Non-Parametric Quantile Forecasts," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.

  19. Giovanni Bonaccolto & Massimiliano Caporin & Rangan Gupta, 2015. "The Dynamic Impact of Uncertainty in Causing and Forecasting the Distribution of Oil Returns and Risk," Working Papers 201564, University of Pretoria, Department of Economics.

    Cited by:

    1. Shi, Chunpei & Wei, Yu & Li, Xiafei & Liu, Yuntong, 2023. "Combination forecasts of China's oil futures returns based on multiple uncertainties and their connectedness with oil," Energy Economics, Elsevier, vol. 126(C).
    2. Bos, Martijn & Demirer, Riza & Gupta, Rangan & Tiwari, Aviral Kumar, 2018. "Oil returns and volatility: The role of mergers and acquisitions," Energy Economics, Elsevier, vol. 71(C), pages 62-69.
    3. Mei, Dexiang & Zeng, Qing & Cao, Xiang & Diao, Xiaohua, 2019. "Uncertainty and oil volatility: New evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 155-163.
    4. Marfatia, Hardik A. & Gupta, Rangan & Cakan, Esin, 2021. "Dynamic impact of the U.S. monetary policy on oil market returns and volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 159-169.
    5. Mehmet Balcilar & Matteo Bonato & Riza Demirer & Rangan Gupta, 2016. "The Effect of Investor Sentiment on Gold Market Dynamics," Working Papers 201638, University of Pretoria, Department of Economics.
    6. Riza Demirer & Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2020. "Effect of Rare Disaster Risks on Crude Oil: Evidence from El Nino from Over 140 Years of Data," Working Papers 2020104, University of Pretoria, Department of Economics.
    7. Demirer, Riza & Gupta, Rangan & Suleman, Tahir & Wohar, Mark E., 2018. "Time-varying rare disaster risks, oil returns and volatility," Energy Economics, Elsevier, vol. 75(C), pages 239-248.
    8. Cao, Yan & Cheng, Sheng & Li, Xinran, 2023. "How economic policy uncertainty affects asymmetric spillovers in food and oil prices: Evidence from wavelet analysis," Resources Policy, Elsevier, vol. 86(PB).
    9. Balcilar, Mehmet & Gupta, Rangan & Wang, Shixuan & Wohar, Mark E., 2020. "Oil price uncertainty and movements in the US government bond risk premia," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    10. Rangan Gupta & Christian Pierdzioch, 2023. "Do U.S. economic conditions at the state level predict the realized volatility of oil-price returns? A quantile machine-learning approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
    11. Nonejad, Nima, 2021. "Predicting the return on the spot price of crude oil out-of-sample by conditioning on news-based uncertainty measures: Some new empirical results," Energy Economics, Elsevier, vol. 104(C).
    12. Syed Jawad Hussain Shahzad & Rangan Gupta & Riza Demirer & Christian Pierdzioch, 2022. "Oil shocks and directional predictability of macroeconomic uncertainties of developed economies: Evidence from high‐frequency data†," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(2), pages 169-185, May.
    13. Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2015. "On Exchange-Rate Movements and Gold-Price Fluctuations: Evidence for Gold-Producing Countries from a Nonparametric Causality-in-Quantiles Test," Working Papers 201598, University of Pretoria, Department of Economics.
    14. Mehmet Balcilar & Rangan Gupta & Clement Kyei, 2018. "Predicting Stock Returns And Volatility With Investor Sentiment Indices: A Reconsideration Using A Nonparametric Causality†In†Quantiles Test," Bulletin of Economic Research, Wiley Blackwell, vol. 70(1), pages 74-87, January.
    15. Zhang, Yue-Jun & Yan, Xing-Xing, 2020. "The impact of US economic policy uncertainty on WTI crude oil returns in different time and frequency domains," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 750-768.
    16. Hasan, Md. Bokhtiar & Kabir Hassan, M. & Gider, Zeynullah & Tahsin Rafia, Humaira & Rashid, Mamunur, 2023. "Searching hedging instruments against diverse global risks and uncertainties," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    17. Balcilar, Mehmet & Gupta, Rangan & Sousa, Ricardo M. & Wohar, Mark E., 2017. "Do cay and cayMS predict stock and housing returns? Evidence from a nonparametric causality test," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 269-279.
    18. Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers," Working Papers 202135, University of Pretoria, Department of Economics.
    19. Rangan Gupta & Hardik A. Marfatia & Eric Olson, 2019. "Effect of Uncertainty on U.S. Stock Returns and Volatility: Evidence from Over Eighty Years of High-Frequency Data," Working Papers 201942, University of Pretoria, Department of Economics.
    20. Çepni, Oğuzhan & Gupta, Rangan & Pienaar, Daniel & Pierdzioch, Christian, 2022. "Forecasting the realized variance of oil-price returns using machine learning: Is there a role for U.S. state-level uncertainty?," Energy Economics, Elsevier, vol. 114(C).
    21. Balcilar, Mehmet & Gupta, Rangan & Sousa, Ricardo M. & Wohar, Mark E., 2021. "Linking U.S. State-level housing market returns, and the consumption-(Dis)Aggregate wealth ratio," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 779-810.
    22. Elie Bouri & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2020. "Infectious Diseases, Market Uncertainty and Oil Market Volatility," Energies, MDPI, vol. 13(16), pages 1-8, August.
    23. Yin, Libo & Wang, Yang, 2019. "Forecasting the oil prices: What is the role of skewness risk?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    24. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    25. Wen, Jun & Zhao, Xin-Xin & Chang, Chun-Ping, 2021. "The impact of extreme events on energy price risk," Energy Economics, Elsevier, vol. 99(C).
    26. Rangan Gupta & Tahir Suleman & Mark E. Wohar, 2019. "The role of time‐varying rare disaster risks in predicting bond returns and volatility," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 327-340, July.
    27. Chang, Tsangyao & Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian, 2019. "Predicting stock market movements with a time-varying consumption-aggregate wealth ratio," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 458-467.
    28. Demirer, Riza & Gupta, Rangan & Pierdzioch, Christian & Shahzad, Syed Jawad Hussain, 2020. "The predictive power of oil price shocks on realized volatility of oil: A note," Resources Policy, Elsevier, vol. 69(C).
    29. Walid Bahloul & Mehmet Balcilar & Juncal Cunado & Rangan Gupta, 2017. "The Role of Economic and Financial Uncertainties in Predicting Commodity Futures Returns and Volatility: Evidence from a Nonparametric Causality-in-Quantiles Test," Working Papers 201725, University of Pretoria, Department of Economics.
    30. Mehmet Balcilar & Esin Cakan & Rangan Gupta, 2016. "Does U.S. News Impact Asian Emerging Markets? Evidence from Nonparametric Causality-in-Quantiles Test," Working Papers 201631, University of Pretoria, Department of Economics.
    31. 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.
    32. Balcilar, Mehmet & Gupta, Rangan & Kim, Won Joong & Kyei, Clement, 2019. "The role of economic policy uncertainties in predicting stock returns and their volatility for Hong Kong, Malaysia and South Korea," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 150-163.
    33. Rangan Gupta & Chi Keung Marco Lau & Wendy Nyakabawo, 2018. "Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment," Working Papers 201866, University of Pretoria, Department of Economics.
    34. Yang, Kun & Wei, Yu & Li, Shouwei & Liu, Liang & Wang, Lei, 2021. "Global financial uncertainties and China’s crude oil futures market: Evidence from interday and intraday price dynamics," Energy Economics, Elsevier, vol. 96(C).
    35. Sheng Cheng & Wei Liu & Qisheng Jiang & Yan Cao, 2023. "Multi–Scale Risk Connectedness Between Economic Policy Uncertainty of China and Global Oil Prices in Time–Frequency Domains," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1593-1616, April.

  20. Massimiliano Caporin & Rangan Gupta, 2014. "Time-Varying Persistence in US Inflation," Working Papers 201457, University of Pretoria, Department of Economics.

    Cited by:

    1. Zhanshou Chen & Yanting Xiao & Fuxiao Li, 2021. "Monitoring memory parameter change-points in long-memory time series," Empirical Economics, Springer, vol. 60(5), pages 2365-2389, May.
    2. Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2016. "Time-Varying Persistence of Inflation: Evidence from a Wavelet-based Approach," Working papers 2016-09, University of Connecticut, Department of Economics.
    3. Hamidreza Ghorbani Dastgerdi, 2020. "Inflation Theories and Inflation Persistence in Iran," Zagreb International Review of Economics and Business, Faculty of Economics and Business, University of Zagreb, vol. 23(2), pages 1-20, November.
    4. Canepa, Alessandra, 2024. "Inflation dynamics and persistence: The importance of the uncertainty channel," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    5. Christou, Christina & Gupta, Rangan & Nyakabawo, Wendy & Wohar, Mark E., 2018. "Do house prices hedge inflation in the US? A quantile cointegration approach," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 15-26.
    6. Wingert, Simon & Mboya, Mwasi Paza & Sibbertsen, Philipp, 2020. "Distinguishing between breaks in the mean and breaks in persistence under long memory," Economics Letters, Elsevier, vol. 193(C).

  21. Massimiliano Caporin & Aleksey Kolokolov & Roberto RenoÕ, 2014. "Multi-jumps," "Marco Fanno" Working Papers 0185, Dipartimento di Scienze Economiche "Marco Fanno".
    • Caporin, Massimiliano & Kolokolov, Aleksey & Renò, Roberto, 2014. "Multi-jumps," MPRA Paper 58175, University Library of Munich, Germany.

    Cited by:

    1. Laurini, Márcio Poletti & Mauad, Roberto Baltieri, 2015. "A common jump factor stochastic volatility model," Finance Research Letters, Elsevier, vol. 12(C), pages 2-10.

  22. Massimiliano Caporin & Luca Corazzini & Michele Costola, 2014. "Measuring the Behavioral Component of Financial Fluctuations: An Analysis Based on the S&P 500," CREATES Research Papers 2014-33, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Michele Costola & Massimiliano Caporin, 2016. "Rational Learning For Risk-Averse Investors By Conditioning On Behavioral Choices," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-26, March.
    2. Olkhov, Victor, 2018. "Expectations, Price Fluctuations and Lorenz Attractor," MPRA Paper 89105, University Library of Munich, Germany.
    3. Olkhov, Victor, 2019. "New essentials of economic theory II. Economic transactions, expectations and asset pricing," MPRA Paper 93428, University Library of Munich, Germany.

  23. 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.

    Cited by:

    1. Swasti R. Khuntia & Jose L. Rueda & Mart A.M.M. Van der Meijden, 2018. "Long-Term Electricity Load Forecasting Considering Volatility Using Multiplicative Error Model," Energies, MDPI, vol. 11(12), pages 1-19, November.
    2. Andrea Barletta & Paolo Santucci de Magistris & Francesco Violante, 2016. "Retrieving Risk-Neutral Densities Embedded in VIX Options: a Non-Structural Approach," CREATES Research Papers 2016-20, Department of Economics and Business Economics, Aarhus University.
    3. Lien, Donald & Lee, Geul & Yang, Li & Zhang, Yuyin, 2018. "Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 187-201.
    4. Barletta, Andrea & Santucci de Magistris, Paolo & Violante, Francesco, 2019. "A non-structural investigation of VIX risk neutral density," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 1-20.
    5. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    6. Giampiero M. Gallo & Edoardo Otranto, 2016. "Combining Markov Switching and Smooth Transition in Modeling Volatility: A Fuzzy Regime MEM," Econometrics Working Papers Archive 2016_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    7. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.

  24. Caporin, Massimiliano & Fontini, Fulvio, 2014. "The Value of Protecting Venice from the Acqua Alta Phenomenon under Different Local Sea Level Rises," MPRA Paper 53779, University Library of Munich, Germany.

    Cited by:

    1. Paunić, Alida, 2016. "Brazil, Preservation of Forest and Biodiversity," MPRA Paper 71462, University Library of Munich, Germany.

  25. Massimiliano Caporin & Grégory M. Jannin & Francesco Lisi & Bertrand Maillet, 2014. "A Survey on the Four Families of Performance Measures," Post-Print hal-01243416, HAL.

    Cited by:

    1. Massimiliano Caporin & Michele Costola & Gregory Mathieu Jannin & Bertrand Maillet, 2016. "On the (Ab)Use of Omega?," Working Papers hal-01697640, HAL.
    2. Giovanni Bonaccolto & Massimiliano Caporin & Sandra Paterlini, 2015. "Asset Allocation Strategies Based On Penalized Quantile Regression," "Marco Fanno" Working Papers 0199, Dipartimento di Scienze Economiche "Marco Fanno".
    3. Hamidi, Benjamin & Maillet, Bertrand & Prigent, Jean-Luc, 2014. "A dynamic autoregressive expectile for time-invariant portfolio protection strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 46(C), pages 1-29.
    4. León, Angel & Navarro, Lluís & Nieto, Belén, 2019. "Screening rules and portfolio performance," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 642-662.
    5. Caporin, Massimiliano & Lisi, Francesco, 2013. "A Conditional Single Index model with Local Covariates for detecting and evaluating active portfolio management," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 236-249.
    6. Niu, Cuizhen & Wong, Wing-Keung & Zhu, Lixing, 2017. "Farinelli and Tibiletti ratio and Stochastic Dominance," MPRA Paper 82737, University Library of Munich, Germany.
    7. Voelzke, Jan, 2015. "Weakening the Gain–Loss-Ratio measure to make it stronger," Finance Research Letters, Elsevier, vol. 12(C), pages 58-66.
    8. Kristiaan Kerstens & Paolo Mazza & Tiantian Ren & Ignace van de Woestyne, 2022. "Multi-Time and Multi-Moment Nonparametric Frontier-Based Fund Rating: Proposal and Buy-and-Hold Backtesting Strategy," Post-Print hal-03833261, HAL.
    9. Carole Bernard & Massimiliano Caporin & Bertrand Maillet & Xiang Zhang, 2023. "Omega Compatibility: A Meta-analysis," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 493-526, August.
    10. Sally G. Arcidiacono & Damiano Rossello, 2022. "A hybrid approach to the discrepancy in financial performance’s robustness," Operational Research, Springer, vol. 22(5), pages 5441-5476, November.
    11. Abdelbari El Khamlichi & Thi Hong Van Hoang & Wing‐keung Wong, 2016. "Is Gold Different for Islamic and Conventional Portfolios? A Sectorial Analysis," Post-Print hal-02964594, HAL.
    12. León, Ángel & Moreno, Manuel, 2015. "Lower Partial Moments under Gram Charlier Distribution: Performance Measures and Efficient Frontiers," QM&ET Working Papers 15-3, University of Alicante, D. Quantitative Methods and Economic Theory.
    13. Monica Billio & Massimiliano Caporin & Michele Costola, 2012. "Backward/forward optimal combination of performance measures for equity screening," Working Papers 2012_13, Department of Economics, University of Venice "Ca' Foscari".
    14. Andrey Leonidov & Ilya Tipunin & Ekaterina Serebryannikova, 2020. "On Evaluation of Risky Investment Projects. Investment Certainty Equivalence," Papers 2005.12173, arXiv.org.
    15. Philippe Bernard & Najat El Mekkaoui de Freitas & Bertrand Maillet, 2022. "A Financial Fraud Detection Indicator for Investors: An IDeA," Post-Print hal-02312401, HAL.
    16. Fischer, Thomas & Lundtofte , Frederik, 2018. "Unequal Returns: Using the Atkinson Index to Measure Financial Risk," Working Papers 2018:25, Lund University, Department of Economics.
    17. Lu, Jin-Ray & Li, Xiu-Yan, 2021. "Identifying the fair value of Sharpe ratio by an option valuation approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 63-70.
    18. Thi-Hong-Van Hoang & Wing-Keung Wong & Zhenzhen Zhu, 2015. "Is gold different for risk-averse and risk-seeking investors? An empirical analysis of the Shanghai Gold Exchange," Post-Print hal-02010732, HAL.
    19. Monica Billio & Bertrand Maillet & Loriana Pelizzon, 2021. "A meta-measure of performance related to both investors and investments characteristics," Post-Print hal-03543398, HAL.
    20. Caporin, Massimiliano & Jimenez-Martin, Juan-Angel & Gonzalez-Serrano, Lydia, 2014. "Currency hedging strategies in strategic benchmarks and the global and Euro sovereign financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 159-177.
    21. Korn, Olaf & Möller, Philipp M. & Schwehm, Christian, 2019. "Drawdown measures: Are they all the same?," CFR Working Papers 19-04, University of Cologne, Centre for Financial Research (CFR).
    22. Dipankar Mondal & N. Selvaraju, 2020. "Upside Beta Ratio: A Performance Measure For Potential-Seeking Investors," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 1-26, April.
    23. Aytaç, Beysül & Hoang, Thi-Hong-Van & Mandou, Cyrille, 2016. "Wine: To drink or invest in? A study of wine as an investment asset in French portfolios," Research in International Business and Finance, Elsevier, vol. 36(C), pages 591-614.
    24. Amélie Charles & Olivier Darné & Jessica Fouilloux, 2016. "The impact of screening strategies on the performance of ESG indices," Working Papers hal-01344699, HAL.
    25. Potrykus Marcin, 2018. "Comparison of Investment Performance Measures Using the Example of Selected Stock Exchanges," Financial Sciences. Nauki o Finansach, Sciendo, vol. 23(2), pages 30-46, June.
    26. León, Angel & Moreno, Manuel, 2017. "One-sided performance measures under Gram-Charlier distributions," Journal of Banking & Finance, Elsevier, vol. 74(C), pages 38-50.
    27. Jan Voelzke, 2014. "Weakening the Gain-Loss-Ratio measure to make it stronger," CQE Working Papers 3114, Center for Quantitative Economics (CQE), University of Muenster.
    28. Bernard, Carole & Vanduffel, Steven & Ye, Jiang, 2019. "Optimal strategies under Omega ratio," European Journal of Operational Research, Elsevier, vol. 275(2), pages 755-767.
    29. Peyman Alipour & Ali Foroush Bastani, 2023. "Value-at-Risk-Based Portfolio Insurance: Performance Evaluation and Benchmarking Against CPPI in a Markov-Modulated Regime-Switching Market," Papers 2305.12539, arXiv.org.
    30. Anna E. Olkova, 2017. "Mutual Funds Performance Assessment Techniques: Comparative Analysis," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 3, pages 85-95, June.
    31. Elisa Pagani, 2015. "Certainty Equivalent: Many Meanings of a Mean," Working Papers 24/2015, University of Verona, Department of Economics.

  26. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2014. "Precious Metals Under the Microscope: A High-Frequency Analysis," Working Papers on Finance 1409, University of St. Gallen, School of Finance.

    Cited by:

    1. R. G. Alcoforado & W. Bernardino & A. D. Eg'idio dos Reis & J. A. C. Santos, 2021. "Modelling risk for commodities in Brazil: An application to live cattle spot and futures prices," Papers 2107.07556, arXiv.org.
    2. Gradojevic, Nikola & Erdemlioglu, Deniz & Gençay, Ramazan, 2020. "A new wavelet-based ultra-high-frequency analysis of triangular currency arbitrage," Economic Modelling, Elsevier, vol. 85(C), pages 57-73.
    3. Guglielmo Maria Caporale & Alex Plastun, 2021. "Gold and oil prices: abnormal returns, momentum and contrarian effects," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 353-368, September.
    4. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
    5. He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2017. "Price forecasting in the precious metal market: A multivariate EMD denoising approach," Resources Policy, Elsevier, vol. 54(C), pages 9-24.
    6. Renata G. Alcoforado & Alfredo D. Egídio dos Reis & Wilton Bernardino & José António C. Santos, 2023. "Modelling Risk for Commodities in Brazil: An Application for Live Cattle Spot and Futures Prices," Commodities, MDPI, vol. 2(4), pages 1-19, November.
    7. Jonathan Batten & Brian Lucey & Frank McGroarty & Maurice Peat & Andrew Urquhart, 2017. "Stylized facts of intraday precious metals," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-21, April.
    8. Štefan Lyócsa & Peter Molnár, 2016. "Volatility forecasting of strategically linked commodity ETFs: gold-silver," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1809-1822, December.
    9. Bao, Dun, 2020. "Dynamics and correlation of platinum-group metals spot prices," Resources Policy, Elsevier, vol. 68(C).
    10. Su, Chi-Wei & Wang, Xiao-Qing & Zhu, Haotian & Tao, Ran & Moldovan, Nicoleta-Claudia & Lobonţ, Oana-Ramona, 2020. "Testing for multiple bubbles in the copper price: Periodically collapsing behavior," Resources Policy, Elsevier, vol. 65(C).
    11. Joel Verghese & Phaik Nie Chin, 2022. "Factors affecting investors’ intention to purchase gold and silver bullion: evidence from Malaysia," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 27(1), pages 41-51, March.
    12. Vigne, Samuel A. & Lucey, Brian M. & O’Connor, Fergal A. & Yarovaya, Larisa, 2017. "The financial economics of white precious metals — A survey," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 292-308.
    13. Zhang, Hanxiong & Auer, Benjamin R. & Vortelinos, Dimitrios I., 2018. "Performance ranking (dis)similarities in commodity markets," Global Finance Journal, Elsevier, vol. 35(C), pages 115-137.
    14. He, Kaijian & Liu, Youjin & Yu, Lean & Lai, Kin Keung, 2016. "Multiscale dependence analysis and portfolio risk modeling for precious metal markets," Resources Policy, Elsevier, vol. 50(C), pages 224-233.
    15. Kentaro Iwatsubo & Clinton Watkins, 2022. "Causality between Arbitrage and Liquidity in Platinum Futures," JRFM, MDPI, vol. 15(12), pages 1-17, December.

  27. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Volatility jumps and their economic determinants," CREATES Research Papers 2014-27, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Mawuli Segnon & Rangan Gupta & Bernd Wilfling, 2022. "Forecasting Stock Market Volatility with Regime-Switching GARCH-MIDAS: The Role of Geopolitical Risks," Working Papers 202203, University of Pretoria, Department of Economics.
    2. Mehmet Balcilar & Elie Bouri & Rangan Gupta & Christian Pierdzioch, 2021. "El Nino, La Nina, and the Forecastability of the Realized Variance of Heating Oil Price Movements," Working Papers 202138, University of Pretoria, Department of Economics.
    3. Gloria Gonzalez-Rivera & Joao Henrique Mazzeu & Esther Ruiz & Helena Veiga, 2017. "A Bootstrap Approach for Generalized Autocontour Testing. Implications for VIX Forecast Densities," Working Papers 201709, University of California at Riverside, Department of Economics.
    4. Jan Hanousek & Evžen Kočenda & Jan Novotný, 2016. "Shluková analýza skoků na kapitálových trzích [Cluster Analysis of Jumps on Capital Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2016(2), pages 127-144.
    5. Selmi, Refk & Bouoiyour, Jamal & Miftah, Amal & Wohar, Mark E., 2021. "Managing exposure to volatile oil prices: Evidence from U.S. sectoral and industry-level data," Resources Policy, Elsevier, vol. 73(C).
    6. Marfatia, Hardik A. & Gupta, Rangan & Cakan, Esin, 2021. "Dynamic impact of the U.S. monetary policy on oil market returns and volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 159-169.
    7. Rangan Gupta & Chi Keung Marco Lau & Seong-Min Yoon, 2017. "OPEC News Announcement Effect on Volatility in the Crude Oil Market: A Reconsideration," Working Papers 201754, University of Pretoria, Department of Economics.
    8. Gonçalves Mazzeu, Joao Henrique & González-Rivera, Gloria & Ruiz Ortega, Esther & Veiga, Helena, 2016. "A Bootstrap Approach for Generalized Autocontour Testing," DES - Working Papers. Statistics and Econometrics. WS 23457, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Gkillas, Konstantinos & Gupta, Rangan & Wohar, Mark E., 2018. "Volatility jumps: The role of geopolitical risks," Finance Research Letters, Elsevier, vol. 27(C), pages 247-258.
    10. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.
    11. Konstantinos Gkillas & Rangan Gupta & Mark E. Wohar, 2020. "Oil shocks and volatility jumps," Review of Quantitative Finance and Accounting, Springer, vol. 54(1), pages 247-272, January.
    12. Bonato, Matteo & Gupta, Rangan & Lau, Chi Keung Marco & Wang, Shixuan, 2020. "Moments-based spillovers across gold and oil markets," Energy Economics, Elsevier, vol. 89(C).
    13. Konstantinos Gkillas & Rangan Gupta & Chi Keung Marco Lau & Tahir Suleman, 2018. "Jumps Beyond the Realms of Cricket: India’s Performance in One Day Internationals and Stock Market Movements," Working Papers 201871, University of Pretoria, Department of Economics.
    14. Marfatia, Hardik A. & Gupta, Rangan & Miller, Stephen, 2020. "125 ​Years of time-varying effects of fiscal policy on financial markets," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 303-320.
    15. Stefano Lovo & Philippe Raimbourg & Federica Salvadè, 2022. "Credit rating agencies, information asymmetry and US bond liquidity," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(9-10), pages 1863-1896, October.
    16. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian & Yoon, Seong-Min, 2021. "OPEC news and jumps in the oil market," Energy Economics, Elsevier, vol. 96(C).
    17. Rangan Gupta & Tahir Suleman & Mark E. Wohar, 2019. "The role of time‐varying rare disaster risks in predicting bond returns and volatility," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 327-340, July.
    18. Hardik A. Marfatia & Rangan Gupta & Stephen M. Miller, 2020. "125 Years of Time-Varying Effects of Fiscal Policy on Financial Markets," Working papers 2020-12, University of Connecticut, Department of Economics.
    19. Giampiero M. Gallo & Edoardo Otranto, 2016. "Combining Markov Switching and Smooth Transition in Modeling Volatility: A Fuzzy Regime MEM," Econometrics Working Papers Archive 2016_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    20. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2022. "A moving average heterogeneous autoregressive model for forecasting the realized volatility of the US stock market: Evidence from over a century of data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 384-400, January.
    21. 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.
    22. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Clement Kyei, 2019. "Monetary Policy Uncertainty and Volatility Jumps in Advanced Equity Markets," Working Papers 201939, University of Pretoria, Department of Economics.
    23. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    24. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2018. "Forecasting (Good and Bad) Realized Exchange-Rate Volatility: Is there a Role for Realized Skewness and Kurtosis?," Working Papers 201879, University of Pretoria, Department of Economics.
    25. Thaddeus Neururer, 2020. "Past managerial guidance and returns to variance trading around earnings announcements," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(3), pages 2995-3031, September.
    26. Kam F. Chan & Philip Gray, 2018. "Volatility jumps and macroeconomic news announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(8), pages 881-897, August.

  28. Fulvio Baldovin & Massimiliano Caporin & Michele Caraglio & Attilio Stella & Marco Zamparo, 2013. "Option pricing with non-Gaussian scaling and infinite-state switching volatility," Papers 1307.6322, arXiv.org, revised May 2014.

    Cited by:

    1. Wang, Xiao-Tian & Li, Zhe & Zhuang, Le, 2017. "Risk preference, option pricing and portfolio hedging with proportional transaction costs," Chaos, Solitons & Fractals, Elsevier, vol. 95(C), pages 111-130.
    2. Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
    3. Chang, C-L. & McAleer, M.J., 2014. "Econometric Analysis of Financial Derivatives," Econometric Institute Research Papers EI 2015-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  29. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About the Dynamic Conditional Correlation Representation," Working Papers in Economics 13/21, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Chia-Lin Chang & Hui-Kuang Hsu & Michael McAleer, 2014. "A Tourism Conditions Index," Documentos de Trabajo del ICAE 2014-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "Connecting VIX and Stock Index ETF," Tinbergen Institute Discussion Papers 16-010/III, Tinbergen Institute, revised 23 Jan 2017.
    3. Chia-Lin Chang & Yiying Li & Michael McAleer, 2015. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Tinbergen Institute Discussion Papers 15-077/III, Tinbergen Institute.
    4. Christian M. Hafner & Michael McAleer, 2014. "A One Line Derivation of DCC: Application of a Vector Random Coefficient Moving Average Process," Documentos de Trabajo del ICAE 2014-29, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    5. Morana, Claudio, 2019. "Regularized semiparametric estimation of high dimensional dynamic conditional covariance matrices," Econometrics and Statistics, Elsevier, vol. 12(C), pages 42-65.
    6. Martin T. Bohl, Badye Essid, Pierre Siklos, 2018. "Short-Selling Bans and the Global Financial Crisis: Are they Inter-Connected?," LCERPA Working Papers 0112, Laurier Centre for Economic Research and Policy Analysis, revised 30 Jan 2018.
    7. Chia-Lin Chang & Michael McAleer & Jiarong Tian, 2019. "Modeling and Testing Volatility Spillovers in Oil and Financial Markets for the USA, the UK, and China," Energies, MDPI, vol. 12(8), pages 1-24, April.
    8. Jiti Gao & Bin Peng & Wei Biao Wu & Yayi Yan, 2022. "Time-Varying Multivariate Causal Processes," Monash Econometrics and Business Statistics Working Papers 8/22, Monash University, Department of Econometrics and Business Statistics.
    9. Klein, Tony, 2018. "Trends and Contagion in WTI and Brent Crude Oil Spot and Futures Markets - The Role of OPEC in the last Decade," QBS Working Paper Series 2018/05, Queen's University Belfast, Queen's Business School.
    10. Gao, Jiti & Peng, Bin & Wu, Wei Biao & Yan, Yayi, 2024. "Time-varying multivariate causal processes," Journal of Econometrics, Elsevier, vol. 240(1).
    11. Irene Henriques & Perry Sadorsky, 2018. "Can Bitcoin Replace Gold in an Investment Portfolio?," JRFM, MDPI, vol. 11(3), pages 1-19, August.
    12. Asai, M. & Caporin, M. & McAleer, M.J., 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Econometric Institute Research Papers EI 2012-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Chang, C-L. & Hsieh, T-L. & McAleer, M.J., 2018. "Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK," Econometric Institute Research Papers EI2018-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Perego, Erica R. & Vermeulen, Wessel N., 2016. "Macro-economic determinants of European stock and government bond correlations: A tale of two regions," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 214-232.
    15. Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2016. "Causes and hazards of the euro area sovereign debt crisis: Pure and fundamentals-based contagion," Economic Modelling, Elsevier, vol. 56(C), pages 133-147.
    16. Vendrame, Vasco & Guermat, Cherif & Tucker, Jon, 2023. "A conditional higher-moment CAPM," International Review of Financial Analysis, Elsevier, vol. 86(C).
    17. Ahmed Ayadi & Marjène Gana & Stéphane Goutte & Khaled Guesmi, 2021. "Equity-Commodity Contagion During Four Recent Crises: Evidence from the USA, Europe and the BRICS," Working Papers halshs-03169699, HAL.
    18. Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
    19. Bram Daelemans & Joseph P. Daniels & Farrokh Nourzad, 2018. "Free Trade Agreements and Volatility of Stock Returns and Exchange Rates: Evidence from NAFTA," Open Economies Review, Springer, vol. 29(1), pages 141-163, February.
    20. Iwatsubo, Kentaro & Watkins, Clinton, 2021. "The changing role of foreign investors in Tokyo stock price formation," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    21. Nathan Lael Joseph & Thi Thuy Anh Vo & Asma Mobarek & Sabur Mollah, 2020. "Volatility and asymmetric dependence in Central and East European stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 55(4), pages 1241-1303, November.
    22. Michael McAleer, 2019. "What They Did Not Tell You about Algebraic (Non-) Existence, Mathematical (IR-)Regularity, and (Non-) Asymptotic Properties of the Dynamic Conditional Correlation (DCC) Model," JRFM, MDPI, vol. 12(2), pages 1-9, April.
    23. 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).
    24. Tsukuda, Yoshihiko & Shimada, Junji & Miyakoshi, Tatsuyoshi, 2017. "Bond market integration in East Asia: Multivariate GARCH with dynamic conditional correlations approach," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 193-213.
    25. Michael mcAleer, 2017. "Stationarity and Invertibility of a Dynamic Correlation Matrix," Tinbergen Institute Discussion Papers 17-082/III, Tinbergen Institute.
    26. Chia-Lin Chang & Michael McAleer & Chia-Ping Liu, 2016. "Volatility spillovers for spot, futures, and ETF prices in energy and agriculture," Documentos de Trabajo del ICAE 2016-11, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    27. Pan, Zhiyuan & Wang, Yudong & Yang, Li, 2014. "Hedging crude oil using refined product: A regime switching asymmetric DCC approach," Energy Economics, Elsevier, vol. 46(C), pages 472-484.
    28. Zhang, Qi & Di, Peng & Farnoosh, Arash, 2021. "Study on the impacts of Shanghai crude oil futures on global oil market and oil industry based on VECM and DAG models," Energy, Elsevier, vol. 223(C).
    29. García Ruiz, Reyna Susana & López Herrera, Francisco & Cruz Aké, Salvador, 2018. "Determinantes del crédito y la morosidad en México / Determinants of credit and defaulting in Mexico," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 8(1), pages 85-104, enero-jun.
    30. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    31. Nikolay Gospodinov, 2017. "Asset Co-movements: Features and Challenges," FRB Atlanta Working Paper 2017-11, Federal Reserve Bank of Atlanta.
    32. Raúl de Jesús-Gutiérrez, 2019. "Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 11(2), pages 353-374, November.
    33. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "How are VIX and Stock Index ETF Related?," Documentos de Trabajo del ICAE 2016-02, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    34. Zhang, Yongli & Rolling, Craig & Yang, Yuhong, 2021. "Estimating and forecasting dynamic correlation matrices: A nonlinear common factor approach," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    35. Jean-David Fermanian & Hassan Malongo, 2013. "On the Stationarity of Dynamic Conditional Correlation Models," Working Papers 2013-26, Center for Research in Economics and Statistics.
    36. Hussain, Saiful Izzuan & Nur-Firyal, R. & Ruza, Nadiah, 2022. "Linkage transitions between oil and the stock markets of countries with the highest COVID-19 cases," Journal of Commodity Markets, Elsevier, vol. 28(C).
    37. Graham Bird & Wenti Du & Eric Pentecost & Thomas Willett, 2017. "Was it different the second time? An empirical analysis of contagion during the crises in Greece 2009–15," The World Economy, Wiley Blackwell, vol. 40(12), pages 2530-2542, December.
    38. Katsiampa, Paraskevi, 2019. "An empirical investigation of volatility dynamics in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 50(C), pages 322-335.
    39. Fantazzini, Dean & Zimin, Stephan, 2019. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," MPRA Paper 95988, University Library of Munich, Germany.
    40. Hou, Yang (Greg) & Li, Steven, 2020. "Volatility and skewness spillover between stock index and stock index futures markets during a crash period: New evidence from China," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 166-188.
    41. Katsiampa, Paraskevi & Yarovaya, Larisa & Zięba, Damian, 2022. "High-frequency connectedness between Bitcoin and other top-traded crypto assets during the COVID-19 crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    42. Cui, Jinxin & Goh, Mark & Li, Binlin & Zou, Huiwen, 2021. "Dynamic dependence and risk connectedness among oil and stock markets: New evidence from time-frequency domain perspectives," Energy, Elsevier, vol. 216(C).
    43. Tsouknidis, Dimitris A., 2016. "Dynamic volatility spillovers across shipping freight markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 90-111.
    44. Benjamin Poignard & Jean-Davis Fermanian, 2014. "Dynamic Asset Correlations Based on Vines," Working Papers 2014-46, Center for Research in Economics and Statistics.
    45. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    46. Mehmet Balcilar & Riza Demirer & Rangan Gupta, 2017. "Do Sustainable Stocks Offer Diversification Benefits for Conventional Portfolios? An Empirical Analysis of Risk Spillovers and Dynamic Correlations," Sustainability, MDPI, vol. 9(10), pages 1-18, October.
    47. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    48. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    49. Jean-David Fermanian & Hassan Malongo, 2014. "On the stationarity of Dynamic Conditional Correlation models," Papers 1405.6905, arXiv.org, revised Mar 2016.
    50. Zhicheng Liang & Junwei Wang & Kin Keung Lai, 2020. "Dependence Structure Analysis and VaR Estimation Based on China’s and International Gold Price: A Copula Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 169-193, February.
    51. Jilber Urbina & Miguel Santolino & Montserrat Guillen, 2021. "Covariance Principle for Capital Allocation: A Time-Varying Approach," Mathematics, MDPI, vol. 9(16), pages 1-13, August.
    52. Hasan Murat Ertuğrul & Ünal Seven, 2023. "Dynamic spillover analysis of international and Turkish food prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1918-1928, April.
    53. Yıldırım, Durmuş Çağrı & Esen, Ömer & Ertuğrul, Hasan Murat, 2022. "Impact of the COVID-19 pandemic on return and risk transmission between oil and precious metals: Evidence from DCC-GARCH model," Resources Policy, Elsevier, vol. 79(C).
    54. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    55. Takashi Isogai, 2015. "An Empirical Study of the Dynamic Correlation of Japanese Stock Returns," Bank of Japan Working Paper Series 15-E-7, Bank of Japan.
    56. Domingo Rodríguez Benavides & Ignacio Perrotini Hernández, 2019. "Las correlaciones dinámicas de contagio financiero:Estados Unidos y América Latina," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(2), pages 151-168, Abril-Jun.
    57. Saker Sabkha & Christian de Peretti, 2022. "On the performances of Dynamic Conditional Correlation models in the Sovereign CDS market and the corresponding bond market," Post-Print hal-01710398, HAL.
    58. Klein, Tony, 2018. "Trends and contagion in WTI and Brent crude oil spot and futures markets - The role of OPEC in the last decade," Energy Economics, Elsevier, vol. 75(C), pages 636-646.
    59. Piao, Xiaorui & Mei, Bin & Xue, Yuan, 2016. "Comparing the financial performance of timber REITs and other REITs," Forest Policy and Economics, Elsevier, vol. 72(C), pages 115-121.

  30. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About DCC," Working Papers in Economics 13/16, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Chia-Lin Chang & Hui-Kuang Hsu & Michael McAleer, 2014. "A Tourism Conditions Index," Documentos de Trabajo del ICAE 2014-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "Connecting VIX and Stock Index ETF," Tinbergen Institute Discussion Papers 16-010/III, Tinbergen Institute, revised 23 Jan 2017.
    3. Chia-Lin Chang & Yiying Li & Michael McAleer, 2015. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Tinbergen Institute Discussion Papers 15-077/III, Tinbergen Institute.
    4. Christian M. Hafner & Michael McAleer, 2014. "A One Line Derivation of DCC: Application of a Vector Random Coefficient Moving Average Process," Documentos de Trabajo del ICAE 2014-29, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    5. Morana, Claudio, 2019. "Regularized semiparametric estimation of high dimensional dynamic conditional covariance matrices," Econometrics and Statistics, Elsevier, vol. 12(C), pages 42-65.
    6. Martin T. Bohl, Badye Essid, Pierre Siklos, 2018. "Short-Selling Bans and the Global Financial Crisis: Are they Inter-Connected?," LCERPA Working Papers 0112, Laurier Centre for Economic Research and Policy Analysis, revised 30 Jan 2018.
    7. Chia-Lin Chang & Michael McAleer & Jiarong Tian, 2019. "Modeling and Testing Volatility Spillovers in Oil and Financial Markets for the USA, the UK, and China," Energies, MDPI, vol. 12(8), pages 1-24, April.
    8. Jiti Gao & Bin Peng & Wei Biao Wu & Yayi Yan, 2022. "Time-Varying Multivariate Causal Processes," Monash Econometrics and Business Statistics Working Papers 8/22, Monash University, Department of Econometrics and Business Statistics.
    9. Gao, Jiti & Peng, Bin & Wu, Wei Biao & Yan, Yayi, 2024. "Time-varying multivariate causal processes," Journal of Econometrics, Elsevier, vol. 240(1).
    10. Irene Henriques & Perry Sadorsky, 2018. "Can Bitcoin Replace Gold in an Investment Portfolio?," JRFM, MDPI, vol. 11(3), pages 1-19, August.
    11. Asai, M. & Caporin, M. & McAleer, M.J., 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Econometric Institute Research Papers EI 2012-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Chang, C-L. & Hsieh, T-L. & McAleer, M.J., 2018. "Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK," Econometric Institute Research Papers EI2018-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Costas Karfakis & Theodore Panagiotidis, 2015. "The effects of global monetary policy and Greek debt crisis on the dynamic conditional correlations of currency markets," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(4), pages 795-811, November.
    14. Perego, Erica R. & Vermeulen, Wessel N., 2016. "Macro-economic determinants of European stock and government bond correlations: A tale of two regions," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 214-232.
    15. Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2016. "Causes and hazards of the euro area sovereign debt crisis: Pure and fundamentals-based contagion," Economic Modelling, Elsevier, vol. 56(C), pages 133-147.
    16. Ahmed Ayadi & Marjène Gana & Stéphane Goutte & Khaled Guesmi, 2021. "Equity-Commodity Contagion During Four Recent Crises: Evidence from the USA, Europe and the BRICS," Working Papers halshs-03169699, HAL.
    17. Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
    18. Carlos Castro & Nini Johana Marin, 2014. "Stock return comovements and integration within the Latin American integrated market," Borradores de Investigación 11041, Universidad del Rosario.
    19. Bram Daelemans & Joseph P. Daniels & Farrokh Nourzad, 2018. "Free Trade Agreements and Volatility of Stock Returns and Exchange Rates: Evidence from NAFTA," Open Economies Review, Springer, vol. 29(1), pages 141-163, February.
    20. Iwatsubo, Kentaro & Watkins, Clinton, 2021. "The changing role of foreign investors in Tokyo stock price formation," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    21. Nathan Lael Joseph & Thi Thuy Anh Vo & Asma Mobarek & Sabur Mollah, 2020. "Volatility and asymmetric dependence in Central and East European stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 55(4), pages 1241-1303, November.
    22. Michael McAleer, 2019. "What They Did Not Tell You about Algebraic (Non-) Existence, Mathematical (IR-)Regularity, and (Non-) Asymptotic Properties of the Dynamic Conditional Correlation (DCC) Model," JRFM, MDPI, vol. 12(2), pages 1-9, April.
    23. 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).
    24. Tsukuda, Yoshihiko & Shimada, Junji & Miyakoshi, Tatsuyoshi, 2017. "Bond market integration in East Asia: Multivariate GARCH with dynamic conditional correlations approach," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 193-213.
    25. Michael mcAleer, 2017. "Stationarity and Invertibility of a Dynamic Correlation Matrix," Tinbergen Institute Discussion Papers 17-082/III, Tinbergen Institute.
    26. Chia-Lin Chang & Michael McAleer & Chia-Ping Liu, 2016. "Volatility spillovers for spot, futures, and ETF prices in energy and agriculture," Documentos de Trabajo del ICAE 2016-11, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    27. Pan, Zhiyuan & Wang, Yudong & Yang, Li, 2014. "Hedging crude oil using refined product: A regime switching asymmetric DCC approach," Energy Economics, Elsevier, vol. 46(C), pages 472-484.
    28. Zhang, Qi & Di, Peng & Farnoosh, Arash, 2021. "Study on the impacts of Shanghai crude oil futures on global oil market and oil industry based on VECM and DAG models," Energy, Elsevier, vol. 223(C).
    29. García Ruiz, Reyna Susana & López Herrera, Francisco & Cruz Aké, Salvador, 2018. "Determinantes del crédito y la morosidad en México / Determinants of credit and defaulting in Mexico," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 8(1), pages 85-104, enero-jun.
    30. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    31. Nikolay Gospodinov, 2017. "Asset Co-movements: Features and Challenges," FRB Atlanta Working Paper 2017-11, Federal Reserve Bank of Atlanta.
    32. Raúl de Jesús-Gutiérrez, 2019. "Integración entre mercados de petróleo de diferente calidad con base en las correlaciones condicionales dinámicas," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 11(2), pages 353-374, November.
    33. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "How are VIX and Stock Index ETF Related?," Documentos de Trabajo del ICAE 2016-02, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    34. Jean-David Fermanian & Hassan Malongo, 2013. "On the Stationarity of Dynamic Conditional Correlation Models," Working Papers 2013-26, Center for Research in Economics and Statistics.
    35. Graham Bird & Wenti Du & Eric Pentecost & Thomas Willett, 2017. "Was it different the second time? An empirical analysis of contagion during the crises in Greece 2009–15," The World Economy, Wiley Blackwell, vol. 40(12), pages 2530-2542, December.
    36. Katsiampa, Paraskevi, 2019. "An empirical investigation of volatility dynamics in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 50(C), pages 322-335.
    37. Fantazzini, Dean & Zimin, Stephan, 2019. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," MPRA Paper 95988, University Library of Munich, Germany.
    38. Hou, Yang (Greg) & Li, Steven, 2020. "Volatility and skewness spillover between stock index and stock index futures markets during a crash period: New evidence from China," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 166-188.
    39. Katsiampa, Paraskevi & Yarovaya, Larisa & Zięba, Damian, 2022. "High-frequency connectedness between Bitcoin and other top-traded crypto assets during the COVID-19 crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    40. Cui, Jinxin & Goh, Mark & Li, Binlin & Zou, Huiwen, 2021. "Dynamic dependence and risk connectedness among oil and stock markets: New evidence from time-frequency domain perspectives," Energy, Elsevier, vol. 216(C).
    41. Tsouknidis, Dimitris A., 2016. "Dynamic volatility spillovers across shipping freight markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 90-111.
    42. Benjamin Poignard & Jean-Davis Fermanian, 2014. "Dynamic Asset Correlations Based on Vines," Working Papers 2014-46, Center for Research in Economics and Statistics.
    43. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    44. Mehmet Balcilar & Riza Demirer & Rangan Gupta, 2017. "Do Sustainable Stocks Offer Diversification Benefits for Conventional Portfolios? An Empirical Analysis of Risk Spillovers and Dynamic Correlations," Sustainability, MDPI, vol. 9(10), pages 1-18, October.
    45. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    46. Jean-David Fermanian & Hassan Malongo, 2014. "On the stationarity of Dynamic Conditional Correlation models," Papers 1405.6905, arXiv.org, revised Mar 2016.
    47. Zhicheng Liang & Junwei Wang & Kin Keung Lai, 2020. "Dependence Structure Analysis and VaR Estimation Based on China’s and International Gold Price: A Copula Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 169-193, February.
    48. Jilber Urbina & Miguel Santolino & Montserrat Guillen, 2021. "Covariance Principle for Capital Allocation: A Time-Varying Approach," Mathematics, MDPI, vol. 9(16), pages 1-13, August.
    49. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    50. Takashi Isogai, 2015. "An Empirical Study of the Dynamic Correlation of Japanese Stock Returns," Bank of Japan Working Paper Series 15-E-7, Bank of Japan.
    51. Domingo Rodríguez Benavides & Ignacio Perrotini Hernández, 2019. "Las correlaciones dinámicas de contagio financiero:Estados Unidos y América Latina," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(2), pages 151-168, Abril-Jun.
    52. Saker Sabkha & Christian de Peretti, 2022. "On the performances of Dynamic Conditional Correlation models in the Sovereign CDS market and the corresponding bond market," Post-Print hal-01710398, HAL.
    53. Klein, Tony, 2018. "Trends and contagion in WTI and Brent crude oil spot and futures markets - The role of OPEC in the last decade," Energy Economics, Elsevier, vol. 75(C), pages 636-646.
    54. Piao, Xiaorui & Mei, Bin & Xue, Yuan, 2016. "Comparing the financial performance of timber REITs and other REITs," Forest Policy and Economics, Elsevier, vol. 72(C), pages 115-121.

  31. Caporin, Massimiliano & Jimenez-Martin, Juan-Angel & Gonzalez-Serrano, Lydia, 2013. "Currency hedging strategies, strategic benchmarks and the Global and Euro Sovereign financial crises," MPRA Paper 50940, University Library of Munich, Germany, revised 23 Oct 2013.

    Cited by:

    1. Kotkatvuori-Örnberg, Juha, 2016. "Dynamic conditional copula correlation and optimal hedge ratios with currency futures," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 60-69.
    2. Burkhardt, Raphael & Ulrych, Urban, 2023. "Sparse and stable international portfolio optimization and currency risk management," Journal of International Money and Finance, Elsevier, vol. 139(C).
    3. Bessler, Wolfgang & Wolff, Dominik, 2014. "Hedging European government bond portfolios during the recent sovereign debt crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 379-399.
    4. Lawrence Kryzanowski & Jie Zhang & Rui Zhong, 2021. "Currency hedging and quantitative easing: Evidence from global bond markets," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 555-597, June.

  32. Fulvio Baldovin & Francesco Camana & Massimiliano Caporin & Michele Caraglio & Attilio L. Stella, 2012. "Ensemble properties of high frequency data and intraday trading rules," Papers 1202.2447, arXiv.org, revised Jul 2013.

    Cited by:

    1. Baldovin, Fulvio & Caporin, Massimiliano & Caraglio, Michele & Stella, Attilio L. & Zamparo, Marco, 2015. "Option pricing with non-Gaussian scaling and infinite-state switching volatility," Journal of Econometrics, Elsevier, vol. 187(2), pages 486-497.
    2. Dieter Hendricks & Tim Gebbie & Diane Wilcox, 2015. "Detecting intraday financial market states using temporal clustering," Papers 1508.04900, arXiv.org, revised Feb 2017.
    3. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2014. "Interpreting Financial Market Crashes as Earthquakes: A New early Warning System for Medium Term Crashes," Tinbergen Institute Discussion Papers 14-067/III, Tinbergen Institute.
    4. Fulvio Baldovin & Francesco Camana & Michele Caraglio & Attilio L. Stella & Marco Zamparo, 2012. "Aftershock prediction for high-frequency financial markets' dynamics," Papers 1203.5893, arXiv.org, revised Jul 2012.

  33. Manabu Asai & Massimiliano Caporin & Michael McAleer, 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Working Papers in Economics 12/04, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Shawkat Hammoudeh & Michael McAleer, 2014. "Advances in Financial Risk Management andEconomic Policy Uncertainty: An Overview," Documentos de Trabajo del ICAE 2014-17, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Benjamin Poignard & Manabu Asaiz, 2020. "A Penalised OLS Framework for High-Dimensional Multivariate Stochastic Volatility Models," Discussion Papers in Economics and Business 20-02, Osaka University, Graduate School of Economics.
    3. Lin, Tiantian & Liu, Dehong & Zhang, Lili & Lung, Peter, 2019. "The information content of realized volatility of sector indices in China’s stock market," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 625-640.
    4. Benjamin Poignard & Manabu Asai, 2022. "High-Dimensional Sparse Multivariate Stochastic Volatility Models," Papers 2201.08584, arXiv.org, revised May 2022.
    5. Yuta Kurose & Yasuhiro Omori, 2016. "Multiple-block Dynamic Equicorrelations with Realized Measures, Leverage and Endogeneity," CIRJE F-Series CIRJE-F-1024, CIRJE, Faculty of Economics, University of Tokyo.
    6. Chen, Qiang & Gong, Yuting, 2019. "The economic sources of China's CSI 300 spot and futures volatilities before and after the 2015 stock market crisis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 102-121.
    7. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.

  34. Monica Billio & Massimiliano Caporin & Michele Costola, 2012. "Backward/forward optimal combination of performance measures for equity screening," Working Papers 2012_13, Department of Economics, University of Venice "Ca' Foscari".

    Cited by:

    1. Massimiliano Caporin & Michele Costola & Gregory Mathieu Jannin & Bertrand Maillet, 2016. "On the (Ab)Use of Omega?," Working Papers hal-01697640, HAL.
    2. León, Angel & Navarro, Lluís & Nieto, Belén, 2019. "Screening rules and portfolio performance," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 642-662.
    3. Michele Costola & Massimiliano Caporin, 2016. "Rational Learning For Risk-Averse Investors By Conditioning On Behavioral Choices," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-26, March.
    4. León, Ángel & Moreno, Manuel, 2015. "Lower Partial Moments under Gram Charlier Distribution: Performance Measures and Efficient Frontiers," QM&ET Working Papers 15-3, University of Alicante, D. Quantitative Methods and Economic Theory.
    5. Massimiliano Caporin & Luca Corazzini & Michele Costola, 2014. "Measuring the Behavioral Component of Financial Fluctuations: An Analysis Based on the S&P 500," CREATES Research Papers 2014-33, Department of Economics and Business Economics, Aarhus University.
    6. Monica Billio & Bertrand Maillet & Loriana Pelizzon, 2021. "A meta-measure of performance related to both investors and investments characteristics," Post-Print hal-03543398, HAL.
    7. José Luis Miralles-Quirós & María Mar Miralles-Quirós, 2021. "Alternative Financial Methods for Improving the Investment in Renewable Energy Companies," Mathematics, MDPI, vol. 9(9), pages 1-25, May.

  35. Matteo Bonato & Massimiliano Caporin & Angelo Ranaldo, 2012. "Risk spillovers in international equity portfolios," Working Papers 2012-03, Swiss National Bank.

    Cited by:

    1. Fengler, Matthias R. & Gisler, Katja I. M., 2014. "A variance spillover analysis without covariances: what do we miss?," Economics Working Paper Series 1409, University of St. Gallen, School of Economics and Political Science.
    2. Bonato, Matteo, 2019. "Realized correlations, betas and volatility spillover in the agricultural commodity market: What has changed?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 184-202.
    3. Buncic, Daniel & Gisler, Katja I. M., 2015. "Global Equity Market Volatility Spillovers: A Broader Role for the United States," Economics Working Paper Series 1508, University of St. Gallen, School of Economics and Political Science.

  36. Massimiliano Caporin & Loriana Pelizzon & Francesco Ravazzolo & Roberto Rigobon, 2012. "Measuring sovereign contagion in Europe," Working Paper 2012/05, Norges Bank.

    Cited by:

    1. Colin Ellis, 2020. "Are Corporate Bond Defaults Contagious across Sectors?," IJFS, MDPI, vol. 8(1), pages 1-17, January.
    2. Ioannis Chatziantoniou & David Gabauer, 2019. "EMU-Risk Synchronisation and Financial Fragility Through the Prism of Dynamic Connectedness," Working Papers in Economics & Finance 2019-07, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    3. Tola, Albi & Wälti, Sébastien, 2012. "Deciphering financial contagion in the euro area during the crisis," MPRA Paper 49251, University Library of Munich, Germany.
    4. Claeys, Peter & Vašíček, Bořek, 2014. "Measuring bilateral spillover and testing contagion on sovereign bond markets in Europe," Working Paper Series 1666, European Central Bank.
    5. Marta Gómez-Puig & Simón Sosvilla-Rivero, 2014. "“Causality and Contagion in EMU Sovereign Debt Markets”," IREA Working Papers 201403, University of Barcelona, Research Institute of Applied Economics, revised Feb 2014.
    6. Di Tommaso, Caterina & Foglia, Matteo & Pacelli, Vincenzo, 2023. "The impact and the contagion effect of natural disasters on sovereign credit risk. An empirical investigation," International Review of Financial Analysis, Elsevier, vol. 87(C).
    7. Jean-Pierre Allegret & Hélène Raymond & Houda Rharrabti, 2016. "The Impact of the Eurozone Crisis on European Banks Stocks Contagion or Interdependence?," Post-Print hal-01659719, HAL.
    8. Rebekka Gätjen & Melanie Schienle, 2015. "Measuring Connectedness of Euro Area Sovereign Risk," SFB 649 Discussion Papers SFB649DP2015-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Augustin, Patrick & Subrahmanyam, Marti G. & Tang, Dragon Yongjun & Wang, Sarah Qian, 2014. "Credit Default Swaps: A Survey," Foundations and Trends(R) in Finance, now publishers, vol. 9(1-2), pages 1-196, December.
    10. Stolbov, Mikhail, 2014. "The causal linkages between sovereign CDS prices for the BRICS and major European economies," Economics Discussion Papers 2014-9, Kiel Institute for the World Economy (IfW Kiel).
    11. Fratzscher, Marcel & Rieth, Malte, 2015. "Monetary policy, bank bailouts and the sovereign-bank risk nexus in the euro area," CEPR Discussion Papers 10370, C.E.P.R. Discussion Papers.
    12. Bampinas, Georgios & Panagiotidis, Theodore & Politsidis, Panagiotis N., 2023. "Sovereign bond and CDS market contagion: A story from the Eurozone crisis," Journal of International Money and Finance, Elsevier, vol. 137(C).
    13. Dungey, Mardi & Flavin, Thomas J. & Lagoa-Varela, Dolores, 2020. "Are banking shocks contagious? Evidence from the eurozone," Journal of Banking & Finance, Elsevier, vol. 112(C).
    14. Jean-Pierre Allegret & Hélène Raymond & Houda Rharrabti, 2014. "The impact of the global and eurozone crises on European banks stocks Some evidence of shift contagion," EconomiX Working Papers 2014-24, University of Paris Nanterre, EconomiX.
    15. David Cronin, 2020. "Are Member States’ Budgetary Policies Adhering to the EU Fiscal Rules?," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot GmbH, Berlin, vol. 66(1), pages 47-64.
    16. Koijen, Ralph & Gabaix, Xavier, 2020. "Granular Instrumental Variables," CEPR Discussion Papers 15531, C.E.P.R. Discussion Papers.
    17. David Greenlaw & James D. Hamilton & Peter Hooper & Frederic S. Mishkin, 2013. "Crunch Time: Fiscal Crises and the Role of Monetary Policy," NBER Working Papers 19297, National Bureau of Economic Research, Inc.
    18. Fernando Fernández-Rodríguez & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2015. "Volatility spillovers in EMU sovereign bond markets," Working Papers del Instituto Complutense de Estudios Internacionales 1504, Universidad Complutense de Madrid, Instituto Complutense de Estudios Internacionales.
    19. Michael Pfarrhofer, 2021. "Modeling tail risks of inflation using unobserved component quantile regressions," Papers 2103.03632, arXiv.org, revised Oct 2021.
    20. De Bruyckere, Valerie & Gerhardt, Maria & Schepens, Glenn & Vander Vennet, Rudi, 2013. "Bank/sovereign risk spillovers in the European debt crisis," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4793-4809.
    21. Zhang, Wenlong & Zhang, Gaiyan & Helwege, Jean, 2022. "Cross country linkages and transmission of sovereign risk: Evidence from China’s credit default swaps," Journal of Financial Stability, Elsevier, vol. 58(C).
    22. Ling, Aifan & Li, Jinlong & Zhang, Yugui, 2023. "Can firms with higher ESG ratings bear higher bank systemic tail risk spillover?—Evidence from Chinese A-share market," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    23. Reboredo, Juan C. & Ugolini, Andrea, 2015. "A vine-copula conditional value-at-risk approach to systemic sovereign debt risk for the financial sector," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 98-123.
    24. Jamal Bouoiyour, Refk Selmi, 2019. "Brexit and CDS spillovers across UK and Europe," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 16(1), pages 105-124, June.
    25. Dimic, Nebojsa & Piljak, Vanja & Swinkels, Laurens & Vulanovic, Milos, 2021. "The structure and degree of dependence in government bond markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    26. Emilios C. Galariotis & Panagiota Makrichoriti & Spyros Spyrou, 2016. "Sovereign CDS Spread Determinants and Spill-Over Effects During Financial Crisis: A Panel VAR Approach," Post-Print hal-01358715, HAL.
    27. Le, Chau & Dickinson, David & Le, Anh, 2022. "Sovereign risk spillovers: A network approach," Journal of Financial Stability, Elsevier, vol. 60(C).
    28. Dungey, Mardi & Gajurel, Dinesh, 2014. "Equity market contagion during the global financial crisis: Evidence from the world's eight largest economies," Economic Systems, Elsevier, vol. 38(2), pages 161-177.
    29. Khalifa, Ahmed & Caporin, Massimiliano & Hammoudeh, Shawkat, 2017. "The relationship between oil prices and rig counts: The importance of lags," Energy Economics, Elsevier, vol. 63(C), pages 213-226.
    30. Dungey, Mardi & Milunovich, George & Thorp, Susan & Yang, Minxian, 2012. "Endogenous crisis dating and contagion using smooth transition structural GARCH," Working Papers 15030, University of Tasmania, Tasmanian School of Business and Economics, revised 29 Aug 2012.
    31. Ehrmann, Michael & Fratzscher, Marcel, 2017. "Euro area government bonds – Fragmentation and contagion during the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 26-44.
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    159. Henri Audigé, 2013. "A new approach of contagion based on smooth transition conditional correlation GARCH models: An empirical application to the Greek crisis," EconomiX Working Papers 2013-2, University of Paris Nanterre, EconomiX.
    160. Elie Bouri & Rangan Gupta & Shixuan Wang, 2022. "Nonlinear contagion between stock and real estate markets: International evidence from a local Gaussian correlation approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2089-2109, April.
    161. Fabrizio Durante & Enrico Foscolo & Alex Weissensteiner, 2017. "Dependence between Stock Returns of Italian Banks and the Sovereign Risk," Econometrics, MDPI, vol. 5(2), pages 1-14, June.
    162. Berardi, Andrea, 2023. "Term premia and short rate expectations in the euro area," Journal of Empirical Finance, Elsevier, vol. 74(C).

  37. Monica Billio & Massimiliano Caporin & Loriana Pelizzon & Domenico Sartore, 2012. "CDS Industrial Sector Indices, credit and liquidity risk," Working Papers 2012_09, Department of Economics, University of Venice "Ca' Foscari".

    Cited by:

    1. Mansur, Alfan, 2018. "Measuring Systemic Risk on Indonesia’s Banking System," MPRA Paper 93300, University Library of Munich, Germany, revised 12 Apr 2018.

  38. Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 12/06, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Ralf Becker & Adam Clements & Robert O'Neill, 2018. "A Multivariate Kernel Approach to Forecasting the Variance Covariance of Stock Market Returns," Econometrics, MDPI, vol. 6(1), pages 1-27, February.
    2. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    3. 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.
    4. Audrino, Francesco, 2011. "Forecasting correlations during the late-2000s financial crisis: short-run component, long-run component, and structural breaks," Economics Working Paper Series 1112, University of St. Gallen, School of Economics and Political Science.
    5. Ashfaq, Saleha & Tang, Yong & Maqbool, Rashid, 2023. "Insights of energy and its trade networking impacts on sustainable economic development," Energy, Elsevier, vol. 265(C).
    6. Jacobs, Michael & Karagozoglu, Ahmet K., 2014. "On the characteristics of dynamic correlations between asset pairs," Research in International Business and Finance, Elsevier, vol. 32(C), pages 60-82.
    7. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2016. "Volatility Dependent Dynamic Equicorrelation," NCER Working Paper Series 111, National Centre for Econometric Research.
    8. Yujia Hu, 2023. "A Heuristic Approach to Forecasting and Selection of a Portfolio with Extra High Dimensions," Mathematics, MDPI, vol. 11(6), pages 1-21, March.
    9. Shang, Han Lin & Kearney, Fearghal, 2022. "Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1025-1049.
    10. Fantazzini, Dean & Zimin, Stephan, 2019. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," MPRA Paper 95988, University Library of Munich, Germany.
    11. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    12. Marc Hallin & Carlos Trucíos, 2020. "Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Approach," Working Papers ECARES 2020-50, ULB -- Universite Libre de Bruxelles.
    13. Takayuki Morimoto & Yoshinori Kawasaki, 2017. "Forecasting Financial Market Volatility Using a Dynamic Topic Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 24(3), pages 149-167, September.
    14. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".
    15. Sofiane Aboura & Julien Chevallier, 2015. "A cross-volatility index for hedging the country risk," Post-Print hal-01529742, HAL.
    16. Mauro Bernardi & Leopoldo Catania, 2016. "Comparison of Value-at-Risk models using the MCS approach," Computational Statistics, Springer, vol. 31(2), pages 579-608, June.
    17. Karim M Abadir, 2023. "Explicit minimal representation of variance matrices, and its implication for dynamic volatility models," The Econometrics Journal, Royal Economic Society, vol. 26(1), pages 88-104.
    18. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    19. Hallin, Marc & Trucíos, Carlos, 2023. "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, vol. 27(C), pages 1-15.
    20. Massimiliano Caporin & Paolo Paruolo, 2015. "Proximity-Structured Multivariate Volatility Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 559-593, May.
    21. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    22. Alexakis, Christos & Pappas, Vasileios, 2018. "Sectoral dynamics of financial contagion in Europe - The cases of the recent crises episodes," Economic Modelling, Elsevier, vol. 73(C), pages 222-239.
    23. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2019. "Volatility-dependent correlations: further evidence of when, where and how," Empirical Economics, Springer, vol. 57(2), pages 505-540, August.
    24. Timo Dimitriadis & Yannick Hoga, 2022. "Dynamic CoVaR Modeling," Papers 2206.14275, arXiv.org, revised Feb 2024.
    25. Sylvain Barde, 2015. "A fast algorithm for finding the confidence set of large collections of models," Studies in Economics 1519, School of Economics, University of Kent.
    26. Pappas, Vasileios & Ingham, Hilary & Izzeldin, Marwan & Steele, Gerry, 2016. "Will the crisis “tear us apart”? Evidence from the EU," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 346-360.

  39. Massimiliano Caporin & Gabriel G. Velo, 2011. "Modeling and forecasting realized range volatility," "Marco Fanno" Working Papers 0128, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," JRFM, MDPI, vol. 9(3), pages 1-25, July.

  40. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2011. "Conditional jumps in volatility and their economic determinants," "Marco Fanno" Working Papers 0138, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Jan Hanousek & Evžen Kočenda & Jan Novotný, 2016. "Shluková analýza skoků na kapitálových trzích [Cluster Analysis of Jumps on Capital Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2016(2), pages 127-144.
    2. Jan Hanousek & Evzen Kocenda & Jan Novotny, 2014. "Price jumps on European stock markets," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 14(1), pages 10-22, March.
    3. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," JRFM, MDPI, vol. 9(3), pages 1-25, July.
    4. Caporin, Massimiliano & Velo, Gabriel G., 2015. "Realized range volatility forecasting: Dynamic features and predictive variables," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 98-112.
    5. Jan Novotn?? & Jan Hanousek & Ev??en Ko??enda, 2013. "Price Jump Indicators: Stock Market Empirics During the Crisis," William Davidson Institute Working Papers Series wp1050, William Davidson Institute at the University of Michigan.

  41. Gian Piero Aielli & Massimiliano Caporin, 2011. "Variance Clustering Improved Dynamic Conditional Correlation MGARCH Estimators," "Marco Fanno" Working Papers 0133, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    2. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    3. Leonardo Chaves Borges Cardoso & Maurício Vaz Lobo Bittencourt, 2016. "Price Volatility Transmission From Oil To Energy And Non-Energy Agricultural Commodities," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 181, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    4. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    5. Aielli, Gian Piero & Caporin, Massimiliano, 2013. "Fast clustering of GARCH processes via Gaussian mixture models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 205-222.
    6. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 383-417.
    7. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".
    8. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Takashi Isogai, 2015. "An Empirical Study of the Dynamic Correlation of Japanese Stock Returns," Bank of Japan Working Paper Series 15-E-7, Bank of Japan.

  42. Massimiliano Caporin & Angelo Ranaldo & Paolo Santucci de Magistris, 2011. "On the Predictability of Stock Prices: A Case for High and Low Prices," "Marco Fanno" Working Papers 0136, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Stoupos, Nikolaos & Kiohos, Apostolos, 2022. "Bond markets integration in the EU: New empirical evidence from the Eastern non-euro member-states," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    2. Søren Johansen & Morten Ørregaard Nielsen, 2018. "Nonstationary cointegration in the fractionally cointegrated VAR model," CREATES Research Papers 2018-17, Department of Economics and Business Economics, Aarhus University.
    3. Donald A. Otieno & Rose W. Ngugi & Peter W. Muriu, 2019. "The impact of inflation rate on stock market returns: evidence from Kenya," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(1), pages 73-90, January.
    4. Stoupos, Nikolaos & Kiohos, Apostolos, 2022. "Euro area stock markets integration: Empirical evidence after the end of 2010 debt crisis," Finance Research Letters, Elsevier, vol. 46(PB).
    5. Stoyan V. Stoyanov & Yong Shin Kim & Svetlozar T. Rachev & Frank J. Fabozzi, 2017. "Option pricing for Informed Traders," Papers 1711.09445, arXiv.org.
    6. Donald A. Otieno & Rose W. Ngugi & Nelson H. W. Wawire, 2017. "Effects of Interest Rate on Stock Market Returns in Kenya," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(8), pages 40-50, August.
    7. OlaOluwa S. Yaya & Xuan Vinh Vo & Ahamuefula E. Ogbonna & Adeolu O. Adewuyi, 2022. "Modelling cryptocurrency high–low prices using fractional cointegrating VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 489-505, January.
    8. Ignacio Escanuela Romana & Clara Escanuela Nieves, 2023. "A spectral approach to stock market performance," Papers 2305.05762, arXiv.org.
    9. Federico Carlini & Paolo Santucci de Magistris, 2019. "Resuscitating the co-fractional model of Granger (1986)," CREATES Research Papers 2019-02, Department of Economics and Business Economics, Aarhus University.
    10. Massimiliano Caporin & Fulvio Fontini & Paolo Santucci De Magistris, 2017. "Price convergence within and between the Italian electricity day-ahead and dispatching services markets," "Marco Fanno" Working Papers 0215, Dipartimento di Scienze Economiche "Marco Fanno".
    11. Farias Nazário, Rodolfo Toríbio & e Silva, Jéssica Lima & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2017. "A literature review of technical analysis on stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 115-126.
    12. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Samuel Tabot Enow, 2022. "Price Clustering in International Financial Markets during the COVID-19 Pandemic and Its Implications," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 10(2), pages 46-53.
    14. Alia Afzal & Philipp Sibbertsen, 2021. "Modeling fractional cointegration between high and low stock prices in Asian countries," Empirical Economics, Springer, vol. 60(2), pages 661-682, February.
    15. Federico Carlini & Paolo Santucci de Magistris, 2019. "Resuscitating the co-fractional model of Granger (1986)," Discussion Papers 19/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    16. Huiwen Wang & Wenyang Huang & Shanshan Wang, 2021. "Forecasting open-high-low-close data contained in candlestick chart," Papers 2104.00581, arXiv.org.
    17. Baruník, Jozef & Dvořáková, Sylvie, 2015. "An empirical model of fractionally cointegrated daily high and low stock market prices," Economic Modelling, Elsevier, vol. 45(C), pages 193-206.
    18. Yaya, OlaOluwa S & Gil-Alana, Luis A., 2018. "High and Low Intraday Commodity Prices: A Fractional Integration and Cointegration Approach," MPRA Paper 90518, University Library of Munich, Germany.
    19. Ni, Yensen & Liao, Yi-Ching & Huang, Paoyu, 2015. "MA trading rules, herding behaviors, and stock market overreaction," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 253-265.
    20. Leandro Maciel, 2020. "Technical analysis based on high and low stock prices forecasts: evidence for Brazil using a fractionally cointegrated VAR model," Empirical Economics, Springer, vol. 58(4), pages 1513-1540, April.
    21. Stoupos, Nikolaos & Kiohos, Apostolos, 2021. "Energy commodities and advanced stock markets: A post-crisis approach," Resources Policy, Elsevier, vol. 70(C).
    22. Nikolaos Stoupos & Apostolos Kiohos, 2022. "Euro Area: Towards a European Common Bond? – Empirical Evidence from the Sovereign Debt Markets," Journal of Common Market Studies, Wiley Blackwell, vol. 60(4), pages 1019-1046, July.
    23. Bravo Caro, José Manuel & Golpe, Antonio A. & Iglesias, Jesús & Vides, José Carlos, 2020. "A new way of measuring the WTI – Brent spread. Globalization, shock persistence and common trends," Energy Economics, Elsevier, vol. 85(C).
    24. Nijolė MAKNICKIENĖ & Jelena STANKEVIČIENĖ & Algirdas MAKNICKAS, 2020. "Comparison of Forex Market Forecasting Tools Based on Evolino Ensemble and Technical Analysis Indicators," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 134-148, September.
    25. Vides, José Carlos & Golpe, Antonio A. & Iglesias, Jesús, 2020. "The EHTS and the persistence in the spread reconsidered. A fractional cointegration approach," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 124-137.

  43. Caporin, Massimiliano & Lisi, Francesco, 2011. "Comparing and selecting performance measures using rank correlations," Economics Discussion Papers 2011-14, Kiel Institute for the World Economy (IfW Kiel).

    Cited by:

    1. León, Angel & Navarro, Lluís & Nieto, Belén, 2019. "Screening rules and portfolio performance," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 642-662.
    2. Massimiliano Caporin & Grégory M. Jannin & Francesco Lisi & Bertrand Maillet, 2014. "A Survey on the Four Families of Performance Measures," Post-Print hal-01243416, HAL.
    3. León, Ángel & Moreno, Manuel, 2015. "Lower Partial Moments under Gram Charlier Distribution: Performance Measures and Efficient Frontiers," QM&ET Working Papers 15-3, University of Alicante, D. Quantitative Methods and Economic Theory.
    4. Anand, Abhinav & Li, Tiantian & Kurosaki, Tetsuo & Kim, Young Shin, 2016. "Foster–Hart optimal portfolios," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 117-130.
    5. Korn, Olaf & Möller, Philipp M. & Schwehm, Christian, 2019. "Drawdown measures: Are they all the same?," CFR Working Papers 19-04, University of Cologne, Centre for Financial Research (CFR).
    6. León, Ángel & Ñíguez, Trino-Manuel, 2020. "Modeling asset returns under time-varying semi-nonparametric distributions," Journal of Banking & Finance, Elsevier, vol. 118(C).
    7. Zhang, Hanxiong & Auer, Benjamin R. & Vortelinos, Dimitrios I., 2018. "Performance ranking (dis)similarities in commodity markets," Global Finance Journal, Elsevier, vol. 35(C), pages 115-137.

  44. Massimiliano Caporin & Michael McAleer, 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Working Papers in Economics 11/23, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Helmut Lütkepohl & Thore Schlaak, 2017. "Choosing between Different Time-Varying Volatility Models for Structural Vector Autoregressive Analysis," Discussion Papers of DIW Berlin 1672, DIW Berlin, German Institute for Economic Research.
    2. Adam E Clements & Ayesha Scott & Annastiina Silvennoinen, 2012. "Forecasting multivariate volatility in larger dimensions: some practical issues," NCER Working Paper Series 80, National Centre for Econometric Research.
    3. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2013. "On the Benefits of Equicorrelation for Portfolio Allocation," NCER Working Paper Series 99, National Centre for Econometric Research.
    4. Zhou, Jian, 2014. "Modeling conditional covariance for mixed-asset portfolios," Economic Modelling, Elsevier, vol. 40(C), pages 242-249.
    5. Bouri, Elie & Chen, Qian & Lien, Donald & Lv, Xin, 2017. "Causality between oil prices and the stock market in China: The relevance of the reformed oil product pricing mechanism," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 34-48.

  45. Manabu Asai & Massimiliano Caporin & Michael McAleer, 2010. "Block Structure Multivariate Stochastic Volatility Models," Working Papers in Economics 10/24, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Shawkat Hammoudeh & Michael McAleer, 2014. "Advances in Financial Risk Management andEconomic Policy Uncertainty: An Overview," Documentos de Trabajo del ICAE 2014-17, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," KIER Working Papers 840, Kyoto University, Institute of Economic Research.
    3. Haroon Mumtaz & Francesco Zanetti, 2013. "The Impact of the Volatility of Monetary Policy Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(4), pages 535-558, June.
    4. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    5. Caldeira, João F & Moura, Guilherme Valle & Santos, André Alves Portela, 2013. "Seleção de carteiras utilizando o modelo Fama-French-Carhart," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(1), April.
    6. Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023. "Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
    7. Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 12/06, University of Canterbury, Department of Economics and Finance.
    8. Asai, M. & Caporin, M. & McAleer, M.J., 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Econometric Institute Research Papers EI 2012-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    10. Yuta Kurose & Yasuhiro Omori, 2014. "Dynamic Equicorrelation Stochastic Volatility," CIRJE F-Series CIRJE-F-941, CIRJE, Faculty of Economics, University of Tokyo.
    11. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," CIRJE F-Series CIRJE-F-638, CIRJE, Faculty of Economics, University of Tokyo.
    12. So, Mike K.P. & Chan, Thomas W.C. & Chu, Amanda M.Y., 2022. "Efficient estimation of high-dimensional dynamic covariance by risk factor mapping: Applications for financial risk management," Journal of Econometrics, Elsevier, vol. 227(1), pages 151-167.
    13. Benjamin Poignard & Manabu Asai, 2022. "High-Dimensional Sparse Multivariate Stochastic Volatility Models," Papers 2201.08584, arXiv.org, revised May 2022.
    14. Sujay K Mukhoti, "undated". "Dynamic Feedback Effect And Skewness In Non-Stationary Stochastic Volatility Model With Leverage," Working papers 145, Indian Institute of Management Kozhikode.
    15. Ishihara, Tsunehiro & Omori, Yasuhiro, 2012. "Efficient Bayesian estimation of a multivariate stochastic volatility model with cross leverage and heavy-tailed errors," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3674-3689.
    16. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
    17. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    18. Mustafa Hakan Eratalay, 2012. "Estimation of Multivariate Stochastic Volatility Models: A Comparative Monte Carlo Study," EUSP Department of Economics Working Paper Series 2012/04, European University at St. Petersburg, Department of Economics.
    19. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2011. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-812, CIRJE, Faculty of Economics, University of Tokyo.
    20. Matteo Bonato & Massimiliano Caporin & Angelo Ranaldo, 2009. "Forecasting realized (co)variances with a block structure Wishart autoregressive model," Working Papers 2009-03, Swiss National Bank.
    21. Michael McAleer & Massimiliano Caporin, 2011. "Ranking Multivariate GARCH Models by Problem Dimension:An Empirical Evaluation," KIER Working Papers 778, Kyoto University, Institute of Economic Research.
    22. McCausland, William & Miller, Shirley & Pelletier, Denis, 2021. "Multivariate stochastic volatility using the HESSIAN method," Econometrics and Statistics, Elsevier, vol. 17(C), pages 76-94.
    23. Anna Pajor & Justyna Wróblewska, 2022. "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 427-448, September.
    24. Trojan, Sebastian, 2014. "Multivariate Stochastic Volatility with Dynamic Cross Leverage," Economics Working Paper Series 1424, University of St. Gallen, School of Economics and Political Science.
    25. Diks, Cees & Panchenko, Valentyn & Sokolinskiy, Oleg & van Dijk, Dick, 2014. "Comparing the accuracy of multivariate density forecasts in selected regions of the copula support," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 79-94.
    26. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    27. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.
    28. Caporin, Massimiliano, 2013. "Equity and CDS sector indices: Dynamic models and risk hedging," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 261-275.
    29. Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
    30. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.
    31. Skaug, Hans J. & Yu, Jun, 2014. "A flexible and automated likelihood based framework for inference in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 642-654.
    32. Geert Mesters & Bernd Schwaab & Siem Jan Koopman, 2014. "A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area," Tinbergen Institute Discussion Papers 14-071/III, Tinbergen Institute.
    33. Fu, Hsuan & Luger, Richard, 2022. "Multiple testing of the forward rate unbiasedness hypothesis across currencies," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 232-245.

  46. Massimiliano Caporin & Juliusz Pres, 2010. "Modelling and forecasting wind speed intensity for weather risk management," "Marco Fanno" Working Papers 0106, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-003/4, Tinbergen Institute.
    2. A. Alexandridis & A. Zapranis, 2013. "Wind Derivatives: Modeling and Pricing," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 299-326, March.
    3. Naseri, Masoud & Baraldi, Piero & Compare, Michele & Zio, Enrico, 2016. "Availability assessment of oil and gas processing plants operating under dynamic Arctic weather conditions," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 66-82.
    4. Matthias Ritter & Zhiwei Shen & Brenda López Cabrera & Martin Odening & Lars Deckert, 2014. "Designing an Index for Assessing Wind Energy Potential," SFB 649 Discussion Papers SFB649DP2014-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Andrea Monticini & Francesco Ravazzolo, 2014. "Forecasting the intraday market price of money," DISCE - Working Papers del Dipartimento di Economia e Finanza def010, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    6. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2018. "Managing renewable energy production risk," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 1-19.
    7. Niu, Tong & Wang, Jianzhou & Zhang, Kequan & Du, Pei, 2018. "Multi-step-ahead wind speed forecasting based on optimal feature selection and a modified bat algorithm with the cognition strategy," Renewable Energy, Elsevier, vol. 118(C), pages 213-229.
    8. Caporin, Massimiliano & Fontini, Fulvio, 2014. "The Value of Protecting Venice from the Acqua Alta Phenomenon under Different Local Sea Level Rises," MPRA Paper 53779, University Library of Munich, Germany.
    9. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2013. "Stylized Facts and Dynamic Modeling of High-frequency Data on Precious Metals," Working Papers on Finance 1318, University of St. Gallen, School of Finance.
    10. Laura Casula & Guglielmo D’Amico & Giovanni Masala & Filippo Petroni, 2020. "Performance estimation of photovoltaic energy production," Letters in Spatial and Resource Sciences, Springer, vol. 13(3), pages 267-285, December.
    11. Huurman, Christian & Ravazzolo, Francesco & Zhou, Chen, 2012. "The power of weather," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3793-3807.
    12. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    13. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2014. "Precious Metals Under the Microscope: A High-Frequency Analysis," Working Papers on Finance 1409, University of St. Gallen, School of Finance.
    14. Ambach, Daniel & Schmid, Wolfgang, 2015. "Periodic and long range dependent models for high frequency wind speed data," Energy, Elsevier, vol. 82(C), pages 277-293.
    15. Yeny E. Rodríguez & Miguel A. Pérez-Uribe & Javier Contreras, 2021. "Wind Put Barrier Options Pricing Based on the Nordix Index," Energies, MDPI, vol. 14(4), pages 1-14, February.
    16. Laura Casula & Guglielmo D'Amico & Giovanni Masala & Filippo Petroni, 2020. "Performance estimation of a wind farm with a dependence structure between electricity price and wind speed," The World Economy, Wiley Blackwell, vol. 43(10), pages 2803-2822, October.
    17. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2017. "An Electricity Price Modeling Framework for Renewable-Dominant Markets," Working Paper Series in Production and Energy 23, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    18. Sun, Zexian & Zhao, Mingyu & Zhao, Guohong, 2022. "Hybrid model based on VMD decomposition, clustering analysis, long short memory network, ensemble learning and error complementation for short-term wind speed forecasting assisted by Flink platform," Energy, Elsevier, vol. 261(PB).
    19. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Nonlinear Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-172/4, Tinbergen Institute.
    20. Contreras, Javier & Rodríguez, Yeny E., 2014. "GARCH-based put option valuation to maximize benefit of wind investors," Applied Energy, Elsevier, vol. 136(C), pages 259-268.

  47. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 10/34, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Yaya, OlaOluwa & Ogbonna, Ahamuefula, 2018. "Modelling crude oil-petroleum products’ price nexus using dynamic conditional correlation GARCH models," MPRA Paper 91227, University Library of Munich, Germany.
    2. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars & VIOLANTE, Francesco, 2012. "The value of multivariate model sophistication: an application to pricing Dow Jones Industrial Average options," LIDAM Discussion Papers CORE 2012003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Becker, R. & Clements, A.E. & Doolan, M.B. & Hurn, A.S., 2015. "Selecting volatility forecasting models for portfolio allocation purposes," International Journal of Forecasting, Elsevier, vol. 31(3), pages 849-861.
    4. Ralf Becker & Adam Clements & Robert O'Neill, 2018. "A Multivariate Kernel Approach to Forecasting the Variance Covariance of Stock Market Returns," Econometrics, MDPI, vol. 6(1), pages 1-27, February.
    5. Adam E Clements & Ayesha Scott & Annastiina Silvennoinen, 2012. "Forecasting multivariate volatility in larger dimensions: some practical issues," NCER Working Paper Series 80, National Centre for Econometric Research.
    6. Massimiliano Caporin & Michael McAleer, 2010. "Model Selection and Testing of Conditional and Stochastic Volatility Models," Working Papers in Economics 10/58, University of Canterbury, Department of Economics and Finance.
    7. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2013. "On the Benefits of Equicorrelation for Portfolio Allocation," NCER Working Paper Series 99, National Centre for Econometric Research.
    8. Salisu, Afees A. & Oloko, Tirimisiyu F., 2015. "Modeling oil price–US stock nexus: A VARMA–BEKK–AGARCH approach," Energy Economics, Elsevier, vol. 50(C), pages 1-12.
    9. LAURENT, Sébastien & ROMBOUTS, Jeroen V. K. & VIOLANTE, Francesco, 2010. "On the forecasting accuracy of multivariate GARCH models," LIDAM Discussion Papers CORE 2010025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Benjamin Poignard & Jean-Davis Fermanian, 2014. "Dynamic Asset Correlations Based on Vines," Working Papers 2014-46, Center for Research in Economics and Statistics.
    11. Manner, Hans & Reznikova, Olga, 2010. "Forecasting international stock market correlations: does anything beat a CCC?," Discussion Papers in Econometrics and Statistics 7/10, University of Cologne, Institute of Econometrics and Statistics.
    12. Massimiliano Caporin & Paolo Paruolo, 2015. "Proximity-Structured Multivariate Volatility Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 559-593, May.
    13. Zolfaghari, Mehdi, 2023. "How does US tariff policy affect the relationship among crude oil, the US dollar and metal markets?," Resources Policy, Elsevier, vol. 85(PB).
    14. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Adam E Clements & Mark Doolan & Stan Hurn & Ralf Becker, 2012. "Selecting forecasting models for portfolio allocation," NCER Working Paper Series 85, National Centre for Econometric Research.

  48. Massimiliano Caporin & Michael McAleer, 2010. "Model Selection and Testing of Conditional and Stochastic Volatility Models," Working Papers in Economics 10/58, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Michael McAleer & Kim Radalj, 2013. "Herding, Information Cascades and Volatility Spillovers in Futures Markets," Documentos de Trabajo del ICAE 2013-25, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Chang, C-L. & Jiménez-Martín, J.A. & McAleer, M.J. & Pérez-Amaral, T., 2011. "Risk Management of Risk under the Basel Accord: Forecasting Value-at-Risk of VIX Futures," Econometric Institute Research Papers EI 2011-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Chang, Chia-Lin & Jiménez-Martín, Juan-Ángel & Maasoumi, Esfandiar & Pérez-Amaral, Teodosio, 2015. "A stochastic dominance approach to financial risk management strategies," Journal of Econometrics, Elsevier, vol. 187(2), pages 472-485.
    4. Helmut Lütkepohl & Thore Schlaak, 2017. "Choosing between Different Time-Varying Volatility Models for Structural Vector Autoregressive Analysis," Discussion Papers of DIW Berlin 1672, DIW Berlin, German Institute for Economic Research.
    5. Michael McAleer & Juan-Ángel Jiménez-Martín & Teodosio Pérez-Amaral, 2010. "GFC-Robust Risk Management Strategies under the Basel Accord," Working Papers in Economics 10/63, University of Canterbury, Department of Economics and Finance.
    6. Chia-Lin Chang & Juan-à ngel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2011. "The Rise and Fall of S&P500 Variance Futures," KIER Working Papers 795, Kyoto University, Institute of Economic Research.
    7. Paulo Araújo Santos & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "GFC-Robust Risk Management Under the Basel Accord Using Extreme Value Methodologies," Working Papers in Economics 11/28, University of Canterbury, Department of Economics and Finance.
    8. Chang, C-L. & Jiménez-Martín, J.A. & Maasoumi, E. & McAleer, M.J., 2015. "Choosing Expected Shortfall over VaR in Basel III Using Stochastic Dominance," Econometric Institute Research Papers EI2015-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. Chang, C-L. & Jiménez-Martín, J.A. & McAleer, M.J. & Pérez-Amaral, T., 2015. "A Stochastic Dominance Approach to the Basel III Dilemma: Expected Shortfall or VaR?," Econometric Institute Research Papers EI2015-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Stavros Stavroyiannis, 2017. "A note on the Nelson Cao inequality constraints in the GJR-GARCH model: Is there a leverage effect?," Papers 1705.00535, arXiv.org.
    12. Michael McAleer & Juan-à ngel Jiménez-Martín & Teodosio Pérez-Amaral, 2011. "International Evidence on GFC-robust Forecasts for Risk Management under the Basel Accord," KIER Working Papers 757, Kyoto University, Institute of Economic Research.
    13. Ahmed, Shamim & Valente, Giorgio, 2015. "Understanding the price of volatility risk in carry trades," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 118-129.
    14. Abad, Pilar & Benito, Sonia, 2013. "A detailed comparison of value at risk estimates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 258-276.
    15. Roberto Casarin & Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures," Documentos de Trabajo del ICAE 2011-32, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    16. Caporin, Massimiliano & Velo, Gabriel G., 2015. "Realized range volatility forecasting: Dynamic features and predictive variables," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 98-112.

  49. Massimiliano Caporin & Juliusz Pres' & Hipolit Torro, 2010. "Model Based Monte Carlo Pricing of Energy and Temperature Quanto Options," "Marco Fanno" Working Papers 0123, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Lunina, Veronika, 2016. "Joint Modelling of Power Price, Temperature, and Hydrological Balance with a View towards Scenario Analysis," Working Papers 2016:30, Lund University, Department of Economics.
    2. Fred Espen Benth, 2021. "Pricing of Commodity and Energy Derivatives for Polynomial Processes," Mathematics, MDPI, vol. 9(2), pages 1-30, January.
    3. Fred Espen Benth & Paul Kruhner, 2014. "Derivatives pricing in energy markets: an infinite dimensional approach," Papers 1412.7943, arXiv.org.
    4. Angelica Gianfreda & Derek Bunn, 2018. "A Stochastic Latent Moment Model for Electricity Price Formation," BEMPS - Bozen Economics & Management Paper Series BEMPS46, Faculty of Economics and Management at the Free University of Bozen.
    5. Cui, Hairong & Zhou, Ying & Dzandu, Michael D. & Tang, Yinshan & Lu, Xunfa, 2019. "Is temperature-index derivative suitable for China?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    6. Aur'elien Alfonsi & Nerea Vadillo, 2023. "Risk valuation of quanto derivatives on temperature and electricity," Papers 2310.07692, arXiv.org, revised Apr 2024.
    7. Massimiliano Caporin & Fulvio Fontini & Paolo Santucci De Magistris, 2017. "Price convergence within and between the Italian electricity day-ahead and dispatching services markets," "Marco Fanno" Working Papers 0215, Dipartimento di Scienze Economiche "Marco Fanno".
    8. Yuji Yamada & Takuji Matsumoto, 2023. "Construction of Mixed Derivatives Strategy for Wind Power Producers," Energies, MDPI, vol. 16(9), pages 1-26, April.
    9. Baltuttis, Dennik & Töppel, Jannick & Tränkler, Timm & Wiethe, Christian, 2020. "Managing the risks of energy efficiency insurances in a portfolio context: An actuarial diversification approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    10. Laura Casula & Guglielmo D’Amico & Giovanni Masala & Filippo Petroni, 2020. "Performance estimation of photovoltaic energy production," Letters in Spatial and Resource Sciences, Springer, vol. 13(3), pages 267-285, December.
    11. Thakur, Jagruti & Hesamzadeh, Mohammad Reza & Date, Paresh & Bunn, Derek, 2023. "Pricing and hedging wind power prediction risk with binary option contracts," Energy Economics, Elsevier, vol. 126(C).
    12. Rodwell Kufakunesu & Farai Mhlanga, 2018. "On the sensitivity analysis of energy quanto options," Papers 1810.06335, arXiv.org.
    13. Mosquera-López, Stephania & Uribe, Jorge M., 2022. "Pricing the risk due to weather conditions in small variable renewable energy projects," Applied Energy, Elsevier, vol. 322(C).
    14. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Modeling and Pricing in Financial Markets for Weather Derivatives," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8457, June.
    15. Khalifa, Ahmed & Caporin, Massimiliano & Hammoudeh, Shawkat, 2015. "Spillovers between energy and FX markets: The importance of asymmetry, uncertainty and business cycle," Energy Policy, Elsevier, vol. 87(C), pages 72-82.
    16. Giovanni Masala & Marco Micocci & Andrea Rizk, 2022. "Hedging Wind Power Risk Exposure through Weather Derivatives," Energies, MDPI, vol. 15(4), pages 1-30, February.

  50. Michael McAleer & Massimiliano Caporin, 2010. "Thresholds, News Impact Surfaces and Dynamic Asymmetric Multivariate GARCH," Working Papers in Economics 10/32, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars & VIOLANTE, Francesco, 2012. "The value of multivariate model sophistication: an application to pricing Dow Jones Industrial Average options," LIDAM Discussion Papers CORE 2012003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. 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.
    3. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    4. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira Da Veiga, María Helena, 2013. "One for all : nesting asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws131110, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Oscar Espinosa & Fabio Nieto, 2020. "A study on the leverage effect on financial series using a TAR model: a Bayesian approach," Papers 2002.05319, arXiv.org, revised Feb 2020.
    6. Asai, Manabu & McAleer, Michael, 2008. "A Portfolio Index GARCH model," International Journal of Forecasting, Elsevier, vol. 24(3), pages 449-461.
    7. Alexander HARIN, 2014. "Partially Unforeseen Events. Corrections and Correcting Formulae for Forecasts," Expert Journal of Economics, Sprint Investify, vol. 2(2), pages 69-79.
    8. Harin, Alexander, 2014. "General correcting formulae for forecasts," MPRA Paper 55283, University Library of Munich, Germany.

  51. Massimiliano Caporin & Michael McAleer, 2010. "Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models," Working Papers in Economics 10/06, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2010. "Analyzing and Forecasting Volatility Spillovers and Asymmetries in Major Crude Oil Spot, Forward and Futures Markets," KIER Working Papers 717, Kyoto University, Institute of Economic Research.
    2. Rasmus Søndergaard Pedersen, 2014. "Targeting estimation of CCC-Garch models with infinite fourth moments," Discussion Papers 14-04, University of Copenhagen. Department of Economics.
    3. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About the Dynamic Conditional Correlation Representation," Working Papers in Economics 13/21, University of Canterbury, Department of Economics and Finance.
    4. Rodrigue Dossou-Cadja, 2024. "The 1992-93 EMS Crisis and the South: Lessons from the Franc Zone System and the 1994 CFA Franc Devaluation," Working Papers 0246, European Historical Economics Society (EHES).
    5. Michael McAleer & Juan-Ángel Jiménez-Martín & Teodosio Pérez Amaral, 2012. "Has the Basel Accord Improved Risk Management During the Global Financial Crisis?," Documentos de Trabajo del ICAE 2012-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Oct 2012.
    6. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "Connecting VIX and Stock Index ETF," Tinbergen Institute Discussion Papers 16-010/III, Tinbergen Institute, revised 23 Jan 2017.
    7. Manabu Asai & Michael McAleer, 2013. "A Fractionally Integrated Wishart Stochastic Volatility Model," Tinbergen Institute Discussion Papers 13-025/III, Tinbergen Institute.
    8. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2010. "Analyzing and Forecasting Volatility Spillovers, Asymmetries and Hedging in Major Oil Markets," Working Papers in Economics 10/19, University of Canterbury, Department of Economics and Finance.
    9. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About DCC," Documentos de Trabajo del ICAE 2013-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    10. Asl, Mahdi Ghaemi & Canarella, Giorgio & Miller, Stephen M., 2021. "Dynamic asymmetric optimal portfolio allocation between energy stocks and energy commodities: Evidence from clean energy and oil and gas companies," Resources Policy, Elsevier, vol. 71(C).
    11. Chang, C-L. & McAleer, M.J. & Wang, Y., 2016. "Testing Co-Volatility Spillovers for Natural Gas Spot, Futures and ETF Spot using Dynamic Conditional Covariances," Econometric Institute Research Papers EI2016-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Guglielmo Maria Caporale & John Hunter & Faek Menla Ali, 2013. "On the Linkages between Stock Prices and Exchange Rates: Evidence from the Banking Crisis of 2007-2010," CESifo Working Paper Series 4189, CESifo.
    13. Chia-Lin Chang & Juan-à ngel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2011. "The Rise and Fall of S&P500 Variance Futures," KIER Working Papers 795, Kyoto University, Institute of Economic Research.
    14. Hafner, Christian M. & Wang, Linqi, 2023. "A dynamic conditional score model for the log correlation matrix," Journal of Econometrics, Elsevier, vol. 237(2).
    15. Martin T. Bohl, Badye Essid, Pierre Siklos, 2018. "Short-Selling Bans and the Global Financial Crisis: Are they Inter-Connected?," LCERPA Working Papers 0112, Laurier Centre for Economic Research and Policy Analysis, revised 30 Jan 2018.
    16. Lerskullawat, Polwat, 2019. "Hedging Effectiveness on the Thailand Futures Exchange Market," Asian Journal of Applied Economics, Kasetsart University, Center for Applied Economics Research, vol. 26(2), December.
    17. David E. Allen & Michael McAleer & Robert Powell & Abhay K. Singh, 2013. "A Non-Parametric and Entropy Based Analysis of the Relationship between the VIX and S&P 500," Tinbergen Institute Discussion Papers 13-018/III, Tinbergen Institute.
    18. Carlo Drago & Andrea Scozzari, 2022. "Evaluating conditional covariance estimates via a new targeting approach and a networks-based analysis," Papers 2202.02197, arXiv.org.
    19. Tsionas, Mike G. & Philippas, Dionisis & Philippas, Nikolaos, 2022. "Multivariate stochastic volatility for herding detection: Evidence from the energy sector," Energy Economics, Elsevier, vol. 109(C).
    20. Louzis, Dimitrios & Vouldis, Angelos, 2013. "A financial systemic stress index for Greece," Working Paper Series 1563, European Central Bank.
    21. Alexandridis, G. & Sahoo, S. & Visvikis, I., 2017. "Economic information transmissions and liquidity between shipping markets: New evidence from freight derivatives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 98(C), pages 82-104.
    22. Shawkat M. Hammoudeh & Yuan Yuan & Michael McAleer, 2010. "Exchange Rate and Industrial Commodity Volatility Transmissions, Asymmetries and Hedging Strategies," CIRJE F-Series CIRJE-F-741, CIRJE, Faculty of Economics, University of Tokyo.
    23. Jamal Bouoiyour, Refk Selmi, 2019. "Brexit and CDS spillovers across UK and Europe," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 16(1), pages 105-124, June.
    24. Chia-Lin Chang & Hui-Kuang Hsu & Michael McAleer, 2013. "Is Small Beautiful? Size Effects of Volatility Spillovers for Firm Performance and Exchange Rates in Tourism," Documentos de Trabajo del ICAE 2013-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    25. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    26. Chia-Lin Chang & Michael McAleer & Yu-Ann Wang, 2016. "Modelling Volatility Spillovers for Bio-ethanol, Sugarcane and Corn Spot and Futures Prices," Tinbergen Institute Discussion Papers 16-014/III, Tinbergen Institute, revised 30 Jan 2017.
    27. Asai, M. & Caporin, M. & McAleer, M.J., 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Econometric Institute Research Papers EI 2012-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    28. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    29. Athanasios Tsagkanos & Konstantinos Gkillas & Christoforos Konstantatos & Christos Floros, 2021. "Does Trading Volume Drive Systemic Banks’ Stock Return Volatility? Lessons from the Greek Banking System," IJFS, MDPI, vol. 9(2), pages 1-13, April.
    30. Chang, C-L. & Hsieh, T-L. & McAleer, M.J., 2018. "Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK," Econometric Institute Research Papers EI2018-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    31. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    32. Hussein Hassan & Minko Markovski & Alexander Mihailov, 2022. "COVID-19 Cases and Stock Prices by Sector in Major Economies: What Do We Learn from the Daily Data?," Economics Discussion Papers em-dp2022-04, Department of Economics, University of Reading.
    33. HAFNER Christian, & HERWARTZ Helmut, & MAXAND Simone,, 2018. "Identification of structural multivariate GARCH models," LIDAM Discussion Papers CORE 2018020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    34. Luke De Clerk & Sergey Savel'ev, 2021. "Non-stationary GARCH modelling for fitting higher order moments of financial series within moving time windows," Papers 2102.11627, arXiv.org, revised Mar 2021.
    35. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & Lingbo Li & David Martinez-Regoband & Fan Wu, 2020. "Cryptocurrency Trading: A Comprehensive Survey," Papers 2003.11352, arXiv.org, revised Jan 2022.
    36. Moawia Alghalith & Christos Floros & Konstantinos Gkillas, 2020. "Estimating Stochastic Volatility under the Assumption of Stochastic Volatility of Volatility," Risks, MDPI, vol. 8(2), pages 1-15, April.
    37. Chang, C-L. & McAleer, M.J. & Wang, Y-A., 2016. "Modelling Volatility Spillovers for Bio-ethanol, Sugarcane and Corn," Econometric Institute Research Papers EI2016-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    38. Chia-Lin Chang & Michael Mcaleer, 2012. "Aggregation, Heterogeneous Autoregression And Volatility Of Daily International Tourist Arrivals And Exchange Rates," The Japanese Economic Review, Japanese Economic Association, vol. 63(3), pages 397-419, September.
    39. Caporale, Guglielmo Maria & Menla Ali, Faek & Spagnolo, Nicola, 2015. "Exchange rate uncertainty and international portfolio flows: A multivariate GARCH-in-mean approach," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 70-92.
    40. Adams, Zeno & Fuess, Roland & Glueck, Thorsten, 2016. "Are Correlations Constant? Empirical and Theoretical Results on Popular Correlation Models in Finance," Working Papers on Finance 1613, University of St. Gallen, School of Finance.
    41. Sayantan Bandhu Majumder & Ranjanendra Narayan Nag, 2018. "Shock and Volatility Spillovers Among Equity Sectors of the National Stock Exchange in India," Global Business Review, International Management Institute, vol. 19(1), pages 227-240, February.
    42. Alina Zaharia, 2021. "Estimation of Correlation between Capital Markets. Analysing the case of Central and Eastern European markets in the context of the COVID-19 pandemic," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 13(1), pages 61-78, June.
    43. Chia-Lin Chang & Michael McAleer & Guangdong Zuo, 2017. "Volatility Spillovers and Causality of Carbon Emissions, Oil and Coal Spot and Futures for the EU and USA," Tinbergen Institute Discussion Papers 17-051/III, Tinbergen Institute.
    44. Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
    45. Syed Kumail Abbas Rizvi & Bushra Naqvi & Nawazish Mirza, 2022. "Is green investment different from grey? Return and volatility spillovers between green and grey energy ETFs," Annals of Operations Research, Springer, vol. 313(1), pages 495-524, June.
    46. Yudong Wang & Li Liu, 2016. "Crude oil and world stock markets: volatility spillovers, dynamic correlations, and hedging," Empirical Economics, Springer, vol. 50(4), pages 1481-1509, June.
    47. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
    48. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2013. "Conditional correlations and volatility spillovers between crude oil and stock index returns," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 116-138.
    49. Michael McAleer, 2019. "What They Did Not Tell You about Algebraic (Non-) Existence, Mathematical (IR-)Regularity, and (Non-) Asymptotic Properties of the Dynamic Conditional Correlation (DCC) Model," JRFM, MDPI, vol. 12(2), pages 1-9, April.
    50. Khalfaoui, R & Boutahar, M, 2012. "Portfolio risk evaluation: An approach based on dynamic conditional correlations models and wavelet multiresolution analysis," MPRA Paper 41624, University Library of Munich, Germany.
    51. Pan, Zhiyuan & Wang, Yudong & Yang, Li, 2014. "Hedging crude oil using refined product: A regime switching asymmetric DCC approach," Energy Economics, Elsevier, vol. 46(C), pages 472-484.
    52. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    53. Aielli, Gian Piero & Caporin, Massimiliano, 2014. "Variance clustering improved dynamic conditional correlation MGARCH estimators," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 556-576.
    54. Christian Francq & Jean-Michel Zakoïan, 2016. "Estimating multivariate volatility models equation by equation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 613-635, June.
    55. Moawia Alghalith, 2022. "Methods in Econophysics: Estimating the Probability Density and Volatility," Papers 2301.10178, arXiv.org.
    56. Marcelo Brutti Righi & Paulo Sergio Ceretta, 2011. "Extreme values dependence of risk in Latin American markets," Economics Bulletin, AccessEcon, vol. 31(4), pages 2903-2914.
    57. Syed Abul, Basher & Perry, Sadorsky, 2015. "Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH," MPRA Paper 68231, University Library of Munich, Germany.
    58. Heidari, Hassan & Ebrahimi Torki, Mahyar & Babaei Balderlou, Saharnaz, 2015. "How Do Different Oil Price Shocks Affect the Relationship Between Oil and Stock Markets?," MPRA Paper 80273, University Library of Munich, Germany, revised 24 Dec 2016.
    59. Burda Martin, 2015. "Constrained Hamiltonian Monte Carlo in BEKK GARCH with Targeting," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 1-19, January.
    60. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    61. Aielli, Gian Piero & Caporin, Massimiliano, 2013. "Fast clustering of GARCH processes via Gaussian mixture models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 205-222.
    62. Bauwens, Luc & Grigoryeva, Lyudmila & Ortega, Juan-Pablo, 2016. "Estimation and empirical performance of non-scalar dynamic conditional correlation models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 17-36.
    63. Zhang, Wenting & He, Xie & Hamori, Shigeyuki, 2022. "Volatility spillover and investment strategies among sustainability-related financial indexes: Evidence from the DCC-GARCH-based dynamic connectedness and DCC-GARCH t-copula approach," International Review of Financial Analysis, Elsevier, vol. 83(C).
    64. Wen, Xiaoqian & Guo, Yanfeng & Wei, Yu & Huang, Dengshi, 2014. "How do the stock prices of new energy and fossil fuel companies correlate? Evidence from China," Energy Economics, Elsevier, vol. 41(C), pages 63-75.
    65. Lakshina, Valeriya, 2014. "Is it possible to break the «curse of dimensionality»? Spatial specifications of multivariate volatility models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 36(4), pages 61-78.
    66. Gatfaoui, Hayette, 2013. "Translating financial integration into correlation risk: A weekly reporting's viewpoint for the volatility behavior of stock markets," Economic Modelling, Elsevier, vol. 30(C), pages 776-791.
    67. Tsang, Andrew & Yiu, Matthew S. & Nguyen, Huy Toan, 2021. "Spillover across sovereign bond markets between the US and ASEAN4 economies," Journal of Asian Economics, Elsevier, vol. 76(C).
    68. R. REYTIER & A. Blanes & Q. Gaucher & S. Thiam & P. Debled, 2015. "Behavior of Covariance Matrices with Equi-Correlation Approach," Proceedings of International Academic Conferences 2805027, International Institute of Social and Economic Sciences.
    69. Boldanov, Rustam & Degiannakis, Stavros & Filis, George, 2017. "Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries," MPRA Paper 80435, University Library of Munich, Germany.
    70. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "How are VIX and Stock Index ETF Related?," Documentos de Trabajo del ICAE 2016-02, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    71. V. Lakshina V. & K. Lapshina A. & В. Лакшина В. & К. Лапшина А., 2016. "Сравнительный Анализ Стратегий Хеджирования Фьючерсами Портфеля Ценных Бумаг // Comparative Analysis Of Strategies For Hedging A Securities Portfolio With Futures," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 20(5), pages 105-114.
    72. Jung-Bin Su, 2020. "The Implementation of Asset Allocation Approaches: Theory and Evidence," Sustainability, MDPI, vol. 12(17), pages 1-28, September.
    73. Katsiampa, Paraskevi, 2019. "An empirical investigation of volatility dynamics in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 50(C), pages 322-335.
    74. David C Broadstock & Hong Cao & Dayong Zhang, 2012. "Oil Shocks and their Impact on Energy Related Stocks in China," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 137, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    75. Katsiampa, Paraskevi & Yarovaya, Larisa & Zięba, Damian, 2022. "High-frequency connectedness between Bitcoin and other top-traded crypto assets during the COVID-19 crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    76. Carlo Drago & Andrea Scozzari, 2023. "A Network-Based Analysis for Evaluating Conditional Covariance Estimates," Mathematics, MDPI, vol. 11(2), pages 1-19, January.
    77. Tsouknidis, Dimitris A., 2016. "Dynamic volatility spillovers across shipping freight markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 90-111.
    78. Caporina, Massimiliano & Costola, Michele, 2021. "Time-varying granger causality tests for applications in global crude oil markets: A study on the DCC-MGARCH Hong test," SAFE Working Paper Series 324, Leibniz Institute for Financial Research SAFE.
    79. De Blasis, Riccardo & Galati, Luca & Webb, Alexander & Webb, Robert I., 2022. "Intelligent design: Stablecoins (in)stability and collateral during market turbulence," Economics & Statistics Discussion Papers esdp22088, University of Molise, Department of Economics.
    80. Ashfaq, Saleha & Tang, Yong & Maqbool, Rashid, 2019. "Volatility spillover impact of world oil prices on leading Asian energy exporting and importing economies’ stock returns," Energy, Elsevier, vol. 188(C).
    81. Katsiampa, Paraskevi, 2019. "Volatility co-movement between Bitcoin and Ether," Finance Research Letters, Elsevier, vol. 30(C), pages 221-227.
    82. Pier Francesco Procacci & Tomaso Aste, 2022. "Portfolio optimization with sparse multivariate modeling," Journal of Asset Management, Palgrave Macmillan, vol. 23(6), pages 445-465, October.
    83. Fengming Qin & Junru Zhang & Zhaoyong Zhang, 2018. "RMB Exchange Rates and Volatility Spillover across Financial Markets in China and Japan," Risks, MDPI, vol. 6(4), pages 1-26, October.
    84. Ana I. Sanjuán-López & Philip J. Dawson, 2017. "Volatility Effects of Index Trading and Spillovers on US Agricultural Futures Markets: A Multivariate GARCH Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(3), pages 822-838, September.
    85. Lv, Xin & Lien, Donald & Yu, Chang, 2020. "Who affects who? Oil price against the stock return of oil-related companies: Evidence from the U.S. and China," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 85-100.
    86. Dimitrios Vortelinos & Konstantinos Gkillas (Gillas) & Costas Syriopoulos & Argyro Svingou, 2017. "Asymmetric and nonlinear inter-relations of US stock indices," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 14(1), pages 78-129, December.
    87. Afees A. Salisu & Kazeem Isah, 2017. "Modeling the spillovers between stock market and money market in Nigeria," Working Papers 023, Centre for Econometric and Allied Research, University of Ibadan.
    88. Hussein Hassan & Minko Markovski & Alexander Mihailov, 2023. "A TGARCH Quantification of the Average Effect of COVID-19 Cases on Share Prices by Sector: Comparing the US and the UK," Economics Discussion Papers em-dp2023-15, Department of Economics, University of Reading.
    89. Kusen, Alex & Rudolf, Markus, 2019. "Feedback trading: Strategies during day and night with global interconnectedness," Research in International Business and Finance, Elsevier, vol. 48(C), pages 438-463.
    90. Galati, Luca & Capalbo, Francesco, 2024. "Silicon Valley Bank bankruptcy and Stablecoins stability," International Review of Financial Analysis, Elsevier, vol. 91(C).
    91. Dimitrios Thomakos & Johannes Klepsch & Dimitris N. Politis, 2020. "Model Free Inference on Multivariate Time Series with Conditional Correlations," Stats, MDPI, vol. 3(4), pages 1-26, November.
    92. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 316-339.
    93. Caporin, Massimiliano & Costola, Michele, 2022. "Time-varying Granger causality tests in the energy markets: A study on the DCC-MGARCH Hong test," Energy Economics, Elsevier, vol. 111(C).
    94. 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.
    95. Filippidis, Michail & Filis, George & Kizys, Renatas, 2020. "Oil price shocks and EMU sovereign yield spreads," Energy Economics, Elsevier, vol. 86(C).
    96. Jessica Leutert, 2018. "The Swiss franc safety premium," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-21, December.
    97. Massimo Peri & Daniela Vandone & Lucia Baldi, 2017. "Volatility Spillover between Water, Energy and Food," Sustainability, MDPI, vol. 9(6), pages 1-16, June.
    98. Berger, T. & Missong, M., 2014. "Financial crisis, Value-at-Risk forecasts and the puzzle of dependency modeling," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 33-38.

  52. Massimiliano Caporin & Paolo Paruolo, 2009. "Structured Multivariate Volatility Models," "Marco Fanno" Working Papers 0091, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 12/06, University of Canterbury, Department of Economics and Finance.
    2. Caporin, M. & McAleer, M.J., 2010. "Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models," Econometric Institute Research Papers EI 2010-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," CIRJE F-Series CIRJE-F-638, CIRJE, Faculty of Economics, University of Tokyo.
    4. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
    5. Caporin, Massimiliano & Jimenez-Martin, Juan-Angel & Gonzalez-Serrano, Lydia, 2014. "Currency hedging strategies in strategic benchmarks and the global and Euro sovereign financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 159-177.
    6. Michael McAleer & Massimiliano Caporin, 2011. "Ranking Multivariate GARCH Models by Problem Dimension:An Empirical Evaluation," KIER Working Papers 778, Kyoto University, Institute of Economic Research.
    7. Lakshina, Valeriya, 2014. "Is it possible to break the «curse of dimensionality»? Spatial specifications of multivariate volatility models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 36(4), pages 61-78.

  53. Massimiliano Caporin & Michael McAleer, 2009. "A Scientific Classification of Volatility Models," Documentos de Trabajo del ICAE 2009-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

    Cited by:

    1. Liang, Chao & Xia, Zhenglan & Lai, Xiaodong & Wang, Lu, 2022. "Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model," Energy Economics, Elsevier, vol. 116(C).
    2. Caporin, Massimiliano & Jimenez-Martin, Juan-Angel & Gonzalez-Serrano, Lydia, 2014. "Currency hedging strategies in strategic benchmarks and the global and Euro sovereign financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 159-177.
    3. Alexander HARIN, 2014. "Partially Unforeseen Events. Corrections and Correcting Formulae for Forecasts," Expert Journal of Economics, Sprint Investify, vol. 2(2), pages 69-79.
    4. Harin, Alexander, 2014. "General correcting formulae for forecasts," MPRA Paper 55283, University Library of Munich, Germany.

  54. Massimiliano Caporin & Francesco Lisi, 2009. "Comparing and selecting performance measures for ranking assets," "Marco Fanno" Working Papers 0099, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Marco Taboga, 2014. "The Riskiness of Corporate Bonds," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(4), pages 693-713, June.
    2. Yildiz Selim & Abdelbari El Khamlichi, 2017. "The Performance Ranking of Emerging Markets Islamic Indices Using Risk Adjusted Performance Measures," Post-Print hal-01653400, HAL.
    3. León, Ángel & Moreno, Manuel, 2015. "Lower Partial Moments under Gram Charlier Distribution: Performance Measures and Efficient Frontiers," QM&ET Working Papers 15-3, University of Alicante, D. Quantitative Methods and Economic Theory.
    4. Monica Billio & Massimiliano Caporin & Michele Costola, 2012. "Backward/forward optimal combination of performance measures for equity screening," Working Papers 2012_13, Department of Economics, University of Venice "Ca' Foscari".
    5. Anand, Abhinav & Li, Tiantian & Kurosaki, Tetsuo & Kim, Young Shin, 2016. "Foster–Hart optimal portfolios," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 117-130.
    6. Korn, Olaf & Möller, Philipp M. & Schwehm, Christian, 2019. "Drawdown measures: Are they all the same?," CFR Working Papers 19-04, University of Cologne, Centre for Financial Research (CFR).
    7. López, Raquel & Esparcia, Carlos, 2021. "Analysis of the performance of volatility-based trading strategies on scheduled news announcement days: An international equity market perspective," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 32-54.
    8. Mohammad Reza Tavakoli Baghdadabad & Paskalis Glabadanidis, 2013. "Average Drawdown Risk and Capital Asset Pricing," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1-21.

  55. Matteo Bonato & Massimiliano Caporin & Angelo Ranaldo, 2009. "Forecasting realized (co)variances with a block structure Wishart autoregressive model," Working Papers 2009-03, Swiss National Bank.

    Cited by:

    1. Fengler, Matthias R. & Gisler, Katja I. M., 2014. "A variance spillover analysis without covariances: what do we miss?," Economics Working Paper Series 1409, University of St. Gallen, School of Economics and Political Science.
    2. Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
    3. Chiriac, Roxana & Voev, Valeri, 2008. "Modelling and forecasting multivariate realized volatility," CoFE Discussion Papers 08/06, University of Konstanz, Center of Finance and Econometrics (CoFE).
    4. Varneskov, Rasmus & Voev, Valeri, 2013. "The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 83-95.
    5. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    6. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," CIRJE F-Series CIRJE-F-638, CIRJE, Faculty of Economics, University of Tokyo.
    7. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
    8. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    9. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    10. BAUWENS, Luc & STORTI, Giuseppe, 2013. "Computationally efficient inference procedures for vast dimensional realized covariance models," LIDAM Reprints CORE 2469, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Michael McAleer & Massimiliano Caporin, 2011. "Ranking Multivariate GARCH Models by Problem Dimension:An Empirical Evaluation," KIER Working Papers 778, Kyoto University, Institute of Economic Research.
    12. Hautsch, Nikolaus & Kyj, Lada M. & Hautsch, Nikolaus, 2009. "A blocking and regularization approach to high dimensional realized covariance estimation," CFS Working Paper Series 2009/20, Center for Financial Studies (CFS).
    13. BAUWENS, Luc & STORTI, Giuseppe & VIOLANTE, Francesco, 2012. "Dynamic conditional correlation models for realized covariance matrices," LIDAM Discussion Papers CORE 2012060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2010. "The conditional autoregressive wishart model for multivariate stock market volatility," Economics Working Papers 2010-07, Christian-Albrechts-University of Kiel, Department of Economics.
    15. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.

  56. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," CARF F-Series CARF-F-156, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

    Cited by:

    1. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2010. "Analyzing and Forecasting Volatility Spillovers and Asymmetries in Major Crude Oil Spot, Forward and Futures Markets," KIER Working Papers 717, Kyoto University, Institute of Economic Research.
    2. Michael McAleer & Juan-Ángel Jiménez-Martín & Teodosio Pérez Amaral, 2012. "Has the Basel Accord Improved Risk Management During the Global Financial Crisis?," Documentos de Trabajo del ICAE 2012-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Oct 2012.
    3. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2010. "Analyzing and Forecasting Volatility Spillovers, Asymmetries and Hedging in Major Oil Markets," Working Papers in Economics 10/19, University of Canterbury, Department of Economics and Finance.
    4. Shawkat M. Hammoudeh & Yuan Yuan & Michael McAleer, 2009. "Exchange Rate and Industrial Commodity Volatility Transmissions and Hedging Strategies," CIRJE F-Series CIRJE-F-668, CIRJE, Faculty of Economics, University of Tokyo.
    5. Shawkat Hammoudeh & Yuan Yuan & Michael McAleer & Mark A. Thompson, 2009. "Precious Metals-Exchange Rate Volatility Transmissions and Hedging Strategies," CARF F-Series CARF-F-187, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    6. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "Has the Basel II Accord Encouraged Risk Management During the 2008-09 Financial Crisis?," CIRJE F-Series CIRJE-F-643, CIRJE, Faculty of Economics, University of Tokyo.
    7. Caporin, M. & McAleer, M.J., 2010. "Threshold, news impact surfaces and dynamic asymmetric multivariate GARCH," Econometric Institute Research Papers EI 2010-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 12/06, University of Canterbury, Department of Economics and Finance.
    9. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2009. "Modelling Conditional Correlations for Risk Diversification in Crude Oil Markets," CIRJE F-Series CIRJE-F-640, CIRJE, Faculty of Economics, University of Tokyo.
    10. Shawkat M. Hammoudeh & Yuan Yuan & Michael McAleer, 2010. "Exchange Rate and Industrial Commodity Volatility Transmissions, Asymmetries and Hedging Strategies," CIRJE F-Series CIRJE-F-741, CIRJE, Faculty of Economics, University of Tokyo.
    11. M. Angeles Carnero Fernández & M. Hakan Eratalay, 2012. "Estimating VAR-MGARCH models in multiple steps," Working Papers. Serie AD 2012-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    12. Roengchai Tansuchat & Chia-Lin Chang & Michael McAleer, 2010. "Crude Oil Hedging Strategies Using Dynamic Multivariate GARCH," Working Papers in Economics 10/03, University of Canterbury, Department of Economics and Finance.
    13. Awartani, Basel & Maghyereh, Aktham Issa, 2013. "Dynamic spillovers between oil and stock markets in the Gulf Cooperation Council Countries," Energy Economics, Elsevier, vol. 36(C), pages 28-42.
    14. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Yoon, Seong-Min, 2014. "Dynamic spillovers among major energy and cereal commodity prices," Energy Economics, Elsevier, vol. 43(C), pages 225-243.
    15. Caporin, M. & McAleer, M.J., 2010. "Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models," Econometric Institute Research Papers EI 2010-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Weiping Li & Wenwen Liu, 2021. "Investor sentiment‐styled index in index futures market," Review of Financial Economics, John Wiley & Sons, vol. 39(1), pages 51-72, January.
    17. Chia-Lin Chang & Michael Mcaleer, 2012. "Aggregation, Heterogeneous Autoregression And Volatility Of Daily International Tourist Arrivals And Exchange Rates," The Japanese Economic Review, Japanese Economic Association, vol. 63(3), pages 397-419, September.
    18. Massimiliano Caporin & Michael McAleer, 2010. "Model Selection and Testing of Conditional and Stochastic Volatility Models," Working Papers in Economics 10/58, University of Canterbury, Department of Economics and Finance.
    19. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2009. "Forecasting Volatility and Spillovers in Crude Oil Spot, Forward and Futures Markets," CARF F-Series CARF-F-163, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    20. Michael McAleer, 2009. "The Ten Commandments for Optimizing Value-at-Risk and Daily Capital Charges," CIRJE F-Series CIRJE-F-652, CIRJE, Faculty of Economics, University of Tokyo.
    21. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
    22. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2013. "Conditional correlations and volatility spillovers between crude oil and stock index returns," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 116-138.
    23. Khalfaoui, R & Boutahar, M, 2012. "Portfolio risk evaluation: An approach based on dynamic conditional correlations models and wavelet multiresolution analysis," MPRA Paper 41624, University Library of Munich, Germany.
    24. Broadstock, David C. & Filis, George, 2014. "Oil price shocks and stock market returns: New evidence from the United States and China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 417-433.
    25. Michael McAleer & Massimiliano Caporin, 2011. "Ranking Multivariate GARCH Models by Problem Dimension:An Empirical Evaluation," KIER Working Papers 778, Kyoto University, Institute of Economic Research.
    26. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2009. "Volatility Spillovers Between Crude Oil Futures Returns and Oil Company Stocks Return," CIRJE F-Series CIRJE-F-639, CIRJE, Faculty of Economics, University of Tokyo.
    27. Abdul Hakim & Michael McAleer, 2009. "Dynamic Conditional Correlations in International Stock, Bond and Foreign Exchange Markets: Emerging Markets Evidence," CIRJE F-Series CIRJE-F-677, CIRJE, Faculty of Economics, University of Tokyo.
    28. Juan‐Ángel Jiménez‐Martín & Michael McAleer & Teodosio Pérez‐Amaral, 2009. "The Ten Commandments For Managing Value At Risk Under The Basel Ii Accord," Journal of Economic Surveys, Wiley Blackwell, vol. 23(5), pages 850-855, December.
    29. David C Broadstock & Hong Cao & Dayong Zhang, 2012. "Oil Shocks and their Impact on Energy Related Stocks in China," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 137, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    30. John Francis T. Diaz, 2018. "Volatility Dynamics in the ASEAN– China Free Trade Agreement," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(3), pages 287-306, December.
    31. Afees A. Salisu & Kazeem Isah, 2017. "Modeling the spillovers between stock market and money market in Nigeria," Working Papers 023, Centre for Econometric and Allied Research, University of Ibadan.

  57. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About the Dynamic Conditional Correlation Representation," Working Papers in Economics 13/21, University of Canterbury, Department of Economics and Finance.
    2. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About DCC," Documentos de Trabajo del ICAE 2013-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    3. Lord Mensah & Charles Andoh & Saint Kuttu & Eric Boachie-Yiadom, 2023. "The level of African forex markets integration and Eurobond issue," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(1), pages 232-250, March.
    4. Evzen Kocenda & Michala Moravcova, 2017. "Exchange Rate Co-movements, Hedging and Volatility Spillovers in New EU Forex Markets," Working Papers IES 2017/27, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2017.
    5. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2017. "The kidnapping of Europe: High-order moments' transmission between developed and emerging markets," Emerging Markets Review, Elsevier, vol. 31(C), pages 96-115.
    6. Cody Yu-Ling Hsiao & James Morley, 2015. "Debt and Financial Market Contagion," Discussion Papers 2015-02, School of Economics, The University of New South Wales.
    7. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    8. Zhang, Yue-Jun & Chevallier, Julien & Guesmi, Khaled, 2017. "“De-financialization” of commodities? Evidence from stock, crude oil and natural gas markets," Energy Economics, Elsevier, vol. 68(C), pages 228-239.
    9. 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.
    10. Haas, Markus & Liu, Ji-Chun, 2015. "Theory for a Multivariate Markov--switching GARCH Model with an Application to Stock Markets," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112855, Verein für Socialpolitik / German Economic Association.
    11. Campos-Martins, Susana & Amado, Cristina, 2022. "Financial market linkages and the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 123(C).
    12. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stober, 2016. "Regime switching vine copula models for global equity and volatility indices," Papers 1604.05598, arXiv.org.
    13. Joshua C.C. Chan & Cody Yu-Ling Hsiao & Renée A. Fry-McKibbin, 2013. "A Regime Switching Skew-normal Model for Measuring Financial Crisis and Contagion," CAMA Working Papers 2013-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Aboura Sofiane & Chevallier Julien & Jammazi Rania & Tiwari Aviral Kumar, 2016. "The place of gold in the cross-market dependencies," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(5), pages 567-586, December.
    15. Sofiane Aboura & Julien Chevallier, 2016. "Oil vs. gasoline: The dark side of volatility and taxation," Post-Print halshs-01348705, HAL.
    16. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    17. Renée Fry-McKibbin & Cody Hsiao & Chrismin Tang, 2014. "Contagion and Global Financial Crises: Lessons from Nine Crisis Episodes," Open Economies Review, Springer, vol. 25(3), pages 521-570, July.
    18. Chan Joshua C.C. & Fry-McKibbin Renée A. & Hsiao Cody Yu-Ling, 2019. "A regime switching skew-normal model of contagion," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(1), pages 1-24, February.
    19. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stöber, 2017. "Regime Switching Vine Copula Models for Global Equity and Volatility Indices," Econometrics, MDPI, vol. 5(1), pages 1-38, January.
    20. Shogbuyi, Abiodun & Steeley, James M., 2017. "The effect of quantitative easing on the variance and covariance of the UK and US equity markets," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 281-291.
    21. Jean-David Fermanian & Hassan Malongo, 2013. "On the Stationarity of Dynamic Conditional Correlation Models," Working Papers 2013-26, Center for Research in Economics and Statistics.
    22. Saart, Patrick W. & Xia, Yingcun, 2022. "Functional time series approach to analyzing asset returns co-movements," Journal of Econometrics, Elsevier, vol. 229(1), pages 127-151.
    23. Emanuele BACCHIOCCHI, 2015. "On the Identification of Interdependence and Contagion of Financial Crises," Departmental Working Papers 2015-12, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    24. Susana Martins & Cristina Amado, 2018. "Financial Market Contagion and the Sovereign Debt Crisis: A Smooth Transition Approach," NIPE Working Papers 08/2018, NIPE - Universidade do Minho.
    25. Singh, Vikkram & Roca, Eduardo & Li, Bin, 2021. "Effectiveness of policy interventions during financial crises in China and Russia: Lessons for the COVID-19 pandemic," Journal of Policy Modeling, Elsevier, vol. 43(2), pages 253-277.
    26. Aboura, Sofiane & Chevallier, Julien, 2015. "Geographical diversification with a World Volatility Index," Journal of Multinational Financial Management, Elsevier, vol. 30(C), pages 62-82.
    27. F. Benedetto & L. Mastroeni & P. Vellucci, 2021. "Modeling the flow of information between financial time-series by an entropy-based approach," Annals of Operations Research, Springer, vol. 299(1), pages 1235-1252, April.
    28. Jean-David Fermanian & Hassan Malongo, 2014. "On the stationarity of Dynamic Conditional Correlation models," Papers 1405.6905, arXiv.org, revised Mar 2016.
    29. Nasha Ananchotikul & Ms. Longmei Zhang, 2014. "Portfolio Flows, Global Risk Aversion and Asset Prices in Emerging Markets," IMF Working Papers 2014/156, International Monetary Fund.
    30. , & Hwa, Yen Siew & Chua, Soo Y. & Hooi, Lean Hooi, 2015. "Do Indian Economic Activities Impact ASEAN-5 Stock Markets?," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 49(2), pages 61-76.
    31. Nasha Ananchotikul & Longmei Zhang, 2016. "Portfolio Flows, Global Risk Aversion and Asset Prices in Emerging Markets," PIER Discussion Papers 36, Puey Ungphakorn Institute for Economic Research.

  58. Massimiliano Caporin & Juliusz Pres, 2008. "Forecasting temperature indices with timevarying long-memory models," "Marco Fanno" Working Papers 0088, Dipartimento di Scienze Economiche "Marco Fanno".

    Cited by:

    1. Massimiliano Caporin & Rangan Gupta, 2017. "Time-varying persistence in US inflation," Empirical Economics, Springer, vol. 53(2), pages 423-439, September.
    2. Caporin, Massimiliano & Preś, Juliusz, 2012. "Modelling and forecasting wind speed intensity for weather risk management," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3459-3476.

  59. Monica Billio & Massimiliano Caporin, 2007. "Market linkages, variance spillovers and correlation stability: empirical evidences of financial contagion," Working Papers 2007_18, Department of Economics, University of Venice "Ca' Foscari".

    Cited by:

    1. el Alaoui, AbdelKader O. & Ismath Bacha, Obiyathulla & Masih, Mansur & Asutay, Mehmet, 2017. "Leverage versus volatility: Evidence from the capital structure of European firms," Economic Modelling, Elsevier, vol. 62(C), pages 145-160.
    2. Jin, Xiaoye, 2015. "Volatility transmission and volatility impulse response functions among the Greater China stock markets," Journal of Asian Economics, Elsevier, vol. 39(C), pages 43-58.
    3. Brière, Marie & Chapelle, Ariane & Szafarz, Ariane, 2012. "No contagion, only globalization and flight to quality," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1729-1744.
    4. Afonso, António & Gomes, Pedro & Taamouti, Abderrahim, 2014. "Sovereign credit ratings, market volatility, and financial gains," Working Paper Series 1654, European Central Bank.
    5. Zied Ftiti & Aviral Tiwari & Amél Belanès & Khaled Guesmi, 2015. "Tests of Financial Market Contagion: Evolutionary Cospectral Analysis Versus Wavelet Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 46(4), pages 575-611, December.
    6. Wuyi Ye & Kebing Luo & Shaofu Du, 2014. "Measuring Contagion of Subprime Crisis Based on MVMQ-CAViaR Method," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-12, June.
    7. Caporin, Massimiliano & Malik, Farooq, 2020. "Do structural breaks in volatility cause spurious volatility transmission?," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 60-82.
    8. Carlo Drago & Andrea Scozzari, 2022. "Evaluating conditional covariance estimates via a new targeting approach and a networks-based analysis," Papers 2202.02197, arXiv.org.
    9. Lopes, José Mário & Nunes, Luis C., 2012. "A Markov regime switching model of crises and contagion: The case of the Iberian countries in the EMS," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 1141-1153.
    10. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".
    11. 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).
    12. Collet, Jerome & Ielpo, Florian, 2018. "Sector spillovers in credit markets," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 267-278.
    13. Noureddine Benlagha, 2014. "Volatility Linkage of Nominal and Index-linked Bond Returns: A Multivariate BEKK-GARCH Approach," Review of Economics & Finance, Better Advances Press, Canada, vol. 4, pages 49-60, November.
    14. Troug, Haytem Ahmed & Murray, Matt, 2015. "Crisis Determination and Financial Contagion: An Analysis of the Hong Kong and Tokyo Stock Markets using an MSBVAR Approach," MPRA Paper 68706, University Library of Munich, Germany.
    15. Ginanjar Dewandaru & Rumi Masih & Mansur Masih, 2018. "Unraveling the Financial Contagion in European Stock Markets During Financial Crises: Multi-Timescale Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(4), pages 859-880, March.
    16. Mehmet Balcilar & Rangan Gupta & Duc Khuong Nguyen & Mark E. Wohar, 2018. "Causal effects of the United States and Japan on Pacific-Rim stock markets: nonparametric quantile causality approach," Applied Economics, Taylor & Francis Journals, vol. 50(53), pages 5712-5727, November.
    17. Caporin, Massimiliano & Chang, Chia-Lin & McAleer, Michael, 2019. "Are the S&P 500 index and crude oil, natural gas and ethanol futures related for intra-day data?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 50-70.
    18. Mariem Talbi & Adel Boubaker & Saber Sebai, 2017. "Behavioral Finance and Financial Contagion: The Evidence of DCC-MGARCH Model From 63 Equity Markets," International Journal of Economics and Financial Issues, Econjournals, vol. 7(4), pages 387-407.
    19. Ferhat Camlica & Didem Gunes & Etkin Ozen, 2017. "A Financial Connectedness Analysis for Turkey," Working Papers 1719, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    20. Edson Z. Monte & Lucas B. Defanti, 2021. "Dynamic Interdependence and Volatility Transmission from the American to the Brazilian Stock Market," EERI Research Paper Series EERI RP 2021/09, Economics and Econometrics Research Institute (EERI), Brussels.
    21. Ana Escribano & Cristina Íñiguez, 2021. "The contagion phenomena of the Brexit process on main stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4462-4481, July.
    22. Kohonen, Anssi, 2013. "On detection of volatility spillovers in overlapping stock markets," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 140-158.
    23. Jung, R.C. & Maderitsch, R., 2014. "Structural breaks in volatility spillovers between international financial markets: Contagion or mere interdependence?," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 331-342.
    24. Hong, Yanran & Ma, Feng & Wang, Lu & Liang, Chao, 2022. "How does the COVID-19 outbreak affect the causality between gold and the stock market? New evidence from the extreme Granger causality test," Resources Policy, Elsevier, vol. 78(C).
    25. Shegorika Rajwani & Dilip Kumar, 2016. "Asymmetric Dynamic Conditional Correlation Approach to Financial Contagion: A Study of Asian Markets," Global Business Review, International Management Institute, vol. 17(6), pages 1339-1356, December.
    26. Konstantinos Tsiaras, 2020. "Contagion in Futures Metal Markets during the Recent Global Financial Crisis: Evidence from Gold, Silver, Copper, Zinc and Aluminium," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 70(3-4), pages 42-55, July-Dece.
    27. Hon-Wei Leow & Wee-Yeap Lau, 2018. "The Impact of Global Financial Crisis on IPO Underpricing in Malaysian Stock Market," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(04), pages 1-17, December.
    28. Kotkatvuori-Örnberg, Juha & Nikkinen, Jussi & Äijö, Janne, 2013. "Stock market correlations during the financial crisis of 2008–2009: Evidence from 50 equity markets," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 70-78.
    29. Gallegati, Marco, 2012. "A wavelet-based approach to test for financial market contagion," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3491-3497.
    30. Burzala, Milda Maria, 2016. "Contagion effects in selected European capital markets during the financial crisis of 2007–2009," Research in International Business and Finance, Elsevier, vol. 37(C), pages 556-571.
    31. Zied Ftiti & Aviral Tiwari & Amél Belanès & Khaled Guesmi, 2014. "Tests of Financial Market Contagion: Evolutionary Cospectral Analysis V.S. Wavelet Analysis," Working Papers 2014-577, Department of Research, Ipag Business School.
    32. António Afonso & João Tovar Jalles, 2020. "Economic volatility and sovereign yields’ determinants: a time-varying approach," Empirical Economics, Springer, vol. 58(2), pages 427-451, February.
    33. Bastian Gribisch, 2016. "Multivariate Wishart stochastic volatility and changes in regime," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 443-473, October.
    34. Guidolin, Massimo & Hansen, Erwin & Pedio, Manuela, 2019. "Cross-asset contagion in the financial crisis: A Bayesian time-varying parameter approach," Journal of Financial Markets, Elsevier, vol. 45(C), pages 83-114.
    35. Carlo Drago & Andrea Scozzari, 2023. "A Network-Based Analysis for Evaluating Conditional Covariance Estimates," Mathematics, MDPI, vol. 11(2), pages 1-19, January.
    36. Ndiweni, Zinzile Lorna & Bonga-Bonga, Lumengo, 2022. "Contagion or decoupling? Evidence from emerging stock markets," MPRA Paper 115170, University Library of Munich, Germany.
    37. Kohonen, Anssi, 2012. "Transmission of Government Default Risk in the Eurozone," MPRA Paper 43823, University Library of Munich, Germany.
    38. Veysov, Alexander, 2012. "Financial Contagion and Systemic Risk: From Theory to Applicable Macroeconomic Model," MPRA Paper 40612, University Library of Munich, Germany.
    39. Chang, Guang-Di & Chen, Chia-Shih, 2014. "Evidence of contagion in global REITs investment," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 148-158.
    40. Григорьев Р.А., 2019. "Одновременные Эффекты Несинхронных Временных Рядов: Проблемы Var-Модели," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 55(2), pages 118-129, апрель.
    41. Bolos, Bradut & Bacarea, Vladimir & Marusteri, Marius, 2011. "Approaching Economic Issues through Epidemiology–An Introduction to Business Epidemiology," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 257-276, March.
    42. Samet Gunay & Gokberk Can, 2022. "The source of financial contagion and spillovers: An evaluation of the covid-19 pandemic and the global financial crisis," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-20, January.
    43. Liu, Bin & Xiao, Wen & Zhu, Xingting, 2023. "How does inter-industry spillover improve the performance of volatility forecasting?," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    44. Alqaralleh, Huthaifa & Canepa, Alessandra & Chini, Zanetti, 2021. "Financial Contagion During the Covid-19 Pandemic: A Wavelet-Copula-GARCH Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202110, University of Turin.
    45. Lamo, Ana & Pérez, Javier J. & Schuknecht, Ludger, 2013. "Are government wages interlinked with private sector wages?," Journal of Policy Modeling, Elsevier, vol. 35(5), pages 697-712.
    46. el Alaoui, AbdelKader & Masih, Mansur & Bacha, Obiyathulla & Asutay, Mehmet, 2014. "Leverage, Sensitivity to Market Risk and Contagion: A Multi-Country Analysis for Shari’ah(Islamic) Stock Screening," MPRA Paper 57685, University Library of Munich, Germany.
    47. Charilaos Mertzanis & Noha Allam, 2018. "Political Instability and Herding Behaviour: Evidence from Egypt’s Stock Market," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(1), pages 29-59, April.
    48. Huthaifa Alqaralleh & Alessandra Canepa, 2021. "Evidence of Stock Market Contagion during the COVID-19 Pandemic: A Wavelet-Copula-GARCH Approach," JRFM, MDPI, vol. 14(7), pages 1-18, July.
    49. Dilip Kumar, 2019. "Structural Breaks in Volatility Transmission from Developed Markets to Major Asian Emerging Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(2), pages 172-209, August.
    50. Sarantis Tsiaplias & Chew Lian Chua, 2013. "A Multivariate GARCH Model Incorporating the Direct and Indirect Transmission of Shocks," Econometric Reviews, Taylor & Francis Journals, vol. 32(2), pages 244-271, February.
    51. Chua, Chew Lian & Suardi, Sandy & Tsiaplias, Sarantis, 2012. "An impulse-response function for a VAR with multivariate GARCH-in-Mean that incorporates direct and indirect transmission of shocks," Economics Letters, Elsevier, vol. 117(2), pages 452-454.
    52. Balli, Faruk & de Bruin, Anne & Chowdhury, Md Iftekhar Hasan, 2019. "Spillovers and the determinants in Islamic equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    53. Troug, Haytem Ahmed & Murray, Matt, 2015. "Quantitative Easing in Japan and the UK An Econometric Evaluation of the Impacts of Unconventional Monetary Policy on the Returns of Aggregate Output and Price Levels," MPRA Paper 68707, University Library of Munich, Germany.
    54. Erdem Kilic & Veysel Ulusoy, 2015. "Evidence for Financial Contagion in Endogenous Volatile Periods," Review of Development Economics, Wiley Blackwell, vol. 19(1), pages 62-74, February.
    55. Kumar, Dilip, 2017. "Realized volatility transmission from crude oil to equity sectors: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 149-167.

  60. Monica Billio & Massimiliano Caporin & Guido Cazzavillan, 2007. "Dating EU15 Monthly Business Cycle Jointly Using GDP and IPI," Working Papers 2007_19, Department of Economics, University of Venice "Ca' Foscari".

    Cited by:

    1. Monica Billio & Laurent Ferrara & Dominique Guegan & Gian Luigi Mazzi, 2009. "Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro area," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00423890, HAL.

  61. Massimiliano Caporin & Domenico Sartore, 2006. "Methodological aspects of time series back-calculation," Working Papers 2006_56, Department of Economics, University of Venice "Ca' Foscari".

    Cited by:

    1. Monica Billio & Massimiliano Caporin & Guido Cazzavillan, 2008. "Dating EU15 monthly business cycle jointly using GDP and IPI," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2007(3), pages 333-366.
    2. Terry Clark & Thomas Martin Key, 2021. "The methodologies of the marketing literature: mechanics, uses and craft," AMS Review, Springer;Academy of Marketing Science, vol. 11(3), pages 416-431, December.
    3. Monica Billio & Roberto Casarin, 2010. "Identifying business cycle turning points with sequential Monte Carlo methods: an online and real-time application to the Euro area," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 145-167.
    4. Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco & van Dijk, Herman K., 2012. "Combination schemes for turning point predictions," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(4), pages 402-412.
    5. Billio Monica & Casarin Roberto, 2011. "Beta Autoregressive Transition Markov-Switching Models for Business Cycle Analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(4), pages 1-32, September.
    6. Monica Billio & Laurent Ferrara & Dominique Guegan & Gian Luigi Mazzi, 2009. "Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro area," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00423890, HAL.

  62. Monica Billio & Massimiliano Caporin, 2006. "A generalized Dynamic Conditional Correlation Model for Portfolio Risk Evaluation," Working Papers 2006_53, Department of Economics, University of Venice "Ca' Foscari".

    Cited by:

    1. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
    2. Xin Liu & Jiang Wu & Chen Yang & Wenjun Jiang, 2018. "A Maximal Tail Dependence-Based Clustering Procedure for Financial Time Series and Its Applications in Portfolio Selection," Risks, MDPI, vol. 6(4), pages 1-26, October.
    3. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    4. Alexandridis, G. & Sahoo, S. & Visvikis, I., 2017. "Economic information transmissions and liquidity between shipping markets: New evidence from freight derivatives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 98(C), pages 82-104.
    5. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    7. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," CIRJE F-Series CIRJE-F-638, CIRJE, Faculty of Economics, University of Tokyo.
    8. Francesca Mariani & Gloria Polinesi & Maria Cristina Recchioni, 2022. "A tail-revisited Markowitz mean-variance approach and a portfolio network centrality," Computational Management Science, Springer, vol. 19(3), pages 425-455, July.
    9. C. Gourieroux, 2006. "Continuous Time Wishart Process for Stochastic Risk," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 177-217.
    10. Noureldin, Diaa & Shephard, Neil & Sheppard, Kevin, 2014. "Multivariate rotated ARCH models," Scholarly Articles 34650305, Harvard University Department of Economics.
    11. Fabrizio Cipollini & Giampiero Gallo & Alessandro Palandri, 2020. "A Dynamic Conditional Approach to Portfolio Weights Forecasting," Econometrics Working Papers Archive 2020_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    12. S.T. Boris Choy & Cathy W.S. Chen & Edward M.H. Lin, 2014. "Bivariate asymmetric GARCH models with heavy tails and dynamic conditional correlations," Quantitative Finance, Taylor & Francis Journals, vol. 14(7), pages 1297-1313, July.
    13. Aielli, Gian Piero & Caporin, Massimiliano, 2014. "Variance clustering improved dynamic conditional correlation MGARCH estimators," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 556-576.
    14. Matteo Bonato & Massimiliano Caporin & Angelo Ranaldo, 2009. "Forecasting realized (co)variances with a block structure Wishart autoregressive model," Working Papers 2009-03, Swiss National Bank.
    15. Yen-Hsien Lee, 2014. "An international analysis of REITs and stock portfolio management based on dynamic conditional correlation models," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 28(2), pages 165-180, May.
    16. Jacobs, Michael & Karagozoglu, Ahmet K., 2014. "On the characteristics of dynamic correlations between asset pairs," Research in International Business and Finance, Elsevier, vol. 32(C), pages 60-82.
    17. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    18. Aielli, Gian Piero & Caporin, Massimiliano, 2013. "Fast clustering of GARCH processes via Gaussian mixture models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 205-222.
    19. Allen, David E. & Gao, Jiti & McAleer, Michael, 2009. "Modelling and managing financial risk: An overview," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2521-2524.
    20. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    21. Cipollini, Fabrizio & Gallo, Giampiero M. & Palandri, Alessandro, 2021. "A dynamic conditional approach to forecasting portfolio weights," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1111-1126.
    22. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    23. Chen Yang & Wenjun Jiang & Jiang Wu & Xin Liu & Zhichuan Li, 2018. "Clustering of financial instruments using jump tail dependence coefficient," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(3), pages 491-513, August.
    24. Fabrizio Durante & Roberta Pappadà & Nicola Torelli, 2014. "Clustering of financial time series in risky scenarios," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(4), pages 359-376, December.
    25. Chaker Aloui, 2011. "Latin American stock markets’ volatility spillovers during the financial crises: a multivariate FIAPARCH-DCC framework," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 4(2), pages 289-326, May.
    26. Benjamin Poignard & Jean-Davis Fermanian, 2014. "Dynamic Asset Correlations Based on Vines," Working Papers 2014-46, Center for Research in Economics and Statistics.
    27. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    28. Amine Lahiani & Khaled Guesmi, 2014. "Commodity Price Correlation and Time varying Hedge Ratios," Working Papers 2014-142, Department of Research, Ipag Business School.
    29. Saker Sabkha & Christian de Peretti, 2022. "On the performances of Dynamic Conditional Correlation models in the Sovereign CDS market and the corresponding bond market," Post-Print hal-01710398, HAL.
    30. Jin Xisong & Lehnert Thorsten, 2018. "Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas," Dependence Modeling, De Gruyter, vol. 6(1), pages 19-46, February.
    31. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
    32. Acatrinei, Marius & Gorun, Adrian & Marcu, Nicu, 2013. "A DCC-GARCH Model To Estimate the Risk to the Capital Market in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 136-148, March.
    33. Lu, Jin-Ray & Lee, Pei-Hsuan & Chuang, I-Yuan, 2011. "Estimation of oil firm's systematic risk via composite time-varying models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(11), pages 2389-2399.

  63. Caporin Massimiliano & Paruolo Paolo, 2005. "Multivariate ARCH with spatial effects for stock sector and size," Economics and Quantitative Methods qf0509, Department of Economics, University of Insubria.

    Cited by:

    1. Massimiliano Caporin & Paolo Paruolo, 2015. "Proximity-Structured Multivariate Volatility Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 559-593, May.

  64. Caporin Massimiliano & Paruolo Paolo, 2005. "Spatial effects in multivariate ARCH," Economics and Quantitative Methods qf0501, Department of Economics, University of Insubria.

    Cited by:

    1. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    2. Matteo Bonato & Massimiliano Caporin & Angelo Ranaldo, 2009. "Forecasting realized (co)variances with a block structure Wishart autoregressive model," Working Papers 2009-03, Swiss National Bank.

Articles

  1. Billio, Monica & Caporin, Massimiliano & Frattarolo, Lorenzo & Pelizzon, Loriana, 2023. "Networks in risk spillovers: A multivariate GARCH perspective," Econometrics and Statistics, Elsevier, vol. 28(C), pages 1-29.
    See citations under working paper version above.
  2. 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.
    See citations under working paper version above.
  3. Caporin, Massimiliano & Fontini, Fulvio & Panzica, Roberto, 2023. "The systemic risk of US oil and natural gas companies," Energy Economics, Elsevier, vol. 121(C).
    See citations under working paper version above.
  4. Ghazani, Majid Mirzaee & Khosravi, Reza & Caporin, Massimiliano, 2023. "Analyzing interconnection among selected commodities in the 2008 global financial crisis and the COVID-19 pandemic," Resources Policy, Elsevier, vol. 80(C).

    Cited by:

    1. Aloui, Riadh & Ben Jabeur, Sami & Rezgui, Hichem & Ben Arfi, Wissal, 2023. "Geopolitical risk and commodity future returns: Fresh insights from dynamic copula conditional value-at-risk approach," Resources Policy, Elsevier, vol. 85(PB).
    2. Lei Li & Kun Qin & Desheng Wu, 2023. "A Hybrid Approach for the Assessment of Risk Spillover to ESG Investment in Financial Networks," Sustainability, MDPI, vol. 15(7), pages 1-16, April.
    3. Karimi, Parinaz & Mirzaee Ghazani, Majid & Ebrahimi, Seyed Babak, 2023. "Analyzing spillover effects of selected cryptocurrencies on gold and brent crude oil under COVID-19 pandemic: Evidence from GJR-GARCH and EVT copula methods," Resources Policy, Elsevier, vol. 85(PB).
    4. Ding, Shusheng & Wang, Kaihao & Cui, Tianxiang & Du, Min, 2023. "The time-varying impact of geopolitical risk on natural resource prices: The post-COVID era evidence," Resources Policy, Elsevier, vol. 86(PB).
    5. Hanif, Waqas & Mensi, Walid & Vo, Xuan Vinh & BenSaïda, Ahmed & Hernandez, Jose Arreola & Kang, Sang Hoon, 2023. "Dependence and risk management of portfolios of metals and agricultural commodity futures," Resources Policy, Elsevier, vol. 82(C).

  5. Bonaccolto, Giovanni & Caporin, Massimiliano & Maillet, Bertrand B., 2022. "Dynamic large financial networks via conditional expected shortfalls," European Journal of Operational Research, Elsevier, vol. 298(1), pages 322-336.
    See citations under working paper version above.
  6. Caporin, Massimiliano & Garcia-Jorcano, Laura & Jimenez-Martin, Juan-Angel, 2022. "Measuring systemic risk during the COVID-19 period: A TALIS3 approach," Finance Research Letters, Elsevier, vol. 46(PA).

    Cited by:

    1. 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.
    2. Massimiliano Caporin & Petre Caraiani & Oguzhan Cepni & Rangan Gupta, 2024. "Predicting the Conditional Distribution of US Stock Market Systemic Stress: The Role of Climate Risks," Working Papers 202407, University of Pretoria, Department of Economics.
    3. Lahmiri, Salim & Bekiros, Stelios & Bezzina, Frank, 2022. "Evidence of the fractal market hypothesis in European industry sectors with the use of bootstrapped wavelet leaders singularity spectrum analysis," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).

  7. Caporin, Massimiliano & Costola, Michele, 2022. "Time-varying Granger causality tests in the energy markets: A study on the DCC-MGARCH Hong test," Energy Economics, Elsevier, vol. 111(C).

    Cited by:

    1. Celso-Arellano, Pedro & Gualajara, Victor & Coronado, Semei & Martinez, Jose N. & Venegas-Martínez, Francisco, 2023. "Impact of the global fear index (covid-19 panic) on the S&P global indices associated with natural resources, agribusiness, energy, metals and mining: Granger Causality and Shannon and Rényi Transfer ," MPRA Paper 117138, University Library of Munich, Germany, revised 06 Feb 2023.
    2. Katarzyna Kuziak & Joanna Górka, 2023. "Dependence Analysis for the Energy Sector Based on Energy ETFs," Energies, MDPI, vol. 16(3), pages 1-30, January.

  8. Caporin, Massimiliano & Costola, Michele & Garibal, Jean-Charles & Maillet, Bertrand, 2022. "Systemic risk and severe economic downturns: A targeted and sparse analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).

    Cited by:

    1. He, Wenjia & He, Wenjing & Xu, Dandan & Yue, Pengpeng, 2023. "Economic volatility, banks’ risk accumulation and systemic risk," Finance Research Letters, Elsevier, vol. 57(C).
    2. Kreppmeier, Julia & Laschinger, Ralf & Steininger, Bertram & Dorfleitner, Gregor, 2023. "Real Estate Security Token Offerings and the Secondary Market: Driven by Crypto Hype or Fundamentals?," Working Paper Series 23/6, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
    3. Yiting Fan & Rui Fang, 2022. "Some Results on Measures of Interaction among Risks," Mathematics, MDPI, vol. 10(19), pages 1-19, October.
    4. Kreppmeier, Julia & Laschinger, Ralf & Steininger, Bertram I. & Dorfleitner, Gregor, 2023. "Real estate security token offerings and the secondary market: Driven by crypto hype or fundamentals?," Journal of Banking & Finance, Elsevier, vol. 154(C).
    5. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2023. "Options-based systemic risk, financial distress, and macroeconomic downturns," LSE Research Online Documents on Economics 119289, London School of Economics and Political Science, LSE Library.
    6. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2023. "Options-based systemic risk, financial distress, and macroeconomic downturns," Journal of Financial Markets, Elsevier, vol. 65(C).

  9. Bonaldo, Cinzia & Caporin, Massimiliano & Fontini, Fulvio, 2022. "The relationship between day-ahead and future prices in electricity markets: An empirical analysis on Italy, France, Germany, and Switzerland," Energy Economics, Elsevier, vol. 110(C).
    See citations under working paper version above.
  10. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).

    Cited by:

    1. Khan, Khalid & Su, Chi Wei & Koseoglu, Sinem Derindere, 2022. "Who are the influencers in the commodity markets during COVID-19?," Resources Policy, Elsevier, vol. 78(C).
    2. Siddique, Md Abubakar & Nobanee, Haitham & Karim, Sitara & Naz, Farah, 2022. "Investigating the role of metal and commodity classes in overcoming resource destabilization," Resources Policy, Elsevier, vol. 79(C).
    3. Bouri, Elie & Lei, Xiaojie & Xu, Yahua & Zhang, Hongwei, 2023. "Connectedness in implied higher-order moments of precious metals and energy markets," Energy, Elsevier, vol. 263(PB).
    4. Maghyereh, Aktham & Awartani, Basel & Virk, Nader S., 2022. "Asymmetric risk transmissions between oil, gold and US equities: Recent evidence from the realized variance of the futures prices," Resources Policy, Elsevier, vol. 79(C).
    5. Naeem, Muhammad Abubakr & Karim, Sitara & Uddin, Gazi Salah & Junttila, Juha, 2022. "Small fish in big ponds: Connections of green finance assets to commodity and sectoral stock markets," International Review of Financial Analysis, Elsevier, vol. 83(C).
    6. Iqbal, Najaf & Naeem, Muhammad Abubakr & Suleman, Muhammed Tahir, 2022. "Quantifying the asymmetric spillovers in sustainable investments," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    7. Naeem, Muhammad Abubakr & Karim, Sitara & Rabbani, Mustafa Raza & Nepal, Rabindra & Uddin, Gazi Salah, 2022. "Market integration in the Australian National Electricity Market: Fresh evidence from asymmetric time-frequency connectedness," Energy Economics, Elsevier, vol. 112(C).
    8. Jiang, Wei & Chen, Yunfei, 2024. "Impact of Russia-Ukraine conflict on the time-frequency and quantile connectedness between energy, metal and agricultural markets," Resources Policy, Elsevier, vol. 88(C).
    9. Lu, Ran & Xu, Wen & Zeng, Hongjun & Zhou, Xiangjing, 2023. "Volatility connectedness among the Indian equity and major commodity markets under the COVID-19 scenario," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1465-1481.
    10. Pham, Linh & Karim, Sitara & Naeem, Muhammad Abubakr & Long, Cheng, 2022. "A tale of two tails among carbon prices, green and non-green cryptocurrencies," International Review of Financial Analysis, Elsevier, vol. 82(C).
    11. Naeem, Muhammad Abubakr & Karim, Sitara & Hasan, Mudassar & Lucey, Brian M. & Kang, Sang Hoon, 2022. "Nexus between oil shocks and agriculture commodities: Evidence from time and frequency domain," Energy Economics, Elsevier, vol. 112(C).
    12. Boubaker, Sabri & Karim, Sitara & Naeem, Muhammad Abubakr & Rahman, Molla Ramizur, 2024. "On the prediction of systemic risk tolerance of cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    13. Abubakr Naeem, Muhammad & Iqbal, Najaf & Lucey, Brian M. & Karim, Sitara, 2022. "Good versus bad information transmission in the cryptocurrency market: Evidence from high-frequency data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    14. Anwer, Zaheer & Khan, Ashraf & Kabir Hassan, M. & Rashid, Mamunur, 2022. "Does the regional proximity lead to exchange rate spillover?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    15. Naeem, Muhammad Abubakr & Gul, Raazia & Farid, Saqib & Karim, Sitara & Lucey, Brian M., 2023. "Assessing linkages between alternative energy markets and cryptocurrencies," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 513-529.
    16. Naeem, Muhammad Abubakr & Farid, Saqib & Yousaf, Imran & Kang, Sang Hoon, 2023. "Asymmetric efficiency in petroleum markets before and during COVID-19," Resources Policy, Elsevier, vol. 86(PA).
    17. Tokgoz, Simla & Traoré, Fousseini, 2023. "Understanding E10 markets in the U.S.: Evidence from spatial data," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1267-1281.
    18. Shahzad, Syed Jawad Hussain & Naeem, Muhammad Abubakr & Peng, Zhe & Bouri, Elie, 2021. "Asymmetric volatility spillover among Chinese sectors during COVID-19," International Review of Financial Analysis, Elsevier, vol. 75(C).
    19. Anwer, Zaheer & Naeem, Muhammad Abubakr & Hassan, M. Kabir & Karim, Sitara, 2022. "Asymmetric connectedness across Asia-Pacific currencies: Evidence from time-frequency domain analysis," Finance Research Letters, Elsevier, vol. 47(PB).
    20. Naeem, Muhammad Abubakr & Karim, Sitara & Jamasb, Tooraj & Nepal, Rabindra, 2022. "Risk Transmission between Green Markets and Commodities," Working Papers 2-2022, Copenhagen Business School, Department of Economics.
    21. Bigerna, Simona, 2023. "Energy price shocks, exchange rates and inflation nexus," Energy Economics, Elsevier, vol. 128(C).
    22. Naeem, Muhammad Abubakr & Gul, Raazia & Shafiullah, Muhammad & Karim, Sitara & Lucey, Brian M., 2024. "Tail risk spillovers between Shanghai oil and other markets," Energy Economics, Elsevier, vol. 130(C).

  11. Khamis Hamed Al-Yahyaee & Walid Mensi & Hee-Un Ko & Massimiliano Caporin & Sang Hoon Kang, 2021. "Is the Korean housing market following Gangnam style?," Empirical Economics, Springer, vol. 61(4), pages 2041-2072, October.

    Cited by:

    1. Kola Ijasan & Peterson Owusu Junior & George Tweneboah & Tunbosun Oyedokun & Anokye M. Adam, 2021. "Analysing the relationship between global REITs and exchange rates: Fresh evidence from frequency-based quantile regressions," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(3), pages 58-91, September.
    2. James E. Payne & Xiaojin Sun, 2023. "Time‐varying connectedness of metropolitan housing markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(2), pages 470-502, March.

  12. Ahmed Khalifa, Massimiliano Caporin, Michele Costola, and Shawkat Hammoudeh, 2021. "Systemic Risk for Financial Institutions in the Major Petroleum-based Economies: The Role of Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    See citations under working paper version above.
  13. Caporin, Massimiliano & Gupta, Rangan & Ravazzolo, Francesco, 2021. "Contagion between real estate and financial markets: A Bayesian quantile-on-quantile approach," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    See citations under working paper version above.
  14. Massimiliano Caporin & Fulvio Fontini & Samuele Segato, 2021. "Has the EU-ETS Financed the Energy Transition of the Italian Power System?," IJFS, MDPI, vol. 9(4), pages 1-15, December.

    Cited by:

    1. Bonaldo, Cinzia & Fontini, Fulvio & Moretto, Michele, 2022. "The Energy Transition and the Value of Capacity Remuneration Mechanisms," FEEM Working Papers 321985, Fondazione Eni Enrico Mattei (FEEM).

  15. Caporin, Massimiliano & Garcia-Jorcano, Laura & Jimenez-Martin, Juan-Angel, 2021. "TrAffic LIght system for systemic Stress: TALIS3," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).

    Cited by:

    1. 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).
    2. Caporin, Massimiliano & Garcia-Jorcano, Laura & Jimenez-Martin, Juan-Angel, 2022. "Measuring systemic risk during the COVID-19 period: A TALIS3 approach," Finance Research Letters, Elsevier, vol. 46(PA).
    3. Paweł Sakowski & Rafał Sieradzki & Robert Ślepaczuk, 2023. "The systemic risk approach based on implied and realized volatility," Working Papers 2023-07, Faculty of Economic Sciences, University of Warsaw.
    4. Massimiliano Caporin & Petre Caraiani & Oguzhan Cepni & Rangan Gupta, 2024. "Predicting the Conditional Distribution of US Stock Market Systemic Stress: The Role of Climate Risks," Working Papers 202407, University of Pretoria, Department of Economics.
    5. Pawe{l} Sakowski & Rafa{l} Sieradzki & Robert 'Slepaczuk, 2023. "Systemic risk indicator based on implied and realized volatility," Papers 2307.05719, arXiv.org.

  16. Liu, Shaowen & Caporin, Massimiliano & Paterlini, Sandra, 2021. "Dynamic network analysis of North American financial institutions," Finance Research Letters, Elsevier, vol. 42(C).

    Cited by:

    1. García, Javier Sánchez & Rambaud, Salvador Cruz, 2023. "Macrofinancial determinants of volatility transmission in a network of European sovereign debt markets," Finance Research Letters, Elsevier, vol. 53(C).
    2. 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).
    3. Iyer, Subramanian Rama & Simkins, Betty J., 2022. "COVID-19 and the Economy: Summary of research and future directions," Finance Research Letters, Elsevier, vol. 47(PB).
    4. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.
    5. Juan Li & Keyin Liu & Zixin Yang & Yi Qu, 2023. "Evolution and Impacting Factors of Global Renewable Energy Products Trade Network: An Empirical Investigation Based on ERGM Model," Sustainability, MDPI, vol. 15(11), pages 1-27, May.

  17. Caporin, Massimiliano & Malik, Farooq, 2020. "Do structural breaks in volatility cause spurious volatility transmission?," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 60-82.

    Cited by:

    1. Malik, Farooq, 2021. "Volatility spillover between exchange rate and stock returns under volatility shifts," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 605-613.
    2. Pan, Zhiyuan & Xiao, Dongli & Dong, Qingma & Liu, Li, 2022. "Structural breaks, macroeconomic fundamentals and cross hedge ratio," Finance Research Letters, Elsevier, vol. 47(PA).
    3. Imran Yousaf & Shoaib Ali, 2020. "Discovering interlinkages between major cryptocurrencies using high-frequency data: new evidence from COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-18, December.
    4. Farooq Malik, 2022. "Volatility spillover among sector equity returns under structural breaks," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1063-1080, April.
    5. Belhassine, Olfa & Karamti, Chiraz, 2021. "Volatility spillovers and hedging effectiveness between oil and stock markets: Evidence from a wavelet-based and structural breaks analysis," Energy Economics, Elsevier, vol. 102(C).
    6. Pham, Son Duy & Nguyen, Thao Thac Thanh & Do, Hung Xuan, 2022. "Dynamic volatility connectedness between thermal coal futures and major cryptocurrencies: Evidence from China," Energy Economics, Elsevier, vol. 112(C).
    7. Vatsa, Puneet & Basnet, Hem C., 2020. "The dynamics of energy prices and the Norwegian economy: A common trends and common cycles analysis," Resources Policy, Elsevier, vol. 68(C).

  18. Massimiliano Caporin & Riccardo (Jack) Lucchetti & Giulio Palomba, 2020. "Analytical Gradients of Dynamic Conditional Correlation Models," JRFM, MDPI, vol. 13(3), pages 1-21, March.

    Cited by:

    1. Massimiliano Caporin & Giuseppe Storti, 2020. "Financial Time Series: Methods and Models," JRFM, MDPI, vol. 13(5), pages 1-3, April.

  19. Shahzad, Syed Jawad Hussain & Caporin, Massimiliano, 2020. "On the volatilities of tourism stocks and oil," Annals of Tourism Research, Elsevier, vol. 81(C).

    Cited by:

    1. Liang, Ruibin & Cheng, Sheng & Cao, Yan & Li, Xinran, 2024. "Multi-scale impacts of oil shocks on travel and leisure stocks: A MODWT-Bayesian TVP model with shrinkage approach," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    2. Corbet, Shaen & Hou, Yang & Hu, Yang & Oxley, Les, 2022. "Did COVID-19 tourism sector supports alleviate investor fear?," Annals of Tourism Research, Elsevier, vol. 95(C).

  20. Massimiliano Caporin & Michele Costola, 2019. "Asymmetry and leverage in GARCH models: a News Impact Curve perspective," Applied Economics, Taylor & Francis Journals, vol. 51(31), pages 3345-3364, July.

    Cited by:

    1. Najam Iqbal & Muhammad Saqib Manzoor & Muhammad Ishaq Bhatti, 2021. "Asymmetry and Leverage with News Impact Curve Perspective in Australian Stock Returns’ Volatility during COVID-19," JRFM, MDPI, vol. 14(7), pages 1-15, July.
    2. Paul R. Dewick, 2022. "On Financial Distributions Modelling Methods: Application on Regression Models for Time Series," JRFM, MDPI, vol. 15(10), pages 1-15, October.
    3. Maurice Omane‐Adjepong & Imhotep Paul Alagidede, 2021. "Modelling Asymmetry and Leverage in Cryptocurrencies and Emerging Financial Markets," Economic Papers, The Economic Society of Australia, vol. 40(2), pages 152-166, June.
    4. Wang, Gang-Jin & Ma, Xin-yu & Wu, Hao-yu, 2020. "Are stablecoins truly diversifiers, hedges, or safe havens against traditional cryptocurrencies as their name suggests?," Research in International Business and Finance, Elsevier, vol. 54(C).
    5. Rachna Mahalwala, 2022. "Analysing exchange rate volatility in India using GARCH family models," SN Business & Economics, Springer, vol. 2(9), pages 1-16, September.
    6. Maurice Omane-Adjepong & Imhotep Paul Alagidede, 2020. "Dynamic Linkages and Economic Role of Leading Cryptocurrencies in an Emerging Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(4), pages 537-585, December.

  21. Rodríguez-Caballero, Carlos Vladimir & Caporin, Massimiliano, 2019. "A multilevel factor approach for the analysis of CDS commonality and risk contribution," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    See citations under working paper version above.
  22. 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.

    Cited by:

    1. Wen, Shigang & Li, Jianping & Huang, Chuangxia & Zhu, Xiaoqian, 2023. "Extreme risk spillovers among traditional financial and FinTech institutions: A complex network perspective," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 190-202.
    2. Karoline Bax & Giovanni Bonaccolto & Sandra Paterlini, 2023. "Do lower environmental, social, and governance (ESG) rated companies have higher systemic impact? Empirical evidence from Europe and the United States," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 30(3), pages 1406-1420, May.
    3. 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).
    4. Giovanni Bonaccolto & Massimiliano Caporin & Bertrand Maillet, 2022. "Dynamic Large Financial Networks via Conditional Expected Shortfalls," Post-Print hal-03287947, HAL.
    5. Michele Costola & Matteo Iacopini & Casper Wichers, 2023. "Bayesian SAR model with stochastic volatility and multiple time-varying weights," Papers 2310.17473, arXiv.org.
    6. Qian, Biyu & Wang, Gang-Jin & Feng, Yusen & Xie, Chi, 2022. "Partial cross-quantilogram networks: Measuring quantile connectedness of financial institutions," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    7. Alessi, Lucia & Elisa, Ossola & Panzica, Roberto, 2021. "When do investors go green? Evidence from a time-varying asset-pricing model," Working Papers 2021-13, Joint Research Centre, European Commission.
    8. Franch, Fabio & Nocciola, Luca & Vouldis, Angelos, 2022. "Temporal networks in the analysis of financial contagion," Working Paper Series 2667, European Central Bank.
    9. Huang, Jionghao & Li, Ziruo & Xia, Xiaohua, 2021. "Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1-39.
    10. 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).

  23. Khalifa, Ahmed & Caporin, Massimiliano & Di Fonzo, Tommaso, 2019. "Scenario-based forecast for the electricity demand in Qatar and the role of energy efficiency improvements," Energy Policy, Elsevier, vol. 127(C), pages 155-164.

    Cited by:

    1. Xin Ma & Yubin Cai & Hong Yuan & Yanqiao Deng, 2023. "Partially Linear Component Support Vector Machine for Primary Energy Consumption Forecasting of the Electric Power Sector in the United States," Sustainability, MDPI, vol. 15(9), pages 1-26, April.
    2. Abulibdeh, Ammar, 2022. "Time series analysis of environmental quality in the state of Qatar," Energy Policy, Elsevier, vol. 168(C).
    3. Chen, Hai-Bao & Pei, Ling-Ling & Zhao, Yu-Feng, 2021. "Forecasting seasonal variations in electricity consumption and electricity usage efficiency of industrial sectors using a grey modeling approach," Energy, Elsevier, vol. 222(C).
    4. Angel Manuel Benitez Rodriguez & Ian Michael Trotter, 2019. "Climate change scenarios for Paraguayan power demand 2017–2050," Climatic Change, Springer, vol. 156(3), pages 425-445, October.
    5. Shayma Al Bannay & Satoshi Takizawa, 2022. "Decoupling of Water Production and Electricity Generation from GDP and Population in the Gulf Cooperation Council (GCC) Countries," Sustainability, MDPI, vol. 14(9), pages 1-20, April.
    6. Yusri Syam Akil & Hajime Miyauchi & Saiful Mangngenre & Kifayah Amar, 2020. "Perceptions and Determinants of SMEs Consumers Behaviors for Electricity Saving: Evidence from Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 10(3), pages 168-174.
    7. Zhixiong Weng & Yuqi Song & Hao Ma & Zhong Ma & Tingting Liu, 2023. "Forecasting energy demand, structure, and CO2 emission: a case study of Beijing, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 10369-10391, September.

  24. Caporin, Massimiliano & Chang, Chia-Lin & McAleer, Michael, 2019. "Are the S&P 500 index and crude oil, natural gas and ethanol futures related for intra-day data?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 50-70.
    See citations under working paper version above.
  25. Caporin, Massimiliano & Natvik, Gisle J. & Ravazzolo, Francesco & Santucci de Magistris, Paolo, 2019. "The bank-sovereign nexus: Evidence from a non-bailout episode," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 181-196.
    See citations under working paper version above.
  26. Caporin, Massimiliano & Fontini, Fulvio & Talebbeydokhti, Elham, 2019. "Testing persistence of WTI and Brent long-run relationship after the shale oil supply shock," Energy Economics, Elsevier, vol. 79(C), pages 21-31.

    Cited by:

    1. Mastroeni, Loretta & Mazzoccoli, Alessandro & Quaresima, Greta & Vellucci, Pierluigi, 2021. "Decoupling and recoupling in the crude oil price benchmarks: An investigation of similarity patterns," Energy Economics, Elsevier, vol. 94(C).
    2. Stavros Malkidis & Stilianos Fountas, 2020. "Liquid fuel price adjustment in Greece:a two-stage, threshold cointegration approach," Discussion Paper Series 2020_04, Department of Economics, University of Macedonia, revised May 2020.
    3. Zhang, Wenbei & Luckert, Marty & Qiu, Feng, 2023. "Asymmetric price transmission and impulse responses from U.S. crude oil to jet fuel and diesel markets," Energy, Elsevier, vol. 283(C).
    4. Chatziantoniou, Ioannis & Gabauer, David & Gupta, Rangan, 2023. "Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach," Resources Policy, Elsevier, vol. 84(C).
    5. Gao, Xin & Li, Bingxin & Liu, Rui, 2023. "The relative pricing of WTI and Brent crude oil futures: Expectations or risk premia?," Journal of Commodity Markets, Elsevier, vol. 30(C).
    6. Qiang Ji & Dayong Zhang & Yuqian Zhao, 2022. "Intra-day co-movements of crude oil futures: China and the international benchmarks," Annals of Operations Research, Springer, vol. 313(1), pages 77-103, June.
    7. Ioannis Chatziantoniou & David Gabauer & Rangan Gupta, 2021. "Integration and Risk Transmission in the Market for Crude Oil: A Time-Varying Parameter Frequency Connectedness Approach," Working Papers 202147, University of Pretoria, Department of Economics.
    8. Cheng, Xian & Wu, Peng & Liao, Stephen Shaoyi & Wang, Xuelian, 2023. "An integrated model for crude oil forecasting: Causality assessment and technical efficiency," Energy Economics, Elsevier, vol. 117(C).
    9. Chatziantoniou, Ioannis & Gabauer, David & Perez de Gracia, Fernando, 2022. "Tail risk connectedness in the refined petroleum market: A first look at the impact of the COVID-19 pandemic," Energy Economics, Elsevier, vol. 111(C).
    10. Caporin, Massimiliano & Fontini, Fulvio & Panzica, Roberto, 2022. "The systemic risk of US oil and natural gas companies," Working Papers 2022-11, Joint Research Centre, European Commission.
    11. Kumar, Satish, 2022. "Speed of adjustment in energy and metal prices: Evidence from India," Resources Policy, Elsevier, vol. 78(C).
    12. Caporina, Massimiliano & Costola, Michele, 2021. "Time-varying granger causality tests for applications in global crude oil markets: A study on the DCC-MGARCH Hong test," SAFE Working Paper Series 324, Leibniz Institute for Financial Research SAFE.
    13. Guo, Yawei & Li, Jianping & Li, Yehua & You, Wanhai, 2021. "The roles of political risk and crude oil in stock market based on quantile cointegration approach: A comparative study in China and US," Energy Economics, Elsevier, vol. 97(C).
    14. Jerome Geyer‐Klingeberg & Andreas W. Rathgeber, 2021. "Determinants of the WTI‐Brent price spread revisited," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 736-757, May.
    15. Caporin, Massimiliano & Costola, Michele, 2022. "Time-varying Granger causality tests in the energy markets: A study on the DCC-MGARCH Hong test," Energy Economics, Elsevier, vol. 111(C).

  27. Bonaccolto, Giovanni & Caporin, Massimiliano & Paterlini, Sandra, 2019. "Decomposing and backtesting a flexible specification for CoVaR," Journal of Banking & Finance, Elsevier, vol. 108(C).

    Cited by:

    1. Luca Merlo & Lea Petrella & Valentina Raponi, 2021. "Forecasting VaR and ES using a joint quantile regression and implications in portfolio allocation," Papers 2106.06518, arXiv.org.
    2. Karoline Bax & Giovanni Bonaccolto & Sandra Paterlini, 2023. "Do lower environmental, social, and governance (ESG) rated companies have higher systemic impact? Empirical evidence from Europe and the United States," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 30(3), pages 1406-1420, May.
    3. 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.
    4. Giovanni Bonaccolto & Massimiliano Caporin & Bertrand Maillet, 2022. "Dynamic Large Financial Networks via Conditional Expected Shortfalls," Post-Print hal-03287947, HAL.
    5. Bianchi, Michele Leonardo & De Luca, Giovanni & Rivieccio, Giorgia, 2023. "Non-Gaussian models for CoVaR estimation," International Journal of Forecasting, Elsevier, vol. 39(1), pages 391-404.
    6. Shaowei Chen & Long Guo & Weike Zhang, 2023. "Financial Risk Measurement and Spatial Spillover Effects Based on an Imported Financial Risk Network: Evidence from Countries along the Belt and Road," Mathematics, MDPI, vol. 11(6), pages 1-25, March.
    7. Xu, Qifa & Jin, Bei & Jiang, Cuixia, 2021. "Measuring systemic risk of the Chinese banking industry: A wavelet-based quantile regression approach," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    8. Merlo, Luca & Petrella, Lea & Raponi, Valentina, 2021. "Forecasting VaR and ES using a joint quantile regression and its implications in portfolio allocation," Journal of Banking & Finance, Elsevier, vol. 133(C).

  28. Giovanni Bonaccolto & Massimiliano Caporin & Sandra Paterlini, 2018. "Asset allocation strategies based on penalized quantile regression," Computational Management Science, Springer, vol. 15(1), pages 1-32, January.
    See citations under working paper version above.
  29. Caporin, Massimiliano & Pelizzon, Loriana & Ravazzolo, Francesco & Rigobon, Roberto, 2018. "Measuring sovereign contagion in Europe," Journal of Financial Stability, Elsevier, vol. 34(C), pages 150-181.
    See citations under working paper version above.
  30. Blasi, Silvia & Caporin, Massimiliano & Fontini, Fulvio, 2018. "A Multidimensional Analysis of the Relationship Between Corporate Social Responsibility and Firms' Economic Performance," Ecological Economics, Elsevier, vol. 147(C), pages 218-229.

    Cited by:

    1. Chang Seop Rhee & Sohee Woo & So-Jin Yu & Hyunjung Rhee, 2021. "Corporate Social Responsibility and Sustainable Employability: Empirical Evidence from Korea," Sustainability, MDPI, vol. 13(14), pages 1-14, July.
    2. Sonia Boukattaya & Zyed Achour & Zeineb Hlioui, 2021. "Corporate Social Responsibility and Corporate Financial Performance: An Empirical Literature Review," Post-Print hal-03472433, HAL.
    3. Kren, Janez & Lawless, Martina, 2023. "Firm-level attitudes and actions to the “Twin Transition” challenges of digitalisation and climate change," Papers WP742, Economic and Social Research Institute (ESRI).
    4. Hunjra, Ahmed Imran & Boubaker, Sabri & Arunachalam, Murugesh & Mehmood, Asad, 2021. "How does CSR mediate the relationship between culture, religiosity and firm performance?," Finance Research Letters, Elsevier, vol. 39(C).
    5. Asif Mahmood & Rana Tahir Naveed & Naveed Ahmad & Miklas Scholz & Muhammad Khalique & Mohammad Adnan, 2021. "Unleashing the Barriers to CSR Implementation in the SME Sector of a Developing Economy: A Thematic Analysis Approach," Sustainability, MDPI, vol. 13(22), pages 1-20, November.
    6. Wassili Lasarov & Stefan Hoffmann & Ulrich Orth, 2023. "Vanishing Boycott Impetus: Why and How Consumer Participation in a Boycott Decreases Over Time," Journal of Business Ethics, Springer, vol. 182(4), pages 1129-1154, February.
    7. D'Amato, D. & Korhonen, J. & Toppinen, A., 2019. "Circular, Green, and Bio Economy: How Do Companies in Land-Use Intensive Sectors Align with Sustainability Concepts?," Ecological Economics, Elsevier, vol. 158(C), pages 116-133.
    8. Cristian Carini & Nicola Comincioli & Laura Poddi & Sergio Vergalli, 2017. "Measure the Performance with the Market Value Added: Evidence from CSR Companies," Sustainability, MDPI, vol. 9(12), pages 1-19, November.
    9. Raja Abid, 2023. "Corporate social (ir)responsibility towards employees and financial performance: using time to solve the chicken-egg problem," Review of Managerial Science, Springer, vol. 17(2), pages 635-659, February.
    10. Fang Zhang & Minghui Li & Meilan Zhang, 2019. "Chinese Financial Market Investors Attitudes toward Corporate Social Responsibility: Evidence from Mergers and Acquisitions," Sustainability, MDPI, vol. 11(9), pages 1-20, May.
    11. Zhao‐Yong Sun & Meng‐Jie Li & Dongdong Li, 2023. "Carbon performance and corporate financial performance: The moderating role of consumer awareness of corporate social responsibility," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(1), pages 663-670, January.
    12. Lasarov, Wassili & Mai, Robert & Krause, Jan S. & Schmidt, Ulrich & Hoffmann, Stefan, 2021. "Too Cold to be Skeptical: How Ambient Temperature Moderates the Effects of CSR Communication," Ecological Economics, Elsevier, vol. 183(C).
    13. Antonio Salvi & Emanuele Doronzo & Anastasia Giakoumelou & Felice Petruzzella, 2021. "CSR and Corporate Financial Performance: An Inter-Sectorial Analysis," International Journal of Business and Management, Canadian Center of Science and Education, vol. 14(11), pages 193-193, July.
    14. Kudłak, Robert, 2019. "The role of corporate social responsibility in predicting CO2 emission: An institutional approach," Ecological Economics, Elsevier, vol. 163(C), pages 169-176.
    15. Sohail Ahmad Javeed & Lin Lefen, 2019. "An Analysis of Corporate Social Responsibility and Firm Performance with Moderating Effects of CEO Power and Ownership Structure: A Case Study of the Manufacturing Sector of Pakistan," Sustainability, MDPI, vol. 11(1), pages 1-25, January.
    16. Shirasu, Yoko & Kawakita, Hidetaka, 2021. "Long-term financial performance of corporate social responsibility," Global Finance Journal, Elsevier, vol. 50(C).
    17. Jakub Horak & Petr Suler & Jaroslav Kollmann & Jan Marecek, 2020. "Credit Absorption Capacity of Businesses in the Construction Sector of the Czech Republic—Analysis Based on the Difference in Values of EVA Entity and EVA Equity," Sustainability, MDPI, vol. 12(21), pages 1-16, October.
    18. Wafa Sahraoui & Rimvie Enoc Kabore, 2021. "The relationship between Corporate Social Responsibility and performance: the moderating effect of financial leverage," Working Papers hal-03503462, HAL.
    19. Úbeda-García, Mercedes & Claver-Cortés, Enrique & Marco-Lajara, Bartolomé & Zaragoza-Sáez, Patrocinio, 2021. "Corporate social responsibility and firm performance in the hotel industry. The mediating role of green human resource management and environmental outcomes," Journal of Business Research, Elsevier, vol. 123(C), pages 57-69.
    20. Olivier Beaumais & Mireille Chiroleu-Assouline, 2020. "Informal versus Formal Corporate Social Responsibility: a Tale of Hidden Green Attitude," PSE Working Papers halshs-03073242, HAL.
    21. Szennay, Áron, 2018. "Nagyvállalatok pénzügyi teljesítményének és társadalmi felelősségvállalásának összefüggései Magyarországon [Relations between financial and non-financial performance in Hungary]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(12), pages 1281-1298.
    22. Muhammad Safdar Sial & Chunmei Zheng & Nguyen Vinh Khuong & Tehmina Khan & Muhammad Usman, 2018. "Does Firm Performance Influence Corporate Social Responsibility Reporting of Chinese Listed Companies?," Sustainability, MDPI, vol. 10(7), pages 1-12, June.
    23. Bang, You-Young & Lee, Dae Sung & Lim, Seong-Rin, 2019. "Analysis of corporate CO2 and energy cost efficiency: The role of performance indicators and effective environmental reporting," Energy Policy, Elsevier, vol. 133(C).
    24. Faisal Mahmood & Faisal Qadeer & Usman Sattar & Antonio Ariza-Montes & Maria Saleem & Jaffar Aman, 2020. "Corporate Social Responsibility and Firms’ Financial Performance: A New Insight," Sustainability, MDPI, vol. 12(10), pages 1-19, May.
    25. Silvia Blasi & Benedetta Crisafulli & Silvia Rita Sedita, 2020. "Selling the circularity: Investigating the impact of circularity promotion on the performance of Italian manufacturing companies," "Marco Fanno" Working Papers 0259, Dipartimento di Scienze Economiche "Marco Fanno".
    26. Slobodan Marić & Nemanja Berber & Agneš Slavić & Marko Aleksić, 2021. "The Mediating Role of Employee Commitment in the Relationship Between Corporate Social Responsibility and Firm Performance in Serbia," SAGE Open, , vol. 11(3), pages 21582440211, August.
    27. Tomlinson, Bill & Silberman, M. Six & Torrance, Andrew W. & Nikols, Nick & Black, Rebecca W. & Squire, Kurt & Atwal, Paramdeep S. & Mandalik, Ameya N. & Railkar, Sahil & Workman, Mary Kate, 2020. "“Environment-selected directors”: An interactive simulation experiment of environmental representation on corporate boards," Ecological Economics, Elsevier, vol. 178(C).
    28. Thomas Bassetti & Silvia Blasi & Silvia Rita Sedita, 2021. "The management of sustainable development: A longitudinal analysis of the effects of environmental performance on economic performance," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 21-37, January.
    29. Wafa Ghardallou & Noha Alessa, 2022. "Corporate Social Responsibility and Firm Performance in GCC Countries: A Panel Smooth Transition Regression Model," Sustainability, MDPI, vol. 14(13), pages 1-21, June.
    30. Dongsheng Zhang & Hongwei Wang & Xiangshan Jin, 2022. "Element Matching and Configuration Path of Corporate Social Responsibility Performance," Sustainability, MDPI, vol. 14(11), pages 1-18, May.
    31. Ben Lahouel, Béchir & Ben Zaied, Younes & Managi, Shunsuke & Taleb, Lotfi, 2022. "Re-thinking about U: The relevance of regime-switching model in the relationship between environmental corporate social responsibility and financial performance," Journal of Business Research, Elsevier, vol. 140(C), pages 498-519.

  31. Caporin, Massimiliano & Costola, Michele & Jannin, Gregory & Maillet, Bertrand, 2018. "“On the (Ab)use of Omega?”," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 11-33.
    See citations under working paper version above.
  32. Bonaccolto, G. & Caporin, M. & Gupta, R., 2018. "The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 446-469.
    See citations under working paper version above.
  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.

    Cited by:

    1. Banerjee, Ameet Kumar & Dionisio, Andreia & Pradhan, H.K. & Mahapatra, Biplab, 2021. "Hunting the quicksilver: Using textual news and causality analysis to predict market volatility," International Review of Financial Analysis, Elsevier, vol. 77(C).
    2. 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.
    3. Chen, Wang & Lu, Xinjie & Wang, Jiqian, 2022. "Modeling and managing stock market volatility using MRS-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 625-635.
    4. Tomáš Plíhal, 2021. "Scheduled macroeconomic news announcements and Forex volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1379-1397, December.
    5. Khan, Muhammad Asif & Hernandez, Jose Arreola & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency relationship between household investors’ sentiment index and US industry stock returns," Finance Research Letters, Elsevier, vol. 36(C).
    6. Mikhaylov, Dmitry, 2023. "Macroeconomic Forecasting with the Use of News Data," Working Papers w20220250, Russian Presidential Academy of National Economy and Public Administration.
    7. Deev, Oleg & Plíhal, Tomáš, 2022. "How to calm down the markets? The effects of COVID-19 economic policy responses on financial market uncertainty," Research in International Business and Finance, Elsevier, vol. 60(C).
    8. Justina Deveikyte & Helyette Geman & Carlo Piccari & Alessandro Provetti, 2020. "A Sentiment Analysis Approach to the Prediction of Market Volatility," Papers 2012.05906, arXiv.org.
    9. Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021. "A machine learning approach to volatility forecasting," CREATES Research Papers 2021-03, Department of Economics and Business Economics, Aarhus University.
    10. Ye, Jing & Xue, Minggao, 2021. "Influences of sentiment from news articles on EU carbon prices," Energy Economics, Elsevier, vol. 101(C).
    11. Fang, Jianchun & Gozgor, Giray & Lau, Chi-Keung Marco & Lu, Zhou, 2020. "The impact of Baidu Index sentiment on the volatility of China's stock markets," Finance Research Letters, Elsevier, vol. 32(C).
    12. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    13. Caporin, Massimiliano & Poli, Francesco, 2022. "News and intraday jumps: Evidence from regularization and class imbalance," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    14. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).
    15. Yicun Li & Yuanyang Teng, 2023. "The Fama–French Five-Factor Model with Hurst Exponents Compared with Machine Learning Methods," Mathematics, MDPI, vol. 11(13), pages 1-19, July.
    16. Alomari, Mohammad & Al Rababa’a, Abdel Razzaq & El-Nader, Ghaith & Alkhataybeh, Ahmad & Ur Rehman, Mobeen, 2021. "Examining the effects of news and media sentiments on volatility and correlation: Evidence from the UK," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 280-297.
    17. Xinjie Lu & Feng Ma & Jiqian Wang & Jing Liu, 2022. "Forecasting oil futures realized range‐based volatility with jumps, leverage effect, and regime switching: New evidence from MIDAS models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 853-868, July.
    18. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.

  34. Khalifa, Ahmed & Caporin, Massimiliano & Hammoudeh, Shawkat, 2017. "The relationship between oil prices and rig counts: The importance of lags," Energy Economics, Elsevier, vol. 63(C), pages 213-226.

    Cited by:

    1. Wu, Bi-Bo, 2021. "The dynamics of oil on China’s commodity sectors: What can we learn from a quantile perspective?," Journal of Commodity Markets, Elsevier, vol. 23(C).
    2. Nicoleta Iliescu, 2018. "Long-run co-movements between oil prices and rig count in the presence of structural breaks," Economics Bulletin, AccessEcon, vol. 38(2), pages 1171-1179.
    3. Nicola Comincioli & Verena Hagspiel & Peter M. Kort & Francesco Menoncin & Raffaele Miniaci & Sergio Vergalli, 2020. "Mothballing in a Duopoly: Evidence from a (Shale) Oil Market," Working Papers 2020.18, Fondazione Eni Enrico Mattei.
    4. Nenubari John Ikue & Lamin Mohammed Magaji & Samuel Zeb-Omoni & Mohammed, Aminu Usman & Joseph Osaro Denwi, 2021. "Trade Balance and Oil Shocks in African Oil Exporting Countries: A Panel Threshold Regression," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 10(4), pages 150-166, October.
    5. Shrestha, Keshab & Subramaniam, Ravichandran & Peranginangin, Yessy & Philip, Sheena Sara Suresh, 2018. "Quantile hedge ratio for energy markets," Energy Economics, Elsevier, vol. 71(C), pages 253-272.
    6. Jamil, Faisal, 2024. "Empirical analysis of investment in Pakistan’s upstream sector," Resources Policy, Elsevier, vol. 88(C).
    7. Nenubari John Ikue & Lucky Ifeanyi Amabuike & Joseph Osaro Denwi & Aminu Usman Mohammed & Ahmadu Uba Musa, 2021. "Economic growth and crude oil revenue in Nigeria: A control for industrial shocks," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(8), pages 218-227, December.
    8. Dean Fantazzini & Nikita Kolodin, 2020. "Does the Hashrate Affect the Bitcoin Price?," JRFM, MDPI, vol. 13(11), pages 1-29, October.
    9. Shakya, Shishir & Li, Bingxin & Etienne, Xiaoli, 2022. "Shale revolution, oil and gas prices, and drilling activities in the United States," Energy Economics, Elsevier, vol. 108(C).
    10. Ali, Muhammad Kashif & Zahoor, Muhammad Khurram & Saeed, Asif & Nosheen, Safia & Thanakijsombat, Thanarerk, 2023. "Institutional and country level determinants of vertical integration: New evidence from the oil and gas industry," Resources Policy, Elsevier, vol. 84(C).
    11. Yang, Dong-Xiao & Wu, Bi-Bo & Tong, Jing-Yang, 2021. "Dynamics and causality of oil price shocks on commodities: Quantile-on-quantile and causality-in-quantiles methods," Resources Policy, Elsevier, vol. 74(C).
    12. Ahmed Khalifa, Massimiliano Caporin, Michele Costola, and Shawkat Hammoudeh, 2021. "Systemic Risk for Financial Institutions in the Major Petroleum-based Economies: The Role of Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    13. Pedro Moreno Alonso & Antonio Mu oz San Roque, 2021. "Oil Costs and Prices: An Empirical Causality Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 546-554.
    14. Song-Zan Chiou-Wei & Sheng-Hung Chen & Wei-Hung Chen, 2023. "Asymmetric Effects of Prices and Storage on Rig Counts: Evidence from the US Natural Gas and Crude Oil Markets," Energies, MDPI, vol. 16(15), pages 1-25, August.
    15. Turgut Yokuş, 2024. "Early Warning Systems for World Energy Crises," Sustainability, MDPI, vol. 16(6), pages 1-18, March.

  35. Caporin, Massimiliano & Fontini, Fulvio, 2017. "The long-run oil–natural gas price relationship and the shale gas revolution," Energy Economics, Elsevier, vol. 64(C), pages 511-519.
    See citations under working paper version above.
  36. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.

    Cited by:

    1. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 122, Paderborn University, CIE Center for International Economics.
    2. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 125, Paderborn University, CIE Center for International Economics.

  37. Massimiliano Caporin & Rangan Gupta, 2017. "Time-varying persistence in US inflation," Empirical Economics, Springer, vol. 53(2), pages 423-439, September.
    See citations under working paper version above.
  38. Caporin, Massimiliano & Kolokolov, Aleksey & Renò, Roberto, 2017. "Systemic co-jumps," Journal of Financial Economics, Elsevier, vol. 126(3), pages 563-591.
    See citations under working paper version above.
  39. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2016. "Volatility Jumps and Their Economic Determinants," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 29-80.
    See citations under working paper version above.
  40. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," JRFM, MDPI, vol. 9(3), pages 1-25, July.

    Cited by:

    1. Tan, Shay-Kee & Ng, Kok-Haur & Chan, Jennifer So-Kuen & Mohamed, Ibrahim, 2019. "Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 537-551.
    2. Dinh, Dung V. & Powell, Robert J. & Vo, Duc H., 2021. "Forecasting corporate financial distress in the Southeast Asian countries: A market-based approach," Journal of Asian Economics, Elsevier, vol. 74(C).

  41. F. Baldovin & F. Camana & M. Caporin & M. Caraglio & A.L. Stella, 2015. "Ensemble properties of high-frequency data and intraday trading rules," Quantitative Finance, Taylor & Francis Journals, vol. 15(2), pages 231-245, February.
    See citations under working paper version above.
  42. Massimiliano Caporin & Paolo Paruolo, 2015. "Proximity-Structured Multivariate Volatility Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 559-593, May.

    Cited by:

    1. Caporin, Massimiliano & Malik, Farooq, 2020. "Do structural breaks in volatility cause spurious volatility transmission?," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 60-82.
    2. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    3. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    4. Francesco Giuseppe Caloia & Andrea Cipollini & Silvia Muzzioli, 2016. "A note on normalization schemes:The case of generalized forecast error variance decompositions," Department of Economics 0092, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    5. Caloia, Francesco Giuseppe & Cipollini, Andrea & Muzzioli, Silvia, 2019. "How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study," Energy Economics, Elsevier, vol. 84(C).
    6. 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.
    7. Philipp Otto & Osman Dou{g}an & Suleyman Tac{s}p{i}nar & Wolfgang Schmid & Anil K. Bera, 2023. "Spatial and Spatiotemporal Volatility Models: A Review," Papers 2308.13061, arXiv.org.
    8. 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.
    9. Billio, Monica & Caporin, Massimiliano & Frattarolo, Lorenzo & Pelizzon, Loriana, 2018. "Networks in risk spillovers: A multivariate GARCH perspective," SAFE Working Paper Series 225, Leibniz Institute for Financial Research SAFE.
    10. Lakshina, Valeriya, 2014. "Is it possible to break the «curse of dimensionality»? Spatial specifications of multivariate volatility models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 36(4), pages 61-78.
    11. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.
    12. Liu, Shaowen & Caporin, Massimiliano & Paterlini, Sandra, 2021. "Dynamic network analysis of North American financial institutions," Finance Research Letters, Elsevier, vol. 42(C).
    13. Francesco Caloia & Andrea Cipollini & Silvia Muzzioli, 2018. "On the financial connectedness of the commodity market: a replication of the Diebold and Yilmaz (2012) study," Department of Economics 0131, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    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. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    16. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2023. "Long monthly European temperature series and the North Atlantic Oscillation," Energy Economics, Elsevier, vol. 126(C).
    17. Philipp Otto & Wolfgang Schmid, 2023. "A general framework for spatial GARCH models," Statistical Papers, Springer, vol. 64(5), pages 1721-1747, October.

  43. Khalifa, Ahmed & Caporin, Massimiliano & Hammoudeh, Shawkat, 2015. "Spillovers between energy and FX markets: The importance of asymmetry, uncertainty and business cycle," Energy Policy, Elsevier, vol. 87(C), pages 72-82.

    Cited by:

    1. Ahmed, Walid M.A., 2018. "On the interdependence of natural gas and stock markets under structural breaks," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 149-161.
    2. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Asymmetric spillovers and connectedness between crude oil and currency markets using high-frequency data," Resources Policy, Elsevier, vol. 77(C).
    3. Lin, Boqiang & Bai, Rui, 2021. "Oil prices and economic policy uncertainty: Evidence from global, oil importers, and exporters’ perspective," Research in International Business and Finance, Elsevier, vol. 56(C).
    4. Qiang Ji & Syed Jawad Hussain Shahzad & Elie Bouri & Muhammad Tahir Suleman, 2020. "Dynamic structural impacts of oil shocks on exchange rates: lessons to learn," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-19, December.
    5. Kumar, Pawan & Singh, Vipul Kumar, 2022. "Does crude oil fire the emerging markets currencies contagion spillover? A systemic perspective," Energy Economics, Elsevier, vol. 116(C).
    6. Li, Xiao-Ping & Zhou, Chun-Yang & Wu, Chong-Feng, 2017. "Jump spillover between oil prices and exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 656-667.
    7. Ahmed, Walid M.A., 2017. "On the dynamic interactions between energy and stock markets under structural shifts: Evidence from Egypt," Research in International Business and Finance, Elsevier, vol. 42(C), pages 61-74.

  44. Caporin, Massimiliano & Velo, Gabriel G., 2015. "Realized range volatility forecasting: Dynamic features and predictive variables," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 98-112.

    Cited by:

    1. Shawkat Hammoudeh & Michael McAleer, 2014. "Advances in Financial Risk Management andEconomic Policy Uncertainty: An Overview," Documentos de Trabajo del ICAE 2014-17, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Gong, Xu & Lin, Boqiang, 2018. "Structural changes and out-of-sample prediction of realized range-based variance in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 27-39.
    3. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
    4. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).
    5. Ma, Feng & Liu, Jing & Huang, Dengshi & Chen, Wang, 2017. "Forecasting the oil futures price volatility: A new approach," Economic Modelling, Elsevier, vol. 64(C), pages 560-566.
    6. 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.

  45. Billio, Monica & Caporin, Massimiliano & Costola, Michele, 2015. "Backward/forward optimal combination of performance measures for equity screening," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 63-83.
    See citations under working paper version above.
  46. Asai, Manabu & Caporin, Massimiliano & McAleer, Michael, 2015. "Forecasting Value-at-Risk using block structure multivariate stochastic volatility models," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 40-50.
    See citations under working paper version above.
  47. Baldovin, Fulvio & Caporin, Massimiliano & Caraglio, Michele & Stella, Attilio L. & Zamparo, Marco, 2015. "Option pricing with non-Gaussian scaling and infinite-state switching volatility," Journal of Econometrics, Elsevier, vol. 187(2), pages 486-497.
    See citations under working paper version above.
  48. Massimiliano Caporin & Angelo Ranaldo & Gabriel G. Velo, 2015. "Precious metals under the microscope: a high-frequency analysis," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 743-759, May.
    See citations under working paper version above.
  49. Caporin, Massimiliano & Jimenez-Martin, Juan-Angel & Gonzalez-Serrano, Lydia, 2014. "Currency hedging strategies in strategic benchmarks and the global and Euro sovereign financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 159-177.
    See citations under working paper version above.
  50. Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
    See citations under working paper version above.
  51. Massimiliano Caporin & Grégory M. Jannin & Francesco Lisi & Bertrand B. Maillet, 2014. "A Survey On The Four Families Of Performance Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 28(5), pages 917-942, December.
    See citations under working paper version above.
  52. Aielli, Gian Piero & Caporin, Massimiliano, 2014. "Variance clustering improved dynamic conditional correlation MGARCH estimators," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 556-576.
    See citations under working paper version above.
  53. Massimiliano Caporin & Juliusz Preś, 2013. "Forecasting Temperature Indices Density with Time‐Varying Long‐Memory Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(4), pages 339-352, July.

    Cited by:

    1. Cui, Hairong & Zhou, Ying & Dzandu, Michael D. & Tang, Yinshan & Lu, Xunfa, 2019. "Is temperature-index derivative suitable for China?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    2. Massimiliano Caporin & Rangan Gupta, 2017. "Time-varying persistence in US inflation," Empirical Economics, Springer, vol. 53(2), pages 423-439, September.
    3. Caporin, Massimiliano & Fontini, Fulvio, 2014. "The Value of Protecting Venice from the Acqua Alta Phenomenon under Different Local Sea Level Rises," MPRA Paper 53779, University Library of Munich, Germany.
    4. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2013. "Stylized Facts and Dynamic Modeling of High-frequency Data on Precious Metals," Working Papers on Finance 1318, University of St. Gallen, School of Finance.
    5. Mehmet Balcilar & Rangan Gupta & Charl Jooste, 2014. "Analysing South Africa's Inflation Persistence Using an ARFIMA Model with Markov-Switching Fractional Differencing Parameter," Working Papers 201440, University of Pretoria, Department of Economics.
    6. Luisa Bisaglia & Matteo Grigoletto, 2018. "A new time-varying model for forecasting long-memory series," Papers 1812.07295, arXiv.org.
    7. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2014. "Precious Metals Under the Microscope: A High-Frequency Analysis," Working Papers on Finance 1409, University of St. Gallen, School of Finance.
    8. Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.

  54. Caporin, Massimiliano & Lisi, Francesco, 2013. "A Conditional Single Index model with Local Covariates for detecting and evaluating active portfolio management," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 236-249.

    Cited by:

    1. Chia-Lin Chang & David Allen & Michael McAleer, 2013. "Recent Developments in Financial Economics and Econometrics: An Overview," Documentos de Trabajo del ICAE 2013-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Ortas, E. & Salvador, M. & Moneva, J.M., 2015. "Improved beta modeling and forecasting: An unobserved component approach with conditional heteroscedastic disturbances," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 27-51.
    3. Jiang, Minqi & Liu, Jiapeng & Zhang, Lu, 2021. "An extended regularized Kalman filter based on Genetic Algorithm: Application to dynamic asset pricing models," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 28-44.
    4. Yang, Tingting & Huang, Xiaoxia, 2022. "Two new mean–variance enhanced index tracking models based on uncertainty theory," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).

  55. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know about the Dynamic Conditional Correlation Representation," Econometrics, MDPI, vol. 1(1), pages 1-12, June.
    See citations under working paper version above.
  56. Aielli, Gian Piero & Caporin, Massimiliano, 2013. "Fast clustering of GARCH processes via Gaussian mixture models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 205-222.

    Cited by:

    1. Chia-Lin Chang & David E. Allen & Michael McAleer & Teodosio Perez Amaral, 2013. "Risk Modelling and Management: An Overview," Tinbergen Institute Discussion Papers 13-085/III, Tinbergen Institute, revised 08 Jul 2013.
    2. B. Lafuente-Rego & P. D’Urso & J. A. Vilar, 2020. "Robust fuzzy clustering based on quantile autocovariances," Statistical Papers, Springer, vol. 61(6), pages 2393-2448, December.
    3. Takashi Isogai, 2015. "An Empirical Study of the Dynamic Correlation of Japanese Stock Returns," Bank of Japan Working Paper Series 15-E-7, Bank of Japan.
    4. Takashi Isogai, 2017. "Analysis of Dynamic Correlation of Japanese Stock Returns with Network Clustering," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 24(3), pages 193-220, September.

  57. Caporin, Massimiliano & Ranaldo, Angelo & Santucci de Magistris, Paolo, 2013. "On the predictability of stock prices: A case for high and low prices," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5132-5146.
    See citations under working paper version above.
  58. Maria Kasch & Massimiliano Caporin, 2013. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," Journal of Financial Econometrics, Oxford University Press, vol. 11(4), pages 706-742, September.
    See citations under working paper version above.
  59. Caporin, Massimiliano, 2013. "Equity and CDS sector indices: Dynamic models and risk hedging," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 261-275.

    Cited by:

    1. Shawkat Hammoudeh & Michael McAleer, 2012. "Risk Management and Financial Derivatives: An Overview," Working Papers in Economics 12/10, University of Canterbury, Department of Economics and Finance.
    2. Caporin, Massimiliano & Jimenez-Martin, Juan-Angel & Gonzalez-Serrano, Lydia, 2014. "Currency hedging strategies in strategic benchmarks and the global and Euro sovereign financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 159-177.
    3. Ayben Koy, 2015. "The Relationship Between Credit Default Swap Spreads, Equity Indices and Sector Equity Indices: An Empirical Study on Istanbul Stock Exchange," Proceedings of International Academic Conferences 2604117, International Institute of Social and Economic Sciences.
    4. Naji Jalkh & Elie Bouri & Xuan Vinh Vo & Anupam Dutta, 2021. "Hedging the risk of travel and leisure stocks: The role of crude oil," Tourism Economics, , vol. 27(7), pages 1337-1356, November.
    5. Choi, Sun-Yong, 2022. "Credit risk interdependence in global financial markets: Evidence from three regions using multiple and partial wavelet approaches," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    6. Wajdi Hamma & Ahmed Ghorbel & Anis Jarboui, 2021. "Hedging Islamic and conventional stock markets with other financial assets: comparison between competing DCC models on hedging effectiveness," Journal of Asset Management, Palgrave Macmillan, vol. 22(3), pages 179-199, May.

  60. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    See citations under working paper version above.
  61. Caporin, Massimiliano & Preś, Juliusz & Torro, Hipolit, 2012. "Model based Monte Carlo pricing of energy and temperature Quanto options," Energy Economics, Elsevier, vol. 34(5), pages 1700-1712.
    See citations under working paper version above.
  62. M. Bonato & M. Caporin & A. Ranaldo, 2012. "A forecast-based comparison of restricted Wishart autoregressive models for realized covariance matrices," The European Journal of Finance, Taylor & Francis Journals, vol. 18(9), pages 761-774, October.

    Cited by:

    1. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    2. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    4. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  63. Caporin, Massimiliano & Preś, Juliusz, 2012. "Modelling and forecasting wind speed intensity for weather risk management," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3459-3476.
    See citations under working paper version above.
  64. Massimiliano Caporin & Michael McAleer, 2012. "Do We Really Need Both Bekk And Dcc? A Tale Of Two Multivariate Garch Models," Journal of Economic Surveys, Wiley Blackwell, vol. 26(4), pages 736-751, September.
    See citations under working paper version above.
  65. Massimiliano Caporin & Paolo Santucci de Magistris, 2012. "On the evaluation of marginal expected shortfall," Applied Economics Letters, Taylor & Francis Journals, vol. 19(2), pages 175-179, February.

    Cited by:

    1. 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.

  66. Francesco Lisi & Massimiliano Caporin, 2012. "On the role of risk in the Morningstar rating for mutual funds," Quantitative Finance, Taylor & Francis Journals, vol. 12(10), pages 1477-1486, October.

    Cited by:

    1. Kozo Omori & Tomoki Kitamura, 2021. "Managers’ skills and fund flows in the Japanese mutual fund market," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 39(4), pages 675-696, November.
    2. Daniel Chiew & Judy Qiu & Sirimon Treepongkaruna & Jiping Yang & Chenxiao Shi, 2019. "The predictive ability of the expected utility-entropy based fund rating approach: A comparison investigation with Morningstar ratings in US," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-22, April.
    3. Massimiliano Caporin & Grégory M. Jannin & Francesco Lisi & Bertrand Maillet, 2014. "A Survey on the Four Families of Performance Measures," Post-Print hal-01243416, HAL.

  67. Caporin, Massimiliano & Lisi, Francesco, 2011. "Comparing and selecting performance measures using rank correlations," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 5, pages 1-34.
    See citations under working paper version above.
  68. Massimiliano Caporin & Michael McAleer, 2011. "Thresholds, news impact surfaces and dynamic asymmetric multivariate GARCH," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 65(2), pages 125-163, May.
    See citations under working paper version above.
  69. Massimiliano Caporin & Michael McAleer, 2010. "The Ten Commandments For Managing Investments," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 196-200, February.

    Cited by:

    1. Chang, C-L. & Jiménez-Martín, J.A. & McAleer, M.J. & Pérez-Amaral, T., 2011. "Risk Management of Risk under the Basel Accord: Forecasting Value-at-Risk of VIX Futures," Econometric Institute Research Papers EI 2011-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Michael McAleer & Juan-Ángel Jiménez-Martín & Teodosio Pérez Amaral, 2012. "Has the Basel Accord Improved Risk Management During the Global Financial Crisis?," Documentos de Trabajo del ICAE 2012-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Oct 2012.
    3. Michael McAleer & Juan-Ángel Jiménez-Martín & Teodosio Pérez-Amaral, 2010. "GFC-Robust Risk Management Strategies under the Basel Accord," Working Papers in Economics 10/63, University of Canterbury, Department of Economics and Finance.
    4. Paulo Araújo Santos & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "GFC-Robust Risk Management Under the Basel Accord Using Extreme Value Methodologies," Working Papers in Economics 11/28, University of Canterbury, Department of Economics and Finance.
    5. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "Has the Basel II Accord Encouraged Risk Management During the 2008-09 Financial Crisis?," CIRJE F-Series CIRJE-F-643, CIRJE, Faculty of Economics, University of Tokyo.
    6. Michael McAleer, 2009. "The Ten Commandments for Optimizing Value-at-Risk and Daily Capital Charges," CIRJE F-Series CIRJE-F-652, CIRJE, Faculty of Economics, University of Tokyo.
    7. Michael McAleer & Juan-à ngel Jiménez-Martín & Teodosio Pérez-Amaral, 2011. "International Evidence on GFC-robust Forecasts for Risk Management under the Basel Accord," KIER Working Papers 757, Kyoto University, Institute of Economic Research.
    8. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "Optimal Risk Management Before, During and After the 2008-09 Financial Crisis," CIRJE F-Series CIRJE-F-667, CIRJE, Faculty of Economics, University of Tokyo.
    9. Roberto Casarin & Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures," Documentos de Trabajo del ICAE 2011-32, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

  70. Billio, Monica & Caporin, Massimiliano, 2010. "Market linkages, variance spillovers, and correlation stability: Empirical evidence of financial contagion," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2443-2458, November.
    See citations under working paper version above.
  71. Massimiliano Caporin & Francesco Lisi, 2010. "Misspecification tests for periodic long memory GARCH models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(1), pages 47-62, March.

    Cited by:

    1. Souhir Ben Amor & Heni Boubaker & Lotfi Belkacem, 2022. "A Dual Generalized Long Memory Modelling for Forecasting Electricity Spot Price: Neural Network and Wavelet Estimate," Papers 2204.08289, arXiv.org.
    2. Bordignon, Silvano & Caporin, Massimiliano & Lisi, Francesco, 2007. "Generalised long-memory GARCH models for intra-daily volatility," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5900-5912, August.
    3. Souhir Ben Amor & Heni Boubaker & Lotfi Belkacem, 2022. "Predictive Accuracy of a Hybrid Generalized Long Memory Model for Short Term Electricity Price Forecasting," Papers 2204.09568, arXiv.org.

  72. Massimiliano Caporin & Michael McAleer, 2010. "A Scientific Classification Of Volatility Models," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 192-195, February.
    See citations under working paper version above.
  73. Silvano Bordignon & Massimiliano Caporin & Francesco Lisi, 2009. "Periodic Long-Memory GARCH Models," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 60-82.

    Cited by:

    1. Leschinski, Christian & Sibbertsen, Philipp, 2014. "Model Order Selection in Seasonal/Cyclical Long Memory Models," Hannover Economic Papers (HEP) dp-535, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Manabu Asai & Shelton Peiris & Michael McAleer, 2017. "Realized Stochastic Volatility Models with Generalized Gegenbauer Long Memory," Documentos de Trabajo del ICAE 2017-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    3. Caporin, Massimiliano & Chang, Chia-Lin & McAleer, Michael, 2019. "Are the S&P 500 index and crude oil, natural gas and ethanol futures related for intra-day data?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 50-70.
    4. Caporin, Massimiliano & Preś, Juliusz & Torro, Hipolit, 2012. "Model based Monte Carlo pricing of energy and temperature Quanto options," Energy Economics, Elsevier, vol. 34(5), pages 1700-1712.
    5. Voges, Michelle & Leschinski, Christian & Sibbertsen, Philipp, 2017. "Seasonal long memory in intraday volatility and trading volume of Dow Jones stocks," Hannover Economic Papers (HEP) dp-599, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2013. "Stylized Facts and Dynamic Modeling of High-frequency Data on Precious Metals," Working Papers on Finance 1318, University of St. Gallen, School of Finance.
    7. Eduardo Rossi & Dean Fantazzini, 2015. "Long Memory and Periodicity in Intraday Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 13(4), pages 922-961.
    8. Arteche, Josu & García-Enríquez, Javier, 2017. "Singular Spectrum Analysis for signal extraction in Stochastic Volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 85-98.
    9. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2014. "Precious Metals Under the Microscope: A High-Frequency Analysis," Working Papers on Finance 1409, University of St. Gallen, School of Finance.
    10. Massimiliano Caporin & Francesco Lisi, 2010. "Misspecification tests for periodic long memory GARCH models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(1), pages 47-62, March.
    11. Bordignon, Silvano & Caporin, Massimiliano & Lisi, Francesco, 2007. "Generalised long-memory GARCH models for intra-daily volatility," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5900-5912, August.
    12. Heni Boubaker & Bassem Saidane & Mouna Ben Saad Zorgati, 2022. "Modelling the dynamics of stock market in the gulf cooperation council countries: evidence on persistence to shocks," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-22, December.
    13. Khalifa, Ahmed & Caporin, Massimiliano & Hammoudeh, Shawkat, 2015. "Spillovers between energy and FX markets: The importance of asymmetry, uncertainty and business cycle," Energy Policy, Elsevier, vol. 87(C), pages 72-82.
    14. Leschinski, Christian & Sibbertsen, Philipp, 2019. "Model order selection in periodic long memory models," Econometrics and Statistics, Elsevier, vol. 9(C), pages 78-94.
    15. Rajesh Mohnot, 2011. "Forecasting Forex Volatility In Turbulent Times," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 5(1), pages 27-38.

  74. Billio, Monica & Caporin, Massimiliano, 2009. "A generalized Dynamic Conditional Correlation model for portfolio risk evaluation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2566-2578.
    See citations under working paper version above.
  75. Massimiliano Caporin & Michael McAleer, 2008. "Scalar BEKK and indirect DCC," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 537-549.

    Cited by:

    1. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About the Dynamic Conditional Correlation Representation," Working Papers in Economics 13/21, University of Canterbury, Department of Economics and Finance.
    2. Shawkat M. Hammoudeh & Yuan Yuan & Michael McAleer, 2009. "Exchange Rate and Industrial Commodity Volatility Transmissions and Hedging Strategies," CIRJE F-Series CIRJE-F-668, CIRJE, Faculty of Economics, University of Tokyo.
    3. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About DCC," Documentos de Trabajo del ICAE 2013-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    4. Chang, C-L. & McAleer, M.J. & Wang, Y., 2016. "Testing Co-Volatility Spillovers for Natural Gas Spot, Futures and ETF Spot using Dynamic Conditional Covariances," Econometric Institute Research Papers EI2016-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Trancoso, Tiago, 2014. "Emerging markets in the global economic network: Real(ly) decoupling?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 499-510.
    6. Caporin, M. & McAleer, M.J., 2010. "Threshold, news impact surfaces and dynamic asymmetric multivariate GARCH," Econometric Institute Research Papers EI 2010-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Alexandridis, G. & Sahoo, S. & Visvikis, I., 2017. "Economic information transmissions and liquidity between shipping markets: New evidence from freight derivatives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 98(C), pages 82-104.
    8. Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 12/06, University of Canterbury, Department of Economics and Finance.
    9. Shawkat M. Hammoudeh & Yuan Yuan & Michael McAleer, 2010. "Exchange Rate and Industrial Commodity Volatility Transmissions, Asymmetries and Hedging Strategies," CIRJE F-Series CIRJE-F-741, CIRJE, Faculty of Economics, University of Tokyo.
    10. Chia-Lin Chang & Hui-Kuang Hsu & Michael McAleer, 2013. "Is Small Beautiful? Size Effects of Volatility Spillovers for Firm Performance and Exchange Rates in Tourism," Documentos de Trabajo del ICAE 2013-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    11. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    12. Chia-Lin Chang & Michael McAleer & Yu-Ann Wang, 2016. "Modelling Volatility Spillovers for Bio-ethanol, Sugarcane and Corn Spot and Futures Prices," Tinbergen Institute Discussion Papers 16-014/III, Tinbergen Institute, revised 30 Jan 2017.
    13. Roengchai Tansuchat & Chia-Lin Chang & Michael McAleer, 2010. "Crude Oil Hedging Strategies Using Dynamic Multivariate GARCH," Working Papers in Economics 10/03, University of Canterbury, Department of Economics and Finance.
    14. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    15. Caporin, M. & McAleer, M.J., 2010. "Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models," Econometric Institute Research Papers EI 2010-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Weiping Li & Wenwen Liu, 2021. "Investor sentiment‐styled index in index futures market," Review of Financial Economics, John Wiley & Sons, vol. 39(1), pages 51-72, January.
    17. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," CIRJE F-Series CIRJE-F-638, CIRJE, Faculty of Economics, University of Tokyo.
    18. Adams, Zeno & Fuess, Roland & Glueck, Thorsten, 2016. "Are Correlations Constant? Empirical and Theoretical Results on Popular Correlation Models in Finance," Working Papers on Finance 1613, University of St. Gallen, School of Finance.
    19. Michael McAleer, 2009. "The Ten Commandments for Optimizing Value-at-Risk and Daily Capital Charges," CIRJE F-Series CIRJE-F-652, CIRJE, Faculty of Economics, University of Tokyo.
    20. Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
    21. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
    22. Caporin, Massimiliano & Jimenez-Martin, Juan-Angel & Gonzalez-Serrano, Lydia, 2014. "Currency hedging strategies in strategic benchmarks and the global and Euro sovereign financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 159-177.
    23. Broadstock, David C. & Filis, George, 2014. "Oil price shocks and stock market returns: New evidence from the United States and China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 417-433.
    24. Chang, Chia-Lin & González-Serrano, Lydia & Jimenez-Martin, Juan-Angel, 2013. "Currency hedging strategies using dynamic multivariate GARCH," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 164-182.
    25. Michael McAleer & Massimiliano Caporin, 2011. "Ranking Multivariate GARCH Models by Problem Dimension:An Empirical Evaluation," KIER Working Papers 778, Kyoto University, Institute of Economic Research.
    26. Zhang, Wenting & He, Xie & Hamori, Shigeyuki, 2022. "Volatility spillover and investment strategies among sustainability-related financial indexes: Evidence from the DCC-GARCH-based dynamic connectedness and DCC-GARCH t-copula approach," International Review of Financial Analysis, Elsevier, vol. 83(C).
    27. Boldanov, Rustam & Degiannakis, Stavros & Filis, George, 2017. "Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries," MPRA Paper 80435, University Library of Munich, Germany.
    28. David E. Allen & Michael McAleer & Robert Powell & Abhay K. Singh, 2017. "Volatility spillover and multivariate volatility impulse response analysis of GFC news events," Applied Economics, Taylor & Francis Journals, vol. 49(33), pages 3246-3262, July.
    29. Bouoiyour, Jamal & Selmi, Refk, 2013. "Commodity Price Uncertainty and Manufactured Exports in Morocco and Tunisia: Some Insights from a Novel GARCH Model," MPRA Paper 53412, University Library of Munich, Germany, revised Nov 2013.
    30. David C Broadstock & Hong Cao & Dayong Zhang, 2012. "Oil Shocks and their Impact on Energy Related Stocks in China," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 137, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    31. Katsiampa, Paraskevi & Yarovaya, Larisa & Zięba, Damian, 2022. "High-frequency connectedness between Bitcoin and other top-traded crypto assets during the COVID-19 crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    32. H. J. Turtle & Kainan Wang, 2014. "Modeling Conditional Covariances With Economic Information Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 217-236, April.
    33. Tsouknidis, Dimitris A., 2016. "Dynamic volatility spillovers across shipping freight markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 90-111.
    34. Caporin, Massimiliano, 2013. "Equity and CDS sector indices: Dynamic models and risk hedging," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 261-275.
    35. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".
    36. G.K., Chetan Kumar & K.B., Rangappa & S., Suchitra, 2022. "Normative analysis of the impact of Covid-19 on prominent sectors of Indian economy by using ARCH Model," MPRA Paper 114027, University Library of Munich, Germany.
    37. Lv, Xin & Lien, Donald & Yu, Chang, 2020. "Who affects who? Oil price against the stock return of oil-related companies: Evidence from the U.S. and China," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 85-100.
    38. Tiago Trancoso, 2013. "Global macroeconomic interdependence: a minimum spanning tree approach," Review of Applied Socio-Economic Research, Pro Global Science Association, vol. 5(1), pages 179-189, June.
    39. Massimiliano Caporin & Michael McAleer, 2009. "A Scientific Classification of Volatility Models," Documentos de Trabajo del ICAE 2009-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    40. Domingo Rodríguez Benavides & Ignacio Perrotini Hernández, 2019. "Las correlaciones dinámicas de contagio financiero:Estados Unidos y América Latina," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(2), pages 151-168, Abril-Jun.
    41. G.K. Chetan Kumar & K.B. Rangappa & S. Suchitra, 2022. "Normative analysis of the impact of Covid-19 on prominent sectors of Indian economy by using ARCH Model," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(631), S), pages 151-164, Summer.
    42. Filippidis, Michail & Filis, George & Kizys, Renatas, 2020. "Oil price shocks and EMU sovereign yield spreads," Energy Economics, Elsevier, vol. 86(C).
    43. Jessica Leutert, 2018. "The Swiss franc safety premium," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-21, December.

  76. Monica Billio & Massimiliano Caporin & Guido Cazzavillan, 2008. "Dating EU15 monthly business cycle jointly using GDP and IPI," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2007(3), pages 333-366.
    See citations under working paper version above.
  77. Bordignon, Silvano & Caporin, Massimiliano & Lisi, Francesco, 2007. "Generalised long-memory GARCH models for intra-daily volatility," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5900-5912, August.

    Cited by:

    1. Richard Hunt & Shelton Peiris & Neville Weber, 2022. "Estimation methods for stationary Gegenbauer processes," Statistical Papers, Springer, vol. 63(6), pages 1707-1741, December.
    2. Manabu Asai & Shelton Peiris & Michael McAleer, 2017. "Realized Stochastic Volatility Models with Generalized Gegenbauer Long Memory," Documentos de Trabajo del ICAE 2017-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    3. Shelton Peiris & Manabu Asai & Michael McAleer, 2016. "Estimating and forecasting generalized fractional Long memory stochastic volatility models," Documentos de Trabajo del ICAE 2016-08, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    4. Caporin, Massimiliano & Chang, Chia-Lin & McAleer, Michael, 2019. "Are the S&P 500 index and crude oil, natural gas and ethanol futures related for intra-day data?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 50-70.
    5. Caporin, Massimiliano & Preś, Juliusz & Torro, Hipolit, 2012. "Model based Monte Carlo pricing of energy and temperature Quanto options," Energy Economics, Elsevier, vol. 34(5), pages 1700-1712.
    6. Voges, Michelle & Leschinski, Christian & Sibbertsen, Philipp, 2017. "Seasonal long memory in intraday volatility and trading volume of Dow Jones stocks," Hannover Economic Papers (HEP) dp-599, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    7. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2013. "Stylized Facts and Dynamic Modeling of High-frequency Data on Precious Metals," Working Papers on Finance 1318, University of St. Gallen, School of Finance.
    8. Borovkova, Svetlana & Permana, Ferry J., 2009. "Implied volatility in oil markets," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2022-2039, April.
    9. Asai Manabu & Peiris Shelton & McAleer Michael & Allen David E., 2020. "Cointegrated Dynamics for a Generalized Long Memory Process: Application to Interest Rates," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-18, January.
    10. Eduardo Rossi & Dean Fantazzini, 2015. "Long Memory and Periodicity in Intraday Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 13(4), pages 922-961.
    11. Boubaker, Heni & Sghaier, Nadia, 2015. "Semiparametric generalized long-memory modeling of some mena stock market returns: A wavelet approach," Economic Modelling, Elsevier, vol. 50(C), pages 254-265.
    12. Souhir Ben Amor & Heni Boubaker & Lotfi Belkacem, 2022. "A Dual Generalized Long Memory Modelling for Forecasting Electricity Spot Price: Neural Network and Wavelet Estimate," Papers 2204.08289, arXiv.org.
    13. Josu Arteche, 2012. "Standard and seasonal long memory in volatility: an application to Spanish inflation," Empirical Economics, Springer, vol. 42(3), pages 693-712, June.
    14. Artiach, Miguel & Arteche, Josu, 2012. "Doubly fractional models for dynamic heteroscedastic cycles," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2139-2158.
    15. Arteche, Josu & García-Enríquez, Javier, 2017. "Singular Spectrum Analysis for signal extraction in Stochastic Volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 85-98.
    16. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2014. "Precious Metals Under the Microscope: A High-Frequency Analysis," Working Papers on Finance 1409, University of St. Gallen, School of Finance.
    17. Heni Boubaker & Nadia Sghaier, 2014. "Semiparametric Generalized Long Memory Modelling of GCC Stock Market Returns: A Wavelet Approach," Working Papers 2014-66, Department of Research, Ipag Business School.
    18. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
    19. Tommaso Proietti & Federico Maddanu, 2021. "Modelling Cycles in Climate Series: the Fractional Sinusoidal Waveform Process," CEIS Research Paper 518, Tor Vergata University, CEIS, revised 19 Oct 2021.
    20. Heni Boubaker & Bassem Saidane & Mouna Ben Saad Zorgati, 2022. "Modelling the dynamics of stock market in the gulf cooperation council countries: evidence on persistence to shocks," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-22, December.
    21. Khalifa, Ahmed & Caporin, Massimiliano & Hammoudeh, Shawkat, 2015. "Spillovers between energy and FX markets: The importance of asymmetry, uncertainty and business cycle," Energy Policy, Elsevier, vol. 87(C), pages 72-82.
    22. Souhir Ben Amor & Heni Boubaker & Lotfi Belkacem, 2022. "Predictive Accuracy of a Hybrid Generalized Long Memory Model for Short Term Electricity Price Forecasting," Papers 2204.09568, arXiv.org.
    23. Trinidad Segovia, J.E. & Fernández-Martínez, M. & Sánchez-Granero, M.A., 2019. "A novel approach to detect volatility clusters in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    24. Alexandra Chronopoulou & Frederi Viens, 2012. "Estimation and pricing under long-memory stochastic volatility," Annals of Finance, Springer, vol. 8(2), pages 379-403, May.
    25. Asai, M. & Peiris, S. & McAleer, M.J. & Allen, D.E., 2018. "Cointegrated Dynamics for A Generalized Long Memory Process," Econometric Institute Research Papers EI 2018-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    26. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  78. Massimiliano Caporin, 2007. "Variance (Non) Causality in Multivariate GARCH," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 1-24.

    Cited by:

    1. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    2. 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).
    3. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    4. Christian Conrad & Menelaos Karanasos, 2008. "Negative Volatility Spillovers in the Unrestricted ECCC-GARCH Model," KOF Working papers 08-189, KOF Swiss Economic Institute, ETH Zurich.
    5. Yip, Iris W.H. & So, Mike K.P., 2009. "Simplified specifications of a multivariate generalized autoregressive conditional heteroscedasticity model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(2), pages 327-340.

  79. Massimiliano Caporin & Michael McAleer, 2006. "Dynamic Asymmetric GARCH," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 385-412.

    Cited by:

    1. Beg, A.B.M. Rabiul Alam & Anwar, Sajid, 2012. "Sources of volatility persistence: A case study of the U.K. pound/U.S. dollar exchange rate returns," The North American Journal of Economics and Finance, Elsevier, vol. 23(2), pages 165-184.
    2. 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.
    3. Caporin, M. & McAleer, M.J., 2010. "Threshold, news impact surfaces and dynamic asymmetric multivariate GARCH," Econometric Institute Research Papers EI 2010-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Rituparna Sen & Pulkit Mehrotra, 2016. "Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 137-150, June.
    5. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    6. Ederington, Louis H. & Guan, Wei, 2010. "How asymmetric is U.S. stock market volatility?," Journal of Financial Markets, Elsevier, vol. 13(2), pages 225-248, May.
    7. A. B. M. Rabiul Alam Beg & Sajid Anwar, 2014. "Detecting volatility persistence in GARCH models in the presence of the leverage effect," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2205-2213, December.
    8. Lönnbark, Carl, 2017. "Long vs. short term asymmetry in volatility and the term structure of risk," Finance Research Letters, Elsevier, vol. 23(C), pages 202-209.
    9. Chorro, Christophe & Guégan, Dominique & Ielpo, Florian & Lalaharison, Hanjarivo, 2018. "Testing for leverage effects in the returns of US equities," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 290-306.
    10. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    11. Asai, Manabu & McAleer, Michael, 2008. "A Portfolio Index GARCH model," International Journal of Forecasting, Elsevier, vol. 24(3), pages 449-461.
    12. Carl Lönnbark, 2016. "Asymmetry with respect to the memory in stock market volatilities," Empirical Economics, Springer, vol. 50(4), pages 1409-1419, June.
    13. Ederington, Louis H. & Guan, Wei, 2013. "The cross-sectional relation between conditional heteroskedasticity, the implied volatility smile, and the variance risk premium," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3388-3400.
    14. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    15. Mariana Petrova & Teodor Todorov, 2023. "Empirical Testing of Models of Autoregressive Conditional Heteroscedasticity Used for Prediction of the Volatility of Bulgarian Investment Funds," Risks, MDPI, vol. 11(11), pages 1-30, November.
    16. Billio, Monica & Caporin, Massimiliano, 2009. "A generalized Dynamic Conditional Correlation model for portfolio risk evaluation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2566-2578.
    17. Mazzotta, Stefano, 2008. "How important is asymmetric covariance for the risk premium of international assets?," Journal of Banking & Finance, Elsevier, vol. 32(8), pages 1636-1647, August.

  80. Monica Billio & Massimiliano Caporin, 2005. "Multivariate Markov switching dynamic conditional correlation GARCH representations for contagion analysis," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 14(2), pages 145-161, November.

    Cited by:

    1. Muñoz, Mª Pilar & Márquez, María Dolores & Sánchez, Josep A., 2011. "Contagion between United States and european markets during the recent crises," MPRA Paper 35993, University Library of Munich, Germany.
    2. Marie Brière & Ombretta Signori, 2009. "Do Inflation‐Linked Bonds Still Diversify?," European Financial Management, European Financial Management Association, vol. 15(2), pages 279-297, March.
    3. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
    4. Philippe Charlot & Olivier Darné & Zakaria Moussa, 2014. "Commodity returns co-movements: Fundamentals or "style" effect?," Working Papers hal-01093631, HAL.
    5. Lee, Hsiang-Tai, 2022. "Regime-switching angular correlation diversification," Finance Research Letters, Elsevier, vol. 50(C).
    6. Dark, Jonathan, 2015. "Futures hedging with Markov switching vector error correction FIEGARCH and FIAPARCH," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 269-285.
    7. Babaei Balderlou, Saharnaz & Ebrahimi Torki, Mahyar & Heidari, Hassan, 2013. "تفكيك اثرات منشأ شوك‌هاي نفتي بر همبستگی پویای بین رشد بخش صنعت و معدن و قیمت نفت خام در ایران [Separation of the Effects of Oil Price Shocks Origin on Dynamic Correlation between Growth of Industr," MPRA Paper 79257, University Library of Munich, Germany.
    8. Kaihua Deng, 2018. "Another Look at Large-Cap Stock Return Comovement: A Semi-Markov-Switching Approach," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 227-262, February.
    9. Jacques Jaussaud & Sophie Nivoix & Serge Rey, 2015. "The Great East Japan Earthquake and Stock Prices," Economics Bulletin, AccessEcon, vol. 35(2), pages 1237-1261.
    10. Cody Yu-Ling Hsiao & James Morley, 2015. "Debt and Financial Market Contagion," Discussion Papers 2015-02, School of Economics, The University of New South Wales.
    11. Serge Darolles & Jeremy Dudek & Gaëlle Le Fol, 2012. "Liquidity Contagion. The Emerging Sovereign Debt Markets example," Post-Print hal-01632803, HAL.
    12. Mehmet Balcilar & Riza Demirer & Shawkat Hammoudeh & Duc Khuong Nguyen, 2014. "Risk Spillovers across the Energy and Carbon Markets and Hedging Strategies for Carbon Risk," Working Papers 15-10, Eastern Mediterranean University, Department of Economics.
    13. Dungey, Mardi & Milunovich, George & Thorp, Susan, 2010. "Unobservable shocks as carriers of contagion," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 1008-1021, May.
    14. Yousaf, Imran & Beljid, Makram & Chaibi, Anis & Ajlouni, Ahmed AL, 2022. "Do volatility spillover and hedging among GCC stock markets and global factors vary from normal to turbulent periods? Evidence from the global financial crisis and Covid-19 pandemic crisis," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    15. Rotta, Pedro Nielsen & Pereira, Pedro L. Valls, 2013. "Analysis of contagion from the constant conditional correlation model with Markov regime switching," Textos para discussão 340, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    16. Idier, J., 2008. "Long term vs. short term comovements in stock markets: the use of Markov-switching multifractal models," Working papers 218, Banque de France.
    17. Haas, Markus & Liu, Ji-Chun, 2015. "Theory for a Multivariate Markov--switching GARCH Model with an Application to Stock Markets," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112855, Verein für Socialpolitik / German Economic Association.
    18. Lee, Hsiang-Tai & Tsang, Wei-Lun, 2011. "Cross hedging single stock with American Depositary Receipt and stock index futures," Finance Research Letters, Elsevier, vol. 8(3), pages 146-157, September.
    19. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    20. Laurini, Márcio Poletti & Mauad, Roberto Baltieri, 2015. "A common jump factor stochastic volatility model," Finance Research Letters, Elsevier, vol. 12(C), pages 2-10.
    21. Yudong Wang & Li Liu, 2016. "Crude oil and world stock markets: volatility spillovers, dynamic correlations, and hedging," Empirical Economics, Springer, vol. 50(4), pages 1481-1509, June.
    22. Abubakar Jamaladeen & David E. Omoregie & Samuel F. Onipede & Nafiu A. Bashir, 2022. "A regime-switching skew-normal model of contagion in some selected stock markets," SN Business & Economics, Springer, vol. 2(12), pages 1-20, December.
    23. Joshua C.C. Chan & Cody Yu-Ling Hsiao & Renée A. Fry-McKibbin, 2013. "A Regime Switching Skew-normal Model for Measuring Financial Crisis and Contagion," CAMA Working Papers 2013-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    24. Lin, Ling & Zhou, Zhongbao & Jiang, Yong & Ou, Yangchen, 2021. "Risk spillovers and hedge strategies between global crude oil markets and stock markets: Do regime switching processes combining long memory and asymmetry matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    25. Pan, Zhiyuan & Wang, Yudong & Yang, Li, 2014. "Hedging crude oil using refined product: A regime switching asymmetric DCC approach," Energy Economics, Elsevier, vol. 46(C), pages 472-484.
    26. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    27. Renée Fry-McKibbin & Cody Hsiao & Chrismin Tang, 2014. "Contagion and Global Financial Crises: Lessons from Nine Crisis Episodes," Open Economies Review, Springer, vol. 25(3), pages 521-570, July.
    28. Chan Joshua C.C. & Fry-McKibbin Renée A. & Hsiao Cody Yu-Ling, 2019. "A regime switching skew-normal model of contagion," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(1), pages 1-24, February.
    29. Pedro Nielsen Rotta & Pedro L. Valls Pereira, 2016. "Analysis of contagion from the dynamic conditional correlation model with Markov Regime switching," Applied Economics, Taylor & Francis Journals, vol. 48(25), pages 2367-2382, May.
    30. Billio, Monica & Caporin, Massimiliano & Frattarolo, Lorenzo & Pelizzon, Loriana, 2018. "Networks in risk spillovers: A multivariate GARCH perspective," SAFE Working Paper Series 225, Leibniz Institute for Financial Research SAFE.
    31. Bouoiyour, Jamal & Selmi, Refk & Miftah, Amal, 2015. "“Every cloud has a silver lining”; to what extent does the Arab Spring accelerate the integration among Arab monarchies?," MPRA Paper 70942, University Library of Munich, Germany.
    32. L. Bauwens & E. Otranto, 2018. "Nonlinearities and Regimes in Conditional Correlations with Different Dynamics," Working Paper CRENoS 201803, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    33. Mehmet Balcilar & Riza Demirer, 2022. "U.S. monetary policy and the predictability of global economic synchronization patterns," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 473-492, July.
    34. Lee, Hsiang-Tai, 2010. "Regime switching correlation hedging," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2728-2741, November.
    35. Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Working Papers hal-00980125, HAL.
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    Cited by:

    1. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    2. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    3. Trino-Manuel Ñíguez, 2008. "Volatility and VaR forecasting in the Madrid Stock Exchange," Spanish Economic Review, Springer;Spanish Economic Association, vol. 10(3), pages 169-196, September.
    4. J. Kim & A. Kartsaklas & M. Karanasos, 2005. "The volume–volatility relationship and the opening of the Korean stock market to foreign investors after the financial turmoil in 1997," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(3), pages 245-271, September.

  82. Stefano Bertelli & Massimiliano Caporin, 2002. "A note on calculating autocovariances of long‐memory processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(5), pages 503-508, September.

    Cited by:

    1. Kristoufek, Ladislav, 2015. "On the interplay between short and long term memory in the power-law cross-correlations setting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 218-222.
    2. Richard Hunt & Shelton Peiris & Neville Weber, 2022. "Estimation methods for stationary Gegenbauer processes," Statistical Papers, Springer, vol. 63(6), pages 1707-1741, December.
    3. Eduardo Rossi & Paolo Santucci de Magistris, 2009. "Long Memory and Tail dependence in Trading Volume and Volatility," CREATES Research Papers 2009-30, Department of Economics and Business Economics, Aarhus University.
    4. Shuping Shi & Jun Yu, 2023. "Volatility Puzzle: Long Memory or Antipersistency," Management Science, INFORMS, vol. 69(7), pages 3861-3883, July.
    5. Rohit Deo & Mengchen Hsieh & Clifford Hurvich, 2005. "Tracing the Source of Long Memory in Volatility," Econometrics 0501005, University Library of Munich, Germany.
    6. Hurvich, Clifford & Wang, Yi, 2009. "A Pure-Jump Transaction-Level Price Model Yielding Cointegration, Leverage, and Nonsynchronous Trading Effects," MPRA Paper 12575, University Library of Munich, Germany.

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