My bibliography
Save this item
Microstructure noise in the continuous case: The pre-averaging approach
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- repec:hal:journl:peer-00815564 is not listed on IDEAS
- Maria Elvira Mancino & Tommaso Mariotti & Giacomo Toscano, 2022. "Asymptotic Normality for the Fourier spot volatility estimator in the presence of microstructure noise," Papers 2209.08967, arXiv.org.
- Yuta Koike, 2013. "Limit Theorems for the Pre-averaged Hayashi-Yoshida Estimator with Random Sampling," Global COE Hi-Stat Discussion Paper Series gd12-276, Institute of Economic Research, Hitotsubashi University.
- Chen, Richard Y. & Mykland, Per A., 2017. "Model-free approaches to discern non-stationary microstructure noise and time-varying liquidity in high-frequency data," Journal of Econometrics, Elsevier, vol. 200(1), pages 79-103.
- Kong, Xin-Bing & Liu, Zhi & Zhou, Wang, 2019. "A rank test for the number of factors with high-frequency data," Journal of Econometrics, Elsevier, vol. 211(2), pages 439-460.
- repec:wyi:journl:002161 is not listed on IDEAS
- Dette, Holger & Golosnoy, Vasyl & Kellermann, Janosch, 2022. "Correcting Intraday Periodicity Bias in Realized Volatility Measures," Econometrics and Statistics, Elsevier, vol. 23(C), pages 36-52.
- Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
- Christensen, Kim & Podolskij, Mark & Vetter, Mathias, 2013.
"On covariation estimation for multivariate continuous Itô semimartingales with noise in non-synchronous observation schemes,"
Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 59-84.
- Kim Christensen & Mark Podolskij & Mathias Vetter, 2011. "On covariation estimation for multivariate continuous Itô semimartingales with noise in non-synchronous observation schemes," CREATES Research Papers 2011-53, Department of Economics and Business Economics, Aarhus University.
- Christensen, Kim & Oomen, Roel & Podolskij, Mark, 2010.
"Realised quantile-based estimation of the integrated variance,"
Journal of Econometrics, Elsevier, vol. 159(1), pages 74-98, November.
- Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
- Kim Christensen & Roel Oomen & Mark Podolskij, 2010. "Realised quantile-based estimation of the integrated variance," Post-Print hal-00732538, HAL.
- Almut Veraart & Luitgard Veraart, 2012.
"Stochastic volatility and stochastic leverage,"
Annals of Finance, Springer, vol. 8(2), pages 205-233, May.
- Almut E. D. Veraart & Luitgard A. M. Veraart, 2009. "Stochastic volatility and stochastic leverage," CREATES Research Papers 2009-20, Department of Economics and Business Economics, Aarhus University.
- Bellia, Mario & Christensen, Kim & Kolokolov, Aleksey & Pelizzon, Loriana & Renò, Roberto, 2022. "Do designated market makers provide liquidity during a flash crash?," SAFE Working Paper Series 270, Leibniz Institute for Financial Research SAFE, revised 2022.
- Song, Xinyu & Kim, Donggyu & Yuan, Huiling & Cui, Xiangyu & Lu, Zhiping & Zhou, Yong & Wang, Yazhen, 2021. "Volatility analysis with realized GARCH-Itô models," Journal of Econometrics, Elsevier, vol. 222(1), pages 393-410.
- Chaker, Selma, 2019. "The signal and the noise volatilities," Research in International Business and Finance, Elsevier, vol. 50(C), pages 79-105.
- Neil Shephard & Dacheng Xiu, 2012.
"Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices,"
Economics Papers
2012-W04, Economics Group, Nuffield College, University of Oxford.
- Neil Shephard & Dacheng Xiu, 2012. "Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices," Economics Series Working Papers 604, University of Oxford, Department of Economics.
- Silja Kinnebrock & Mark Podolskij, 2008.
"An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models,"
OFRC Working Papers Series
2008fe25, Oxford Financial Research Centre.
- Silja Kinnebrock & Mark Podolskij, 2008. "An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models," CREATES Research Papers 2008-23, Department of Economics and Business Economics, Aarhus University.
- Kim, Donggyu & Song, Xinyu & Wang, Yazhen, 2022.
"Unified discrete-time factor stochastic volatility and continuous-time Itô models for combining inference based on low-frequency and high-frequency,"
Journal of Multivariate Analysis, Elsevier, vol. 192(C).
- Donggyu Kim & Xinyu Song & Yazhen Wang, 2020. "Unified Discrete-Time Factor Stochastic Volatility and Continuous-Time Ito Models for Combining Inference Based on Low-Frequency and High-Frequency," Papers 2006.12039, arXiv.org.
- Aït-Sahalia, Yacine & Xiu, Dacheng, 2019. "A Hausman test for the presence of market microstructure noise in high frequency data," Journal of Econometrics, Elsevier, vol. 211(1), pages 176-205.
- Koike, Yuta, 2014. "Limit theorems for the pre-averaged Hayashi–Yoshida estimator with random sampling," Stochastic Processes and their Applications, Elsevier, vol. 124(8), pages 2699-2753.
- M. Podolskij & D. Ziggel, 2010. "New tests for jumps in semimartingale models," Statistical Inference for Stochastic Processes, Springer, vol. 13(1), pages 15-41, April.
- Podolskij, Mark & Vetter, Mathias, 2009.
"Bipower-type estimation in a noisy diffusion setting,"
Stochastic Processes and their Applications, Elsevier, vol. 119(9), pages 2803-2831, September.
- Mark Podolskij & Mathias Vetter, 2008. "Bipower-type estimation in a noisy diffusion setting," CREATES Research Papers 2008-25, Department of Economics and Business Economics, Aarhus University.
- Podolskij, Mark & Vetter, Mathias, 2008. "Bipower-type estimation in a noisy diffusion setting," Technical Reports 2008,24, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Aleksey Kolokolov & Giulia Livieri & Davide Pirino, 2022. "Testing for Endogeneity of Irregular Sampling Schemes," CEIS Research Paper 547, Tor Vergata University, CEIS, revised 19 Dec 2022.
- Virgil DAMIAN & Cosmin – Octavian CEPOI, 2016. "Volatility Estimators With High-Frequency Data From Bucharest Stock Exchange," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 247-264.
- Altmeyer, Randolf & Bibinger, Markus, 2015. "Functional stable limit theorems for quasi-efficient spectral covolatility estimators," Stochastic Processes and their Applications, Elsevier, vol. 125(12), pages 4556-4600.
- Minseog Oh & Donggyu Kim, 2024.
"Effect of the U.S.–China Trade War on Stock Markets: A Financial Contagion Perspective,"
Journal of Financial Econometrics, Oxford University Press, vol. 22(4), pages 954-1005.
- Minseog Oh & Donggyu Kim, 2021. "Effect of the U.S.--China Trade War on Stock Markets: A Financial Contagion Perspective," Papers 2111.09655, arXiv.org.
- Andersen, Torben G. & Bondarenko, Oleg & Todorov, Viktor & Tauchen, George, 2015.
"The fine structure of equity-index option dynamics,"
Journal of Econometrics, Elsevier, vol. 187(2), pages 532-546.
- Torben G. Andersen & Oleg Bondarenko & Viktor Todorov & George Tauchen, 2013. "The Fine Structure of Equity-Index Option Dynamics," CREATES Research Papers 2013-52, Department of Economics and Business Economics, Aarhus University.
- Richard Y. Chen & Per A. Mykland, 2015. "Model-Free Approaches to Discern Non-Stationary Microstructure Noise and Time-Varying Liquidity in High-Frequency Data," Papers 1512.06159, arXiv.org, revised Oct 2018.
- Christensen, Kim & Oomen, Roel & Renò, Roberto, 2022. "The drift burst hypothesis," Journal of Econometrics, Elsevier, vol. 227(2), pages 461-497.
- Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Decoupling the short- and long-term behavior of stochastic volatility," CREATES Research Papers 2017-26, Department of Economics and Business Economics, Aarhus University.
- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016.
"Do We Need High Frequency Data to Forecast Variances?,"
Annals of Economics and Statistics, GENES, issue 123-124, pages 135-174.
- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
- Wang, Fangfang, 2014. "Optimal design of Fourier estimator in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 708-722.
- repec:hal:journl:peer-00732538 is not listed on IDEAS
- Cecilia Mancini & Vanessa Mattiussi & Roberto Renò, 2015.
"Spot volatility estimation using delta sequences,"
Finance and Stochastics, Springer, vol. 19(2), pages 261-293, April.
- Cecilia Mancini & Vanessa Mattiussi & Roberto Reno', 2012. "Spot Volatility Estimation Using Delta Sequences," Working Papers - Mathematical Economics 2012-10, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
- Cai, T. Tony & Hu, Jianchang & Li, Yingying & Zheng, Xinghua, 2020. "High-dimensional minimum variance portfolio estimation based on high-frequency data," Journal of Econometrics, Elsevier, vol. 214(2), pages 482-494.
- David E. Allen & Michael McAleer & Marcel Scharth, 2009.
"Realized Volatility Risk,"
CARF F-Series
CARF-F-197, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, revised Jan 2010.
- David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," KIER Working Papers 753, Kyoto University, Institute of Economic Research.
- David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," Working Papers in Economics 10/26, University of Canterbury, Department of Economics and Finance.
- David E. Allen & Michael McAleer & Marcel Scharth, 2013. "Realized Volatility Risk," Tinbergen Institute Discussion Papers 13-092/III, Tinbergen Institute.
- David E. Allen & Michael McAleer & Marcel Scharth, 2013. "Realized volatility risk," Documentos de Trabajo del ICAE 2013-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- David E. Allen & Michael McAleer & Marcel Scharth, 2009. "Realized Volatility Risk," CIRJE F-Series CIRJE-F-693, CIRJE, Faculty of Economics, University of Tokyo.
- Aït-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2011.
"Ultra high frequency volatility estimation with dependent microstructure noise,"
Journal of Econometrics, Elsevier, vol. 160(1), pages 160-175, January.
- Yacine Ait-Sahalia & Per A. Mykland & Lan Zhang, 2005. "Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise," NBER Working Papers 11380, National Bureau of Economic Research, Inc.
- Ait-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2005. "Ultra high frequency volatility estimation with dependent microstructure noise," Discussion Paper Series 1: Economic Studies 2005,30, Deutsche Bundesbank.
- Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008.
"Measuring downside risk - realised semivariance,"
OFRC Working Papers Series
2008fe01, Oxford Financial Research Centre.
- Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk — realised semivariance," CREATES Research Papers 2008-42, Department of Economics and Business Economics, Aarhus University.
- Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk-realised semivariance," Economics Papers 2008-W02, Economics Group, Nuffield College, University of Oxford.
- Maria Elvira Mancino & Simona Sanfelici, 2012.
"Estimation of quarticity with high-frequency data,"
Quantitative Finance, Taylor & Francis Journals, vol. 12(4), pages 607-622, December.
- Maria Elvira Mancino & Simona Sanfelici, 2011. "Estimation of Quarticity with High Frequency Data," Working Papers - Mathematical Economics 2011-06, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, revised Jan 2012.
- Clinet, Simon & Potiron, Yoann, 2019.
"Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book,"
Journal of Econometrics, Elsevier, vol. 209(2), pages 289-337.
- Simon Clinet & Yoann Potiron, 2017. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Papers 1709.02502, arXiv.org, revised Feb 2019.
- Li, Yingying & Zhang, Zhiyuan & Zheng, Xinghua, 2013. "Volatility inference in the presence of both endogenous time and microstructure noise," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2696-2727.
- Chaboud, Alain P. & Chiquoine, Benjamin & Hjalmarsson, Erik & Loretan, Mico, 2010.
"Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets,"
Journal of Empirical Finance, Elsevier, vol. 17(2), pages 212-240, March.
- Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2007. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," International Finance Discussion Papers 905, Board of Governors of the Federal Reserve System (U.S.).
- Alain Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2008. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," BIS Working Papers 249, Bank for International Settlements.
- Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018.
"Risk Everywhere: Modeling and Managing Volatility,"
The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
- Pedersen, Lasse Heje & Bollerslev, Tim & Hood, Benjamin & Huss, John, 2018. "Risk Everywhere: Modeling and Managing Volatility," CEPR Discussion Papers 12687, C.E.P.R. Discussion Papers.
- David E. Allen & Michael McAleer & Marcel Scharth, 2014.
"Asymmetric Realized Volatility Risk,"
JRFM, MDPI, vol. 7(2), pages 1-30, June.
- David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Documentos de Trabajo del ICAE 2014-16, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Tinbergen Institute Discussion Papers 14-075/III, Tinbergen Institute.
- David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Working Papers in Economics 14/20, University of Canterbury, Department of Economics and Finance.
- Christensen, Kim & Oomen, Roel C.A. & Podolskij, Mark, 2014.
"Fact or friction: Jumps at ultra high frequency,"
Journal of Financial Economics, Elsevier, vol. 114(3), pages 576-599.
- Kim Christensen & Roel Oomen & Mark Podolskij, 2011. "Fact or friction: Jumps at ultra high frequency," CREATES Research Papers 2011-19, Department of Economics and Business Economics, Aarhus University.
- Harry-Paul Vander Elst, 2015.
"FloGARCH: Realizing Long Memory and Asymmetries in Returns Valitility,"
Working Papers ECARES
ECARES 2015-12, ULB -- Universite Libre de Bruxelles.
- Harry Vander Elst, 2015. "FloGARCH : Realizing long memory and asymmetries in returns volatility," Working Paper Research 280, National Bank of Belgium.
- Corsi, Fulvio & Pirino, Davide & Renò, Roberto, 2010.
"Threshold bipower variation and the impact of jumps on volatility forecasting,"
Journal of Econometrics, Elsevier, vol. 159(2), pages 276-288, December.
- Fulvio Corsi & Davide Pirino & Roberto Reno', 2010. "Threshold Bipower Variation and the Impact of Jumps on Volatility Forecasting," LEM Papers Series 2010/11, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
- Fulvio Corsi & Davide Pirino & Roberto Renò, 2010. "Threshold bipower variation and the impact of jumps on volatility forecasting," Post-Print hal-00741630, HAL.
- Ilze Kalnina, 2023.
"Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 538-549, April.
- KALNINA, Ilze, 2015. "Inference for nonparametric high-frequency estimators with an application to time variation in betas," Cahiers de recherche 2015-08, Universite de Montreal, Departement de sciences economiques.
- Ilze KALNINA, 2015. "Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas," Cahiers de recherche 13-2015, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Winkelmann, Lars & Yao, Wenying, 2020. "Cojump anchoring," Discussion Papers 2020/17, Free University Berlin, School of Business & Economics.
- Tian, Fengping & Yang, Ke & Chen, Langnan, 2017. "Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity," International Journal of Forecasting, Elsevier, vol. 33(1), pages 132-152.
- Fangfang Wang, 2016. "An Unbiased Measure of Integrated Volatility in the Frequency Domain," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(2), pages 147-164, March.
- Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020.
"Liquidity and volatility in the U.S. Treasury market,"
Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
- Robert Engle & Michael J. Fleming & Eric Ghysels & Giang Nguyen, 2012. "Liquidity and volatility in the U.S. treasury market," Staff Reports 590, Federal Reserve Bank of New York.
- Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2015.
"Parametric Inference and Dynamic State Recovery From Option Panels,"
Econometrica, Econometric Society, vol. 83(3), pages 1081-1145, May.
- Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2011. "Parametric Inference and Dynamic State Recovery from Option Panels," CREATES Research Papers 2012-11, Department of Economics and Business Economics, Aarhus University.
- Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2012. "Parametric Inference and Dynamic State Recovery from Option Panels," Global COE Hi-Stat Discussion Paper Series gd12-266, Institute of Economic Research, Hitotsubashi University.
- Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2012. "Parametric Inference and Dynamic State Recovery from Option Panels," NBER Working Papers 18046, National Bureau of Economic Research, Inc.
- Wang, Kent & Liu, Junwei & Liu, Zhi, 2013. "Disentangling the effect of jumps on systematic risk using a new estimator of integrated co-volatility," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1777-1786.
- Härdle, Wolfgang Karl & Chen, Shi & Liang, Chong & Schienle, Melanie, 2018. "Time-varying Limit Order Book Networks," IRTG 1792 Discussion Papers 2018-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Lorenzo Camponovo & Yukitoshi Matsushita & Taisuke Otsu, 2017. "Empirical likelihood for high frequency data," STICERD - Econometrics Paper Series 591, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Markus Bibinger & Per A. Mykland, 2016. "Inference for Multi-dimensional High-frequency Data with an Application to Conditional Independence Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1078-1102, December.
- Mancini, Cecilia, 2013. "Measuring the relevance of the microstructure noise in financial data," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2728-2751.
- Kirill Dragun & Kris Boudt & Orimar Sauri & Steven Vanduffel, 2021. "Beta-Adjusted Covariance Estimation," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1010, Ghent University, Faculty of Economics and Business Administration.
- Bolko, Anine E. & Christensen, Kim & Pakkanen, Mikko S. & Veliyev, Bezirgen, 2023.
"A GMM approach to estimate the roughness of stochastic volatility,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 745-778.
- Anine E. Bolko & Kim Christensen & Mikko S. Pakkanen & Bezirgen Veliyev, 2020. "A GMM approach to estimate the roughness of stochastic volatility," Papers 2010.04610, arXiv.org, revised Apr 2022.
- Neil Shephard & Ole E. Barndorff-Nielsen, 2008.
"Modelling and measuring volatility,"
Economics Series Working Papers
2008--FE-31, University of Oxford, Department of Economics.
- Ole E. Barndorff-Nielsen & Neil Shephard, 2008. "Modelling and measuring volatility," OFRC Working Papers Series 2008fe31, Oxford Financial Research Centre.
- Masato Ubukata & Toshiaki Watanabe, 2014. "Market variance risk premiums in Japan for asset predictability," Empirical Economics, Springer, vol. 47(1), pages 169-198, August.
- Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015.
"Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes,"
Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
- Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
- Boudt, Kris & Laurent, Sébastien & Lunde, Asger & Quaedvlieg, Rogier & Sauri, Orimar, 2017.
"Positive semidefinite integrated covariance estimation, factorizations and asynchronicity,"
Journal of Econometrics, Elsevier, vol. 196(2), pages 347-367.
- Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg, 2014. "Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity," CREATES Research Papers 2014-05, Department of Economics and Business Economics, Aarhus University.
- Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
- Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
- Linton, Oliver & Whang, Yoon-Jae & Yen, Yu-Min, 2016.
"A nonparametric test of a strong leverage hypothesis,"
Journal of Econometrics, Elsevier, vol. 194(1), pages 153-186.
- Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2013. "A nonparametric test of a strong leverage hypothesis," CeMMAP working papers CWP28/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2013. "A nonparametric test of a strong leverage hypothesis," CeMMAP working papers 28/13, Institute for Fiscal Studies.
- Hounyo, Ulrich & Gonçalves, Sílvia & Meddahi, Nour, 2017.
"Bootstrapping Pre-Averaged Realized Volatility Under Market Microstructure Noise,"
Econometric Theory, Cambridge University Press, vol. 33(4), pages 791-838, August.
- Ulrich Hounyo & Sílvia Goncalves & Nour Meddahi, 2013. "Bootstrapping pre-averaged realized volatility under market microstructure noise," CREATES Research Papers 2013-28, Department of Economics and Business Economics, Aarhus University.
- Goncalves, Silvia & Hounyo, Ulrich & Meddahi, Nour, 2017. "Bootstrapping Pre-Averaged Realized Volatility under Market Microstructure Noise," IDEI Working Papers 869, Institut d'Économie Industrielle (IDEI), Toulouse.
- Goncalves, Silvia & Hounyo, Ulrich & Meddahi, Nour, 2017. "Bootstrapping Pre-Averaged Realized Volatility under Market Microstructure Noise," TSE Working Papers 17-809, Toulouse School of Economics (TSE).
- Ulrich Hounyo & Silvia Gonçalves & Nour Meddahi, 2016. "Bootstrapping pre-averaged realized volatility under market microstructure noise," CIRANO Working Papers 2016s-25, CIRANO.
- Bu, R. & Li, D. & Linton, O. & Wang, H., 2022.
"Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data,"
Cambridge Working Papers in Economics
2218, Faculty of Economics, University of Cambridge.
- Ruijun Bu & Degui Li & Oliver Linton & Hanchao Wang, 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Working Papers 202212, University of Liverpool, Department of Economics.
- Ruijun Bu & Degui Li & Oliver Linton & Hanchao Wang, 2023. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Papers 2307.01348, arXiv.org.
- Bu, R. & Li, D. & Linton, O. & Wang, H., 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Janeway Institute Working Papers 2208, Faculty of Economics, University of Cambridge.
- Giorgio Mirone, 2017. "Inference from the futures: ranking the noise cancelling accuracy of realized measures," CREATES Research Papers 2017-24, Department of Economics and Business Economics, Aarhus University.
- Giorgio Mirone, 2018. "Cross-sectional noise reduction and more efficient estimation of Integrated Variance," CREATES Research Papers 2018-18, Department of Economics and Business Economics, Aarhus University.
- Neil Shephard & Kevin Sheppard, 2010.
"Realising the future: forecasting with high-frequency-based volatility (HEAVY) models,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 197-231.
- Neil Shephard & Kevin Sheppard, 2009. "Realising the future: forecasting with high frequency based volatility (HEAVY) models," OFRC Working Papers Series 2009fe02, Oxford Financial Research Centre.
- Neil Shephard & Kevin Sheppard, 2009. "Realising the future: forecasting with high frequency based volatility (HEAVY) models," Economics Series Working Papers 438, University of Oxford, Department of Economics.
- Neil Shephard & Kevin Sheppard, 2009. "Realising the future: forecasting with high frequency based volatility (HEAVY) models," Economics Papers 2009-W03, Economics Group, Nuffield College, University of Oxford.
- Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013.
"Financial Risk Measurement for Financial Risk Management,"
Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220,
Elsevier.
- 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.
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, Department of Economics and Business Economics, Aarhus University.
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2012. "Financial Risk Measurement for Financial Risk Management," NBER Working Papers 18084, National Bureau of Economic Research, Inc.
- Wang, Moming & Xia, Ningning, 2021. "Estimation of high-dimensional integrated covariance matrix based on noisy high-frequency data with multiple observations," Statistics & Probability Letters, Elsevier, vol. 170(C).
- Xinghua Zheng & Yingying Li, 2010. "On the estimation of integrated covariance matrices of high dimensional diffusion processes," Papers 1005.1862, arXiv.org, revised Mar 2012.
- Bibinger, Markus & Winkelmann, Lars, 2015. "Econometrics of co-jumps in high-frequency data with noise," Journal of Econometrics, Elsevier, vol. 184(2), pages 361-378.
- Qi Wang & Jos'e E. Figueroa-L'opez & Todd Kuffner, 2019. "Bayesian Inference on Volatility in the Presence of Infinite Jump Activity and Microstructure Noise," Papers 1909.04853, arXiv.org.
- Elena Ivona Dumitrescu & Georgiana-Denisa Banulescu, 2019.
"Do High-frequency-based Measures Improve Conditional Covariance Forecasts?,"
Post-Print
hal-03331122, HAL.
- Denisa BANULESCU-RADU & Elena Ivona DUMITRESCU, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," LEO Working Papers / DR LEO 2709, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
- Lars Winkelmann & Wenying Yao, 2024.
"Tests for Jumps in Yield Spreads,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 946-957, July.
- Winkelmann, Lars & Yao, Wenying, 2021. "Tests for jumps in yield spreads," Discussion Papers 2021/15, Free University Berlin, School of Business & Economics.
- Lars Winkelmann & Wenying Yao, 2023. "Tests for Jumps in Yield Spreads," Berlin School of Economics Discussion Papers 0024, Berlin School of Economics.
- Nikolaus Hautsch & Mark Podolskij, 2013.
"Preaveraging-Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 165-183, April.
- Hautsch, Nikolaus & Podolskij, Mark, 2010. "Pre-averaging based estimation of quadratic variation in the presence of noise and jumps: Theory, implementation, and empirical evidence," SFB 649 Discussion Papers 2010-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Nikolaus Hautsch & Mark Podolskij, 2010. "Pre-Averaging Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence," CREATES Research Papers 2010-29, Department of Economics and Business Economics, Aarhus University.
- Hautsch, Nikolaus & Podolskij, Mark, 2010. "Pre-averaging based estimation of quadratic variation in the presence of noise and jumps: Theory, implementation, and empirical evidence," CFS Working Paper Series 2010/17, Center for Financial Studies (CFS).
- Chao YU & Xujie ZHAO, 2021. "Measuring the Jump Risk Contribution under Market Microstructure Noise – Evidence from Chinese Stock Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 32-47, December.
- Habib Hasnaoui, 2014. "Alternative Beta Risk Estimators in Emerging Markets: The Case of Tunisia," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 2(2), pages 96-105.
- Liu, Cheng & Tang, Cheng Yong, 2014. "A quasi-maximum likelihood approach for integrated covariance matrix estimation with high frequency data," Journal of Econometrics, Elsevier, vol. 180(2), pages 217-232.
- Ubukata, Masato & Watanabe, Toshiaki, 2015. "Evaluating the performance of futures hedging using multivariate realized volatility," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 148-171.
- Cecilia Mancini, 2012. "Measuring the relevance of the microstructure noise in financial data," Working Papers - Mathematical Economics 2012-09, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
- Chen, Shi & Härdle, Wolfgang & Schienle, Melanie, 2021. "High-dimensional statistical learning techniques for time-varying limit order book networks," IRTG 1792 Discussion Papers 2021-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2016. "Decoupling the short- and long-term behavior of stochastic volatility," Papers 1610.00332, arXiv.org, revised Jan 2021.
- Xin Jin & Jia Liu & Qiao Yang, 2021. "Does the Choice of Realized Covariance Measures Empirically Matter? A Bayesian Density Prediction Approach," Econometrics, MDPI, vol. 9(4), pages 1-22, December.
- Wu, Fan & Wang, Guan-jun & Kong, Xin-bing, 2022. "Inference on common intraday periodicity at high frequencies," Statistics & Probability Letters, Elsevier, vol. 191(C).
- Liu, Cheng & Wang, Moming & Xia, Ningning, 2022. "Design-free estimation of integrated covariance matrices for high-frequency data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
- Barndorff-Nielsen, Ole E. & Hansen, Peter Reinhard & Lunde, Asger & Shephard, Neil, 2011.
"Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading,"
Journal of Econometrics, Elsevier, vol. 162(2), pages 149-169, June.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Economics Papers 2008-W10, Economics Group, Nuffield College, University of Oxford.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2009. "Multivariate Realised Kernels: Consistent Positive Semi-Definite Estimators of the Covariation of Equity Prices with Noise and Non-Synchronous Trading," Global COE Hi-Stat Discussion Paper Series gd08-037, Institute of Economic Research, Hitotsubashi University.
- Neil Shephard & Ole E. Barndorff-Nielsen & Peter Reinhard Hansen, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Economics Series Working Papers 397, University of Oxford, Department of Economics.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2011. "Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Post-Print hal-00815564, HAL.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," OFRC Working Papers Series 2008fe29, Oxford Financial Research Centre.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," CREATES Research Papers 2008-63, Department of Economics and Business Economics, Aarhus University.
- Wang, Chengyang & Nishiyama, Yoshihiko, 2015. "Volatility forecast of stock indices by model averaging using high-frequency data," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 324-337.
- Harry-Paul Vander Elst & David Veredas, 2014.
"Disentangled Jump-Robust Realized Covariances and Correlations with Non-Synchronous Prices,"
Working Papers ECARES
ECARES 2014-35, ULB -- Universite Libre de Bruxelles.
- Vander Elst, Harry & Veredas, David, 2014. "Disentangled jump-robust realized covariances and correlations with non-synchronous prices," DES - Working Papers. Statistics and Econometrics. WS ws142416, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- 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.
- Rasmus Tangsgaard Varneskov & Valeri Voev, 2010. "The Role of Realized Ex-post Covariance Measures and Dynamic Model Choice on the Quality of Covariance Forecasts," CREATES Research Papers 2010-45, Department of Economics and Business Economics, Aarhus University.
- Xin-Bing Kong, 2013. "A direct approach to risk approximation for vast portfolios under gross-exposure constraint using high-frequency data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(4), pages 647-669, November.
- Chen, Dachuan, 2024. "High frequency principal component analysis based on correlation matrix that is robust to jumps, microstructure noise and asynchronous observation times," Journal of Econometrics, Elsevier, vol. 240(1).
- Huiling Yuan & Yong Zhou & Zhiyuan Zhang & Xiangyu Cui, 2019. "Forecasting security's volatility using low-frequency historical data, high-frequency historical data and option-implied volatility," Papers 1907.02666, arXiv.org.
- Shen, Keren & Yao, Jianfeng & Li, Wai Keung, 2019. "On a spiked model for large volatility matrix estimation from noisy high-frequency data," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 207-221.
- Novotný, Jan & Petrov, Dmitri & Urga, Giovanni, 2015. "Trading price jump clusters in foreign exchange markets," Journal of Financial Markets, Elsevier, vol. 24(C), pages 66-92.
- Ma, Chaoqun & Mi, Xianhua & Cai, Zongwu, 2020. "Nonlinear and time-varying risk premia," China Economic Review, Elsevier, vol. 62(C).
- Christensen, Bent Jesper & Kjær, Mads Markvart & Veliyev, Bezirgen, 2023.
"The incremental information in the yield curve about future interest rate risk,"
Journal of Banking & Finance, Elsevier, vol. 155(C).
- Bent Jesper Christensen & Mads Markvart Kjær & Bezirgen Veliyev, 2021. "The incremental information in the yield curve about future interest rate risk," CREATES Research Papers 2021-11, Department of Economics and Business Economics, Aarhus University.
- Mykland, Per A. & Zhang, Lan & Chen, Dachuan, 2019. "The algebra of two scales estimation, and the S-TSRV: High frequency estimation that is robust to sampling times," Journal of Econometrics, Elsevier, vol. 208(1), pages 101-119.
- Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
- Huiling Yuan & Guodong Li & Junhui Wang, 2022. "High-Frequency-Based Volatility Model with Network Structure," Papers 2204.12933, arXiv.org.
- Carol Alexander & Daniel F. Heck & Andreas Kaeck, 2022.
"The Role of Binance in Bitcoin Volatility Transmission,"
Applied Mathematical Finance, Taylor & Francis Journals, vol. 29(1), pages 1-32, January.
- Carol Alexander & Daniel Heck & Andreas Kaeck, 2021. "The Role of Binance in Bitcoin Volatility Transmission," Papers 2107.00298, arXiv.org, revised Aug 2021.
- Siem Jan Koopman & Marcel Scharth, 2012.
"The Analysis of Stochastic Volatility in the Presence of Daily Realized Measures,"
Journal of Financial Econometrics, Oxford University Press, vol. 11(1), pages 76-115, December.
- Siem Jan Koopman & Marcel Scharth, 2011. "The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures," Tinbergen Institute Discussion Papers 11-132/4, Tinbergen Institute.
- Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2020. "Economic indicators and stock market volatility in an emerging economy," Economic Systems, Elsevier, vol. 44(2).
- Clinet, Simon & Potiron, Yoann, 2018.
"Efficient asymptotic variance reduction when estimating volatility in high frequency data,"
Journal of Econometrics, Elsevier, vol. 206(1), pages 103-142.
- Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.
- Lee, Suzanne S. & Mykland, Per A., 2012. "Jumps in equilibrium prices and market microstructure noise," Journal of Econometrics, Elsevier, vol. 168(2), pages 396-406.
- Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018.
"Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting,"
MPRA Paper
94289, University Library of Munich, Germany.
- Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018. "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper 83893, University Library of Munich, Germany.
- Marine Carrasco & Rachidi Kotchoni, 2015.
"Adaptive Realized Kernels,"
Journal of Financial Econometrics, Oxford University Press, vol. 13(4), pages 757-797.
- Marine Carrasco & Rachidi Kotchoni, 2011. "Adaptive Realized Kernels," CIRANO Working Papers 2011s-29, CIRANO.
- Marine Carrasco & Rachidi Kotchoni, 2014. "Adaptive Realized Kernels," Post-Print hal-01386059, HAL.
- Marine Carrasco & Rachidi Kotchoni, 2013. "Adaptive Realized Kernels," Working Papers hal-00867967, HAL.
- Li, Shaoyu & Zheng, Tingguo, 2017. "Modeling spot rate using a realized stochastic volatility model with level effect and dynamic drift☆," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 200-221.
- Dohyun Chun & Donggyu Kim, 2022.
"State Heterogeneity Analysis of Financial Volatility using high‐frequency Financial Data,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 105-124, January.
- Dohyun Chun & Donggyu Kim, 2021. "State Heterogeneity Analysis of Financial Volatility Using High-Frequency Financial Data," Papers 2102.13404, arXiv.org.
- Griffin, Jim E. & Oomen, Roel C.A., 2011. "Covariance measurement in the presence of non-synchronous trading and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 58-68, January.
- Yao Axel Ehouman, 2020. "Volatility transmission between oil prices and banks’ stock prices as a new source of instability: Lessons from the United States experience," Post-Print hal-02960571, HAL.
- Simon Clinet & Yoann Potiron, 2021.
"Estimation for high-frequency data under parametric market microstructure noise,"
Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 649-669, August.
- Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.
- Aït-Sahalia, Yacine & Xiu, Dacheng, 2016. "Increased correlation among asset classes: Are volatility or jumps to blame, or both?," Journal of Econometrics, Elsevier, vol. 194(2), pages 205-219.
- Zu, Yang & Peter Boswijk, H., 2014. "Estimating spot volatility with high-frequency financial data," Journal of Econometrics, Elsevier, vol. 181(2), pages 117-135.
- Yacine Aït-Sahalia & Jianqing Fan & Roger J. A. Laeven & Christina Dan Wang & Xiye Yang, 2017. "Estimation of the Continuous and Discontinuous Leverage Effects," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1744-1758, October.
- Sílvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2014.
"Bootstrap Inference for Pre-averaged Realized Volatility based on Nonoverlapping Returns,"
Journal of Financial Econometrics, Oxford University Press, vol. 12(4), pages 679-707.
- Sílvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2013. "Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns," CREATES Research Papers 2013-07, Department of Economics and Business Economics, Aarhus University.
- Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
- Park, Sujin & Hong, Seok Young & Linton, Oliver, 2016. "Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error," Journal of Econometrics, Elsevier, vol. 191(2), pages 325-347.
- Bing-Yi Jing & Zhi Liu & Xin-Bing Kong, 2014. "On the Estimation of Integrated Volatility With Jumps and Microstructure Noise," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 457-467, July.
- Vladimír Holý & Petra Tomanová, 2023. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 463-485, June.
- Li, M. Z. & Linton, O., 2021. "Robust Estimation of Integrated and Spot Volatility," Cambridge Working Papers in Economics 2115, Faculty of Economics, University of Cambridge.
- Flavia Barsotti & Simona Sanfelici, 2012. "Microstructure effect on firm’s volatility risk," Working Papers - Mathematical Economics 2012-05, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
- Fulvio Corsi & Roberto Renò, 2012. "Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 368-380, January.
- Zhang, Lan, 2011. "Estimating covariation: Epps effect, microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 33-47, January.
- Christensen, Kim & Kinnebrock, Silja & Podolskij, Mark, 2010.
"Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data,"
Journal of Econometrics, Elsevier, vol. 159(1), pages 116-133, November.
- Kim Christensen & Silja Kinnebrock & Mark Podolskij, 2009. "Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data," CREATES Research Papers 2009-45, Department of Economics and Business Economics, Aarhus University.
- Kim Christensen & Silja Kinnebrock & Mark Podolskij, 2010. "Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data," Post-Print hal-00732537, HAL.
- repec:wyi:journl:002184 is not listed on IDEAS
- Shephard, Neil & Xiu, Dacheng, 2017. "Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading," Journal of Econometrics, Elsevier, vol. 201(1), pages 19-42.
- Markus Bibinger & Markus Reiß, 2014. "Spectral Estimation of Covolatility from Noisy Observations Using Local Weights," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 23-50, March.
- Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023.
"The contribution of jump signs and activity to forecasting stock price volatility,"
Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
- , 2019. "The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility," Working Papers 1902, Federal Reserve Bank of Dallas, revised 17 Dec 2022.
- Ruijun Bu & Rodrigo Hizmeri & Marwan Izzeldin & Anthony Murphy & Mike G. Tsionas, 2021. "The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility," Working Papers 202109, University of Liverpool, Department of Economics.
- Kevin Sheppard & Wen Xu, 2019. "Factor High-Frequency-Based Volatility (HEAVY) Models," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 33-65.
- Schmisser Emeline, 2011. "Non-parametric drift estimation for diffusions from noisy data," Statistics & Risk Modeling, De Gruyter, vol. 28(2), pages 119-150, May.
- Chaker, Selma, 2017. "On high frequency estimation of the frictionless price: The use of observed liquidity variables," Journal of Econometrics, Elsevier, vol. 201(1), pages 127-143.
- Xin Zhang & Donggyu Kim & Yazhen Wang, 2016. "Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets," Econometrics, MDPI, vol. 4(3), pages 1-26, August.
- Christensen, K. & Podolskij, M. & Thamrongrat, N. & Veliyev, B., 2017.
"Inference from high-frequency data: A subsampling approach,"
Journal of Econometrics, Elsevier, vol. 197(2), pages 245-272.
- Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
- Bollerslev, Tim & Meddahi, Nour & Nyawa, Serge, 2019. "High-dimensional multivariate realized volatility estimation," Journal of Econometrics, Elsevier, vol. 212(1), pages 116-136.
- Chang, Jinyuan & Hu, Qiao & Liu, Cheng & Tang, Cheng Yong, 2024. "Optimal covariance matrix estimation for high-dimensional noise in high-frequency data," Journal of Econometrics, Elsevier, vol. 239(2).
- Liao, Yin & Anderson, Heather M., 2019.
"Testing for cojumps in high-frequency financial data: An approach based on first-high-low-last prices,"
Journal of Banking & Finance, Elsevier, vol. 99(C), pages 252-274.
- Yin Liao & Heather M. Anderson, 2011. "Testing for co-jumps in high-frequency financial data: an approach based on first-high-low-last prices," Monash Econometrics and Business Statistics Working Papers 9/11, Monash University, Department of Econometrics and Business Statistics.
- Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
- Liu, Zhi & Kong, Xin-Bing & Jing, Bing-Yi, 2018. "Estimating the integrated volatility using high-frequency data with zero durations," Journal of Econometrics, Elsevier, vol. 204(1), pages 18-32.
- Per A. Mykland & Neil Shephard & Kevin Sheppard, 2012.
"Efficient and feasible inference for the components of financial variation using blocked multipower variation,"
Economics Papers
2012-W02, Economics Group, Nuffield College, University of Oxford.
- Neil Shephard & Kevin Sheppard, 2012. "Efficient and feasible inference for the components of financial variation using blocked multipower variation," Economics Series Working Papers 593, University of Oxford, Department of Economics.
- Cheng, Mingmian & Swanson, Norman R. & Yang, Xiye, 2021. "Forecasting volatility using double shrinkage methods," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 46-61.
- Andersen, Torben G. & Li, Yingying & Todorov, Viktor & Zhou, Bo, 2023. "Volatility measurement with pockets of extreme return persistence," Journal of Econometrics, Elsevier, vol. 237(2).
- Christensen, Kim & Thyrsgaard, Martin & Veliyev, Bezirgen, 2019.
"The realized empirical distribution function of stochastic variance with application to goodness-of-fit testing,"
Journal of Econometrics, Elsevier, vol. 212(2), pages 556-583.
- Kim Christensen & Martin Thyrsgaard & Bezirgen Veliyev, 2018. "The realized empirical distribution function of stochastic variance with application to goodness-of-fit testing," CREATES Research Papers 2018-19, Department of Economics and Business Economics, Aarhus University.
- Shota Gugushvili & Frank van der Meulen & Moritz Schauer & Peter Spreij, 2018. "Nonparametric Bayesian volatility learning under microstructure noise," Papers 1805.05606, arXiv.org, revised Mar 2024.
- Hwang, Eunju & Shin, Dong Wan, 2018. "Two-stage stationary bootstrapping for bivariate average realized volatility matrix under market microstructure noise and asynchronicity," Journal of Econometrics, Elsevier, vol. 202(2), pages 178-195.
- Kim, Donggyu & Wang, Yazhen, 2016. "Unified discrete-time and continuous-time models and statistical inferences for merged low-frequency and high-frequency financial data," Journal of Econometrics, Elsevier, vol. 194(2), pages 220-230.
- Tobias Fissler & Mark Podolskij, 2014. "Testing the maximal rank of the volatility process for continuous diffusions observed with noise," CREATES Research Papers 2014-52, Department of Economics and Business Economics, Aarhus University.
- Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2016. "Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach," CREATES Research Papers 2016-27, Department of Economics and Business Economics, Aarhus University.
- Qiang Liu & Zhi Liu & Chuanhai Zhang, 2020. "Heteroscedasticity test of high-frequency data with jumps and microstructure noise," Papers 2010.07659, arXiv.org.
- Selma Chaker & Nour Meddahi, 2013. "Volatility Forecasting when the Noise Variance Is Time-Varying," Staff Working Papers 13-48, Bank of Canada.
- Zhihong Jian & Zhican Zhu & Jie Zhou & Shuai Wu, 2018. "The Magnet Effect of Circuit Breakers: A role of price jumps and market liquidity," Departmental Working Papers 2018-01, The University of Winnipeg, Department of Economics.
- Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
- Donggyu Kim & Minseok Shin & Yazhen Wang, 2023.
"Overnight GARCH-Itô Volatility Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1215-1227, October.
- Donggyu Kim & Minseok Shin & Yazhen Wang, 2021. "Overnight GARCH-It\^o Volatility Models," Papers 2102.13467, arXiv.org, revised Jun 2022.
- Chen, Dachuan & Mykland, Per A. & Zhang, Lan, 2024. "Realized regression with asynchronous and noisy high frequency and high dimensional data," Journal of Econometrics, Elsevier, vol. 239(2).
- Naoto Kunitomo & Hiroumi Misaki & Seisho Sato, 2015. "The SIML Estimation of Integrated Covariance and Hedging Coefficient Under Round-off Errors, Micro-market Price Adjustments and Random Sampling," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 22(3), pages 333-368, September.
- Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
- Yu, Chao & Fang, Yue & Zhao, Xujie & Zhang, Bo, 2013. "Kernel filtering of spot volatility in presence of Lévy jumps and market microstructure noise," MPRA Paper 63293, University Library of Munich, Germany, revised 10 Mar 2014.
- Jacod, Jean & Li, Yingying & Zheng, Xinghua, 2019. "Estimating the integrated volatility with tick observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 80-100.
- Kim, Donggyu & Kong, Xin-Bing & Li, Cui-Xia & Wang, Yazhen, 2018. "Adaptive thresholding for large volatility matrix estimation based on high-frequency financial data," Journal of Econometrics, Elsevier, vol. 203(1), pages 69-79.
- Emeline Schmisser, 2012. "Non-parametric estimation of the diffusion coefficient from noisy data," Statistical Inference for Stochastic Processes, Springer, vol. 15(3), pages 193-223, October.
- Hounyo, Ulrich, 2017. "Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading," Journal of Econometrics, Elsevier, vol. 197(1), pages 130-152.
- Shin, Minseok & Kim, Donggyu & Fan, Jianqing, 2023. "Adaptive robust large volatility matrix estimation based on high-frequency financial data," Journal of Econometrics, Elsevier, vol. 237(1).
- Selma Chaker & Nour Meddahi, 2013. "A Distributional Approach to Realized Volatility," Staff Working Papers 13-49, Bank of Canada.
- E. Bacry & S. Delattre & M. Hoffmann & J. F. Muzy, 2013.
"Modelling microstructure noise with mutually exciting point processes,"
Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 65-77, January.
- E. Bacry & S. Delattre & M. Hoffmann & J. F. Muzy, 2011. "Modeling microstructure noise with mutually exciting point processes," Papers 1101.3422, arXiv.org.
- Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
- Anne Brix & Asger Lunde, 2015. "Prediction-based estimating functions for stochastic volatility models with noisy data: comparison with a GMM alternative," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(4), pages 433-465, October.
- Fu, Jin-Yu & Lin, Jin-Guan & Hao, Hong-Xia, 2023. "Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1698-1712.
- Clément, Emmanuelle & Gloter, Arnaud, 2011. "Limit theorems in the Fourier transform method for the estimation of multivariate volatility," Stochastic Processes and their Applications, Elsevier, vol. 121(5), pages 1097-1124, May.
- Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016.
"Exploiting the errors: A simple approach for improved volatility forecasting,"
Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
- Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2015. "Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting," CREATES Research Papers 2015-14, Department of Economics and Business Economics, Aarhus University.
- Jean Jacod, 2019. "Estimation of volatility in a high-frequency setting: a short review," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 351-385, December.
- Jorge M. Uribe, 2018. "“Scaling Down Downside Risk with Inter-Quantile Semivariances”," IREA Working Papers 201826, University of Barcelona, Research Institute of Applied Economics, revised Oct 2018.
- Podolskij, Mark & Veliyev, Bezirgen & Yoshida, Nakahiro, 2017.
"Edgeworth expansion for the pre-averaging estimator,"
Stochastic Processes and their Applications, Elsevier, vol. 127(11), pages 3558-3595.
- Mark Podolskij & Bezirgen Veliyev & Nakahiro Yoshida, 2015. "Edgeworth expansion for the pre-averaging estimator," Papers 1512.04716, arXiv.org.
- Mark Podolskij & Bezirgen Veliyev & Nakahiro Yoshida, 2015. "Edgeworth expansion for the pre-averaging estimator," CREATES Research Papers 2015-60, Department of Economics and Business Economics, Aarhus University.
- Zhang, Lan & Mykland, Per A. & Aït-Sahalia, Yacine, 2011.
"Edgeworth expansions for realized volatility and related estimators,"
Journal of Econometrics, Elsevier, vol. 160(1), pages 190-203, January.
- Lan Zhang & Per A. Mykland & Yacine Ait-Sahalia, 2005. "Edgeworth Expansions for Realized Volatility and Related Estimators," NBER Technical Working Papers 0319, National Bureau of Economic Research, Inc.
- Wang Pu & Yixiang Chen & Feng Ma, 2016. "Forecasting the realized volatility in the Chinese stock market: further evidence," Applied Economics, Taylor & Francis Journals, vol. 48(33), pages 3116-3130, July.
- repec:cte:wsrepe:es142416 is not listed on IDEAS
- Markus Reiss, 2010. "Asymptotic equivalence and sufficiency for volatility estimation under microstructure noise," Papers 1001.3006, arXiv.org.
- Li, Yingying & Liu, Guangying & Zhang, Zhiyuan, 2022. "Volatility of volatility: Estimation and tests based on noisy high frequency data with jumps," Journal of Econometrics, Elsevier, vol. 229(2), pages 422-451.
- Jian, Zhihong & Zhu, Zhican & Zhou, Jie & Wu, Shuai, 2020. "Intraday price jumps, market liquidity, and the magnet effect of circuit breakers," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 168-186.
- Julius Bonart & Fabrizio Lillo, 2016. "A continuous and efficient fundamental price on the discrete order book grid," Papers 1608.00756, arXiv.org, revised Aug 2016.
- Yusuke Kaino & Shogo H. Nakakita & Masayuki Uchida, 2020. "Hybrid estimation for ergodic diffusion processes based on noisy discrete observations," Statistical Inference for Stochastic Processes, Springer, vol. 23(1), pages 171-198, April.
- Bandi, F.M. & Renò, R., 2016. "Price and volatility co-jumps," Journal of Financial Economics, Elsevier, vol. 119(1), pages 107-146.
- Li, Z. Merrick & Laeven, Roger J.A. & Vellekoop, Michel H., 2020.
"Dependent microstructure noise and integrated volatility estimation from high-frequency data,"
Journal of Econometrics, Elsevier, vol. 215(2), pages 536-558.
- Li, Z. M. & Laeven, R. J. A. & Vellekoop, M. H., 2019. "Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data," Cambridge Working Papers in Economics 1952, Faculty of Economics, University of Cambridge.
- Neil Shephard & Silja Kinnebrock & Ole E. Barndorff-Neilsen, 2008. "Measuring downside risk - realised semivariance," Economics Series Working Papers 382, University of Oxford, Department of Economics.
- Adamantios Ntakaris & Giorgio Mirone & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Feature Engineering for Mid-Price Prediction with Deep Learning," Papers 1904.05384, arXiv.org, revised Jun 2019.
- Figueroa-López, José E. & Nisen, Jeffrey, 2013. "Optimally thresholded realized power variations for Lévy jump diffusion models," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2648-2677.
- Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
- Aït-Sahalia, Yacine & Fan, Jianqing & Li, Yingying, 2013.
"The leverage effect puzzle: Disentangling sources of bias at high frequency,"
Journal of Financial Economics, Elsevier, vol. 109(1), pages 224-249.
- Yacine Ait-Sahalia & Jianqing Fan & Yingying Li, 2011. "The Leverage Effect Puzzle: Disentangling Sources of Bias at High Frequency," NBER Working Papers 17592, National Bureau of Economic Research, Inc.
- Shogo H. Nakakita & Yusuke Kaino & Masayuki Uchida, 2021. "Quasi-likelihood analysis and Bayes-type estimators of an ergodic diffusion plus noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(1), pages 177-225, February.
- Lyócsa, Štefan & Plíhal, Tomáš & Výrost, Tomáš, 2021. "FX market volatility modelling: Can we use low-frequency data?," Finance Research Letters, Elsevier, vol. 40(C).
- Bonart, Julius & Lillo, Fabrizio, 2018. "A continuous and efficient fundamental price on the discrete order book grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 698-713.
- Fan, Jianqing & Kim, Donggyu, 2019. "Structured volatility matrix estimation for non-synchronized high-frequency financial data," Journal of Econometrics, Elsevier, vol. 209(1), pages 61-78.
- N.H. Bingham & John M. Fry & Rüdiger Kiesel, 2010. "Multivariate elliptic processes," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(s1), pages 352-366.
- Jacod, Jean & Mykland, Per A., 2015. "Microstructure noise in the continuous case: Approximate efficiency of the adaptive pre-averaging method," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2910-2936.
- Yao Axel Ehouman, 2019. "Volatility transmission between oil prices and banks stock prices as a new source of instability: Lessons from the US Experience," EconomiX Working Papers 2019-19, University of Paris Nanterre, EconomiX.
- Yinfen Tang & Tao Su & Zhiyuan Zhang, 2022. "Distribution-free specification test for volatility function based on high-frequency data with microstructure noise," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(8), pages 977-1022, November.
- Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.
- Tingguo Zheng & Tao Song, 2014. "A Realized Stochastic Volatility Model With Box-Cox Transformation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 593-605, October.
- Masato Ubukata & Toshiaki Watanabe, 2013. "Pricing Nikkei 225 Options Using Realized Volatility," Global COE Hi-Stat Discussion Paper Series gd12-273, Institute of Economic Research, Hitotsubashi University.
- Wenjing Wang & Minjing Tao, 2020. "Forecasting Realized Volatility Matrix With Copula-Based Models," Papers 2002.08849, arXiv.org.
- Svetlana Borovkova & Diego Mahakena, 2015. "News, volatility and jumps: the case of natural gas futures," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1217-1242, July.
- Ehouman, Yao Axel, 2020. "Volatility transmission between oil prices and banks' stock prices as a new source of instability: Lessons from the United States experience," Economic Modelling, Elsevier, vol. 91(C), pages 198-217.
- Zhang, Congshan & Li, Jia & Bollerslev, Tim, 2022. "Occupation density estimation for noisy high-frequency data," Journal of Econometrics, Elsevier, vol. 227(1), pages 189-211.
- Pelger, Markus, 2019. "Large-dimensional factor modeling based on high-frequency observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 23-42.
- Asger Lunde & Anne Floor Brix, 2013. "Estimating Stochastic Volatility Models using Prediction-based Estimating Functions," CREATES Research Papers 2013-23, Department of Economics and Business Economics, Aarhus University.
- Yuan, Huiling & Zhou, Yong & Xu, Lu & Sun, Yulei & Cui, Xiangyu, 2020. "A New Volatility Model: GQARCH-Ito Model," SocArXiv hkzdr, Center for Open Science.
- Charles S. Bos & Pawel Janus, 2013. "A Quantile-based Realized Measure of Variation: New Tests for Outlying Observations in Financial Data," Tinbergen Institute Discussion Papers 13-155/III, Tinbergen Institute.
- Xiao, Xijuan & Yamamoto, Ryuichi, 2024. "Realized volatility, price informativeness, and tick size: A market microstructure approach," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 410-426.
- Kim Christensen & Roel Oomen & Roberto Renò, 2018. "The drift burst hypothesis," CREATES Research Papers 2018-21, Department of Economics and Business Economics, Aarhus University.
- Charles S. Bos & Paweł Janus & Siem Jan Koopman, 2012.
"Spot Variance Path Estimation and Its Application to High-Frequency Jump Testing,"
Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 354-389, 2012 06.
- Charles S. Bos & Pawel Janus & Siem Jan Koopman, 2009. "Spot Variance Path Estimation and its Application to High Frequency Jump Testing," Tinbergen Institute Discussion Papers 09-110/4, Tinbergen Institute.
- Kim, Jihyun & Meddahi, Nour, 2020. "Volatility Regressions with Fat Tails," TSE Working Papers 20-1097, Toulouse School of Economics (TSE).
- Zhi Liu, 2022. "Testing for the Presence of the Leverage Effect without Estimation," Mathematics, MDPI, vol. 10(14), pages 1-16, July.
- Donggyu Kim, 2016. "Statistical Inference for Unified Garch–Itô Models with High-Frequency Financial Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 513-532, July.
- Xiu, Dacheng, 2010. "Quasi-maximum likelihood estimation of volatility with high frequency data," Journal of Econometrics, Elsevier, vol. 159(1), pages 235-250, November.
- Aït-Sahalia, Yacine & Jacod, Jean & Li, Jia, 2012. "Testing for jumps in noisy high frequency data," Journal of Econometrics, Elsevier, vol. 168(2), pages 207-222.
- Li, Y-N. & Chen, J. & Linton, O., 2021. "Estimation of Common Factors for Microstructure Noise and Efficient Price in a High-frequency Dual Factor Model," Cambridge Working Papers in Economics 2150, Faculty of Economics, University of Cambridge.
- Wooyong Lee & Priscilla E. Greenwood & Nancy Heckman & Wolfgang Wefelmeyer, 2017. "Pre-averaged kernel estimators for the drift function of a diffusion process in the presence of microstructure noise," Statistical Inference for Stochastic Processes, Springer, vol. 20(2), pages 237-252, July.
- Ulrich Hounyo & Bezirgen Veliyev, 2016.
"Validity of Edgeworth expansions for realized volatility estimators,"
Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
- Ulrich Hounyo & Bezirgen Veliyev, 2015. "Validity of Edgeworth expansions for realized volatility estimators," CREATES Research Papers 2015-21, Department of Economics and Business Economics, Aarhus University.
- O. E. Barndorff-Nielsen & P. Reinhard Hansen & A. Lunde & N. Shephard, 2009. "Realized kernels in practice: trades and quotes," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 1-32, November.
- Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
- Ogihara, Teppei, 2021. "Misspecified diffusion models with high-frequency observations and an application to neural networks," Stochastic Processes and their Applications, Elsevier, vol. 142(C), pages 245-292.
- Vetter, Mathias, 2014. "Inference on the Lévy measure in case of noisy observations," Statistics & Probability Letters, Elsevier, vol. 87(C), pages 125-133.
- Xinyu Song, 2019. "Large Volatility Matrix Prediction with High-Frequency Data," Papers 1907.01196, arXiv.org, revised Sep 2019.
- Yuta Koike & Zhi Liu, 2019. "Asymptotic properties of the realized skewness and related statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 703-741, August.
- Reiß, Markus & Todorov, Viktor & Tauchen, George, 2015. "Nonparametric test for a constant beta between Itô semi-martingales based on high-frequency data," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2955-2988.
- Zhi Liu, 2017. "Jump-robust estimation of volatility with simultaneous presence of microstructure noise and multiple observations," Finance and Stochastics, Springer, vol. 21(2), pages 427-469, April.
- Ikeda, Shin S., 2016. "A bias-corrected estimator of the covariation matrix of multiple security prices when both microstructure effects and sampling durations are persistent and endogenous," Journal of Econometrics, Elsevier, vol. 193(1), pages 203-214.
- Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
- Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
- Rosenbaum, Mathieu & Tankov, Peter, 2011. "Asymptotic results for time-changed Lévy processes sampled at hitting times," Stochastic Processes and their Applications, Elsevier, vol. 121(7), pages 1607-1632, July.
- Zhang, Chuanhai & Liu, Zhi & Liu, Qiang, 2021. "Jumps at ultra-high frequency: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
- Xin-Bing Kong, 2017. "On the number of common factors with high-frequency data," Biometrika, Biometrika Trust, vol. 104(2), pages 397-410.
- Todorov, Viktor, 2009. "Estimation of continuous-time stochastic volatility models with jumps using high-frequency data," Journal of Econometrics, Elsevier, vol. 148(2), pages 131-148, February.
- The Editors, 2018. "Reviews of Books and Teaching Materials," The American Statistician, Taylor & Francis Journals, vol. 72(2), pages 206-212, April.
- Jihyun Kim & Nour Meddahi, 2020. "Volatility Regressions with Fat Tails," Post-Print hal-03142647, HAL.
- Cui, Wenhao & Hu, Jie & Wang, Jiandong, 2024. "Nonparametric estimation for high-frequency data incorporating trading information," Journal of Econometrics, Elsevier, vol. 240(1).
- Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
- Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong, 2015. "Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects," International Journal of Forecasting, Elsevier, vol. 31(3), pages 609-619.
- Flavia Barsotti & Simona Sanfelici, 2016. "Market Microstructure Effects on Firm Default Risk Evaluation," Econometrics, MDPI, vol. 4(3), pages 1-31, July.
- Soumik Pal & Ting-Kam Leonard Wong, 2014. "The geometry of relative arbitrage," Papers 1402.3720, arXiv.org, revised Jul 2015.
- Kim, Seonjin & Zhao, Zhibiao, 2014. "Specification test for Markov models with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 118-133.
- Kim, Donggyu & Wang, Yazhen & Zou, Jian, 2016. "Asymptotic theory for large volatility matrix estimation based on high-frequency financial data," Stochastic Processes and their Applications, Elsevier, vol. 126(11), pages 3527-3577.
- Kim, Donggyu & Wang, Yazhen, 2016. "Sparse PCA-based on high-dimensional Itô processes with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 172-189.
- Yiqi Liu & Qiang Liu & Zhi Liu & Deng Ding, 2017. "Determining the integrated volatility via limit order books with multiple records," Quantitative Finance, Taylor & Francis Journals, vol. 17(11), pages 1697-1714, November.
- Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
- Tao, Minjing & Wang, Yahzen & Yao, Qiwei & Zou, Jian, 2011. "Large volatility matrix inference via combining low-frequency and high-frequency approaches," LSE Research Online Documents on Economics 39321, London School of Economics and Political Science, LSE Library.
- Shen, Yiwen & Shi, Meiqi, 2024. "Intraday variation in cross-sectional stock comovement and impact of index-based strategies," Journal of Financial Markets, Elsevier, vol. 68(C).
- Mykland, Per A. & Zhang, Lan, 2016. "Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price," Journal of Econometrics, Elsevier, vol. 194(2), pages 242-262.
- Bibinger, Markus, 2012. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," Stochastic Processes and their Applications, Elsevier, vol. 122(6), pages 2411-2453.
- Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2019. "Empirical likelihood for high frequency data," LSE Research Online Documents on Economics 100320, London School of Economics and Political Science, LSE Library.
- repec:hal:journl:peer-00741630 is not listed on IDEAS
- Donggyu Kim, 2021. "Exponential GARCH-Ito Volatility Models," Papers 2111.04267, arXiv.org.
- Li, Yingying & Xie, Shangyu & Zheng, Xinghua, 2016. "Efficient estimation of integrated volatility incorporating trading information," Journal of Econometrics, Elsevier, vol. 195(1), pages 33-50.
- Adam D. Bull, 2015. "Semimartingale detection and goodness-of-fit tests," Papers 1506.00088, arXiv.org, revised Jun 2016.
- Curato, Imma Valentina & Sanfelici, Simona, 2022. "Stochastic leverage effect in high-frequency data: a Fourier based analysis," Econometrics and Statistics, Elsevier, vol. 23(C), pages 53-82.
- Vladim'ir Hol'y & Petra Tomanov'a, 2020. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Papers 2003.13062, arXiv.org, revised Dec 2021.
- Vladim'ir Hol'y & Petra Tomanov'a, 2018. "Estimation of Ornstein-Uhlenbeck Process Using Ultra-High-Frequency Data with Application to Intraday Pairs Trading Strategy," Papers 1811.09312, arXiv.org, revised Jul 2022.
- Torben B. Rasmussen, 2009. "Jump Testing and the Speed of Market Adjustment," CREATES Research Papers 2009-08, Department of Economics and Business Economics, Aarhus University.
- Jonathan Haynes & Daniel Schmitt & Lukas Grimm, 2019. "Estimating stochastic volatility: the rough side to equity returns," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 449-469, December.
- Ole Martin & Mathias Vetter, 2019. "Laws of large numbers for Hayashi–Yoshida-type functionals," Finance and Stochastics, Springer, vol. 23(3), pages 451-500, July.
- Jean Jacod & Mark Podolskij & Mathias Vetter, 2008. "Intertemporal Asset Allocation with Habit Formation in Preferences: An Approximate Analytical Solution," CREATES Research Papers 2008-61, Department of Economics and Business Economics, Aarhus University.
- Anine E. Bolko & Kim Christensen & Mikko S. Pakkanen & Bezirgen Veliyev, 2020. "Roughness in spot variance? A GMM approach for estimation of fractional log-normal stochastic volatility models using realized measures," CREATES Research Papers 2020-12, Department of Economics and Business Economics, Aarhus University.
- Kalnina, Ilze, 2011. "Subsampling high frequency data," Journal of Econometrics, Elsevier, vol. 161(2), pages 262-283, April.