Estimating Stochastic Volatility and Jumps Using High-Frequency Data and Bayesian Methods
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- Franses,Philip Hans & Dijk,Dick van, 2000.
"Non-Linear Time Series Models in Empirical Finance,"
Cambridge Books,
Cambridge University Press, number 9780521779654.
- Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415.
- Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2017.
"Inference on Self‐Exciting Jumps in Prices and Volatility Using High‐Frequency Measures,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 504-532, April.
- Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2013. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Monash Econometrics and Business Statistics Working Papers 28/13, Monash University, Department of Econometrics and Business Statistics.
- Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2016. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Monash Econometrics and Business Statistics Working Papers 8/16, Monash University, Department of Econometrics and Business Statistics.
- Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2014. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Papers 1401.3911, arXiv.org, revised Mar 2016.
- Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2014. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Monash Econometrics and Business Statistics Working Papers 30/14, Monash University, Department of Econometrics and Business Statistics.
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005.
"Volatility Forecasting,"
PIER Working Paper Archive
05-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," NBER Working Papers 11188, National Bureau of Economic Research, Inc.
- Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
- 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.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003.
"Modeling and Forecasting Realized Volatility,"
Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
- 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.
- Jan Hanousek & Ev??en Ko??enda & Jan Novotn??, 2013. "Price Jumps on European Stock Markets," William Davidson Institute Working Papers Series wp1059, William Davidson Institute at the University of Michigan.
- Jiří Witzany, 2013.
"Estimating Correlated Jumps and Stochastic Volatilities,"
Prague Economic Papers, Prague University of Economics and Business, vol. 2013(2), pages 251-283.
- Jiří Witzany, 2011. "Estimating Correlated Jumps and Stochastic Volatilities," Working Papers IES 2011/35, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2011.
- Ole E. Barndorff-Nielsen, 2004.
"Power and Bipower Variation with Stochastic Volatility and Jumps,"
Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
- Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Power and bipower variation with stochastic volatility and jumps," Economics Papers 2003-W17, Economics Group, Nuffield College, University of Oxford.
- Emmanuel Bacry & Iacopo Mastromatteo & Jean-Franc{c}ois Muzy, 2015. "Hawkes processes in finance," Papers 1502.04592, arXiv.org, revised May 2015.
- Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002.
"Bayesian Analysis of Stochastic Volatility Models,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
- Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 371-389, October.
- Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models: Comments: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 413-417, October.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007.
"Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility,"
The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2005. "Roughing it Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," NBER Working Papers 11775, National Bureau of Economic Research, Inc.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," CREATES Research Papers 2007-18, Department of Economics and Business Economics, Aarhus University.
- Bjørn Eraker, 2004. "Do Stock Prices and Volatility Jump? Reconciling Evidence from Spot and Option Prices," Journal of Finance, American Finance Association, vol. 59(3), pages 1367-1404, June.
- repec:hal:journl:peer-00741630 is not listed on IDEAS
- Jonathan R. Stroud & Michael S. Johannes, 2014. "Bayesian Modeling and Forecasting of 24-Hour High-Frequency Volatility," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1368-1384, December.
- Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005.
"A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data,"
Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
- Lan Zhang & Per A. Mykland & Yacine Ait-Sahalia, 2003. "A Tale of Two Time Scales: Determining Integrated Volatility with Noisy High Frequency Data," NBER Working Papers 10111, National Bureau of Economic Research, Inc.
- Prosper Dovonon & Sílvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2019.
"Bootstrapping High-Frequency Jump Tests,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 793-803, April.
- Prosper Dovonon & Silvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2016. "Bootstrapping high-frequency jump tests," CIRANO Working Papers 2016s-24, CIRANO.
- Dovonon, Prosper & Goncalves, Silvia & Hounyo, Ulrich & Meddahi, Nour, 2017. "Bootstrapping high-frequency jump tests," TSE Working Papers 17-810, Toulouse School of Economics (TSE).
- Dovonon, Prosper & Goncalves, Silvia & Hounyo, Ulrich & Meddahi, Nour, 2017. "Bootstrapping high-frequency jump tests," IDEI Working Papers 870, Institut d'Économie Industrielle (IDEI), Toulouse.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008.
"Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise,"
Econometrica, Econometric Society, vol. 76(6), pages 1481-1536, November.
- Ole E Barndorff-Nielsen & Peter Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," OFRC Working Papers Series 2006fe05, Oxford Financial Research Centre.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Papers 2006-W03, Economics Group, Nuffield College, University of Oxford.
- Suzanne S. Lee & Per A. Mykland, 2008. "Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics," The Review of Financial Studies, Society for Financial Studies, vol. 21(6), pages 2535-2563, November.
- Aït-Sahalia, Yacine & Cacho-Diaz, Julio & Laeven, Roger J.A., 2015.
"Modeling financial contagion using mutually exciting jump processes,"
Journal of Financial Economics, Elsevier, vol. 117(3), pages 585-606.
- Yacine Aït-Sahalia & Julio Cacho-Diaz & Roger J.A. Laeven, 2010. "Modeling Financial Contagion Using Mutually Exciting Jump Processes," NBER Working Papers 15850, National Bureau of Economic Research, Inc.
- Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
- Markku Lanne, 2006. "Forecasting Realized Volatility by Decomposition," Economics Working Papers ECO2006/20, European University Institute.
- Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2014.
"A Robust Neighborhood Truncation Approach To Estimation Of Integrated Quarticity,"
Econometric Theory, Cambridge University Press, vol. 30(1), pages 3-59, February.
- Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2013. "A robust neighborhood truncation approach to estimation of integrated quarticity," International Finance Discussion Papers 1078, Board of Governors of the Federal Reserve System (U.S.).
- Viktor Todorov, 2010. "Variance Risk-Premium Dynamics: The Role of Jumps," The Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 345-383, January.
- Shephard, Neil (ed.), 2005. "Stochastic Volatility: Selected Readings," OUP Catalogue, Oxford University Press, number 9780199257201.
- Andras Fulop & Junye Li & Jun Yu, 2015. "Self-Exciting Jumps, Learning, and Asset Pricing Implications," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 876-912.
- Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
- 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.
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- Makoto Nakakita & Teruo Nakatsuma, 2021. "Bayesian Analysis of Intraday Stochastic Volatility Models of High-Frequency Stock Returns with Skew Heavy-Tailed Errors," JRFM, MDPI, vol. 14(4), pages 1-29, March.
- Janda, Karel & Kourilek, Jakub, 2020. "Residual shape risk on natural gas market with mixed jump diffusion price dynamics," Energy Economics, Elsevier, vol. 85(C).
- Jiří Witzany & Milan Fičura, 2023. "Machine Learning Applications to Valuation of Options on Non-liquid Markets," FFA Working Papers 5.001, Prague University of Economics and Business, revised 24 Jan 2023.
- Milan Fičura & Jiří Witzany, 2018. "Use of Adapted Particle Filters in SVJD Models," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2018(3), pages 5-20.
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More about this item
Keywords
stochastic volatility; Bayesian inference; quadratic variation; realized variance; bipower variation; self-exciting jumps;All these keywords.
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- G1 - Financial Economics - - General Financial Markets
Statistics
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