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Simulation-based sequential analysis of Markov switching stochastic volatility models

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Cited by:

  1. Kenichiro McAlinn & Asahi Ushio & Teruo Nakatsuma, 2020. "Volatility forecasts using stochastic volatility models with nonlinear leverage effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 143-154, March.
  2. Raggi, Davide & Bordignon, Silvano, 2012. "Long memory and nonlinearities in realized volatility: A Markov switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3730-3742.
  3. Sengupta, Raghu Nandan & Sengupta, Angana, 2011. "Some variants of adaptive sampling procedures and their applications," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3183-3196, December.
  4. Rimstad, Kjartan & Omre, Henning, 2013. "Approximate posterior distributions for convolutional two-level hidden Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 187-200.
  5. Monica Billio & Maddalena Cavicchioli, 2013. "�Markov Switching Models for Volatility: Filtering, Approximation and Duality�," Working Papers 2013:24, Department of Economics, University of Venice "Ca' Foscari".
  6. 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.
  7. Enrique Ter Horst & Abel Rodriguez & Henryk Gzyl & German Molina, 2012. "Stochastic volatility models including open, close, high and low prices," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 199-212, May.
  8. Liu Xiangdong & Li Xianglong & Zheng Shaozhi & Qian Hangyong, 2020. "PMCMC for Term Structure of Interest Rates under Markov Regime Switching and Jumps," Journal of Systems Science and Information, De Gruyter, vol. 8(2), pages 159-169, April.
  9. Karol Gellert & Erik Schlögl, 2021. "Parameter Learning and Change Detection Using a Particle Filter with Accelerated Adaptation," Risks, MDPI, vol. 9(12), pages 1-18, December.
  10. Gallo, Giampiero M. & Otranto, Edoardo, 2008. "Volatility spillovers, interdependence and comovements: A Markov Switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3011-3026, February.
  11. Kenichiro McAlinn & Asahi Ushio & Teruo Nakatsuma, 2016. "Volatility Forecasts Using Nonlinear Leverage Effects," Papers 1605.06482, arXiv.org, revised Dec 2017.
  12. Sadefo Kamdem, J. & Genz, A., 2008. "Approximation of multiple integrals over hyperboloids with application to a quadratic portfolio with options," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3389-3407, March.
  13. Abdelhakim Aknouche, 2017. "Periodic autoregressive stochastic volatility," Statistical Inference for Stochastic Processes, Springer, vol. 20(2), pages 139-177, July.
  14. Karamé, Frédéric, 2018. "A new particle filtering approach to estimate stochastic volatility models with Markov-switching," Econometrics and Statistics, Elsevier, vol. 8(C), pages 204-230.
  15. Audrone Virbickaite & Hedibert F. Lopes, 2018. "Bayesian Semi-Parametric Markov Switching Stochastic Volatility Model," DEA Working Papers 89, Universitat de les Illes Balears, Departament d'Economía Aplicada.
  16. Carlos A. Abanto‐Valle & Helio S. Migon & Hedibert F. Lopes, 2010. "Bayesian modeling of financial returns: A relationship between volatility and trading volume," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(2), pages 172-193, March.
  17. Trojan, Sebastian, 2013. "Regime Switching Stochastic Volatility with Skew, Fat Tails and Leverage using Returns and Realized Volatility Contemporaneously," Economics Working Paper Series 1341, University of St. Gallen, School of Economics and Political Science, revised Aug 2014.
  18. Aknouche, Abdelhakim, 2013. "Periodic autoregressive stochastic volatility," MPRA Paper 69571, University Library of Munich, Germany, revised 2015.
  19. Paul Gaskell & Frank McGroarty & Thanassis Tiropanis, 2014. "Signal Diffusion Mapping: Optimal Forecasting with Time Varying Lags," Papers 1409.6443, arXiv.org.
  20. Chiarella, Carl & He, Xue-Zhong & Huang, Weihong & Zheng, Huanhuan, 2012. "Estimating behavioural heterogeneity under regime switching," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 446-460.
  21. Dendramis, Yiannis & Kapetanios, George & Tzavalis, Elias, 2015. "Shifts in volatility driven by large stock market shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 130-147.
  22. He, Zhongfang & Maheu, John M., 2010. "Real time detection of structural breaks in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2628-2640, November.
  23. Morio, Jérôme & Jacquemart, Damien & Balesdent, Mathieu & Marzat, Julien, 2013. "Optimisation of interacting particle systems for rare event estimation," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 117-128.
  24. Prado, Raquel, 2013. "Sequential estimation of mixtures of structured autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 58-70.
  25. Saldaña-Zepeda, Dayna P. & Velasco-Cruz, Ciro & Torres-Preciado, Víctor H., 2020. "Mexican peso-USD exchange rate: A switching linear dynamical model application," International Economics, Elsevier, vol. 162(C), pages 80-91.
  26. Pan, Qi & Li, Yong, 2013. "Testing volatility persistence on Markov switching stochastic volatility models," Economic Modelling, Elsevier, vol. 35(C), pages 45-50.
  27. Francq, Christian & ZakoI¨an, Jean-Michel, 2008. "Deriving the autocovariances of powers of Markov-switching GARCH models, with applications to statistical inference," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3027-3046, February.
  28. Shoudong Chen & Yan-lin Sun & Yang Liu, 2018. "Forecast of stock price fluctuation based on the perspective of volume information in stock and exchange market," China Finance Review International, Emerald Group Publishing Limited, vol. 8(3), pages 297-314, May.
  29. Yu-Ying Tzeng & Paul M. Beaumont & Giray Ökten, 2018. "Time Series Simulation with Randomized Quasi-Monte Carlo Methods: An Application to Value at Risk and Expected Shortfall," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 55-77, June.
  30. Yanlin Shi, 2023. "Long memory and regime switching in the stochastic volatility modelling," Annals of Operations Research, Springer, vol. 320(2), pages 999-1020, January.
  31. Yun Bao & Carl Chiarella & Boda Kang, 2012. "Particle Filters for Markov Switching Stochastic Volatility Models," Research Paper Series 299, Quantitative Finance Research Centre, University of Technology, Sydney.
  32. Fernando Nascimento & Dani Gamerman & Hedibert Lopes, 2016. "Time-varying extreme pattern with dynamic models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 131-149, March.
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