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Application of Hidden Markov Models and Hidden Semi-Markov Models to Financial Time Series

Citations

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Cited by:

  1. Milan Kumar Das & Anindya Goswami, 2019. "Testing of binary regime switching models using squeeze duration analysis," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-20, March.
  2. Wang, Shixuan & Gupta, Rangan & Zhang, Yue-Jun, 2021. "Bear, Bull, Sidewalk, and Crash: The Evolution of the US Stock Market Using Over a Century of Daily Data," Finance Research Letters, Elsevier, vol. 43(C).
  3. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
  4. Milan Kumar Das & Anindya Goswami, 2018. "Testing of Binary Regime Switching Models using Squeeze Duration Analysis," Papers 1807.04393, arXiv.org, revised Aug 2018.
  5. Wang, Ting & Bebbington, Mark, 2013. "Identifying anomalous signals in GPS data using HMMs: An increased likelihood of earthquakes?," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 27-44.
  6. Kaihua Deng, 2018. "Another Look at Large-Cap Stock Return Comovement: A Semi-Markov-Switching Approach," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 227-262, February.
  7. 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.
  8. Haas, Markus, 2009. "Persistence in volatility, conditional kurtosis, and the Taylor property in absolute value GARCH processes," Statistics & Probability Letters, Elsevier, vol. 79(15), pages 1674-1683, August.
  9. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2017. "Multiple risk measures for multivariate dynamic heavy–tailed models," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 1-32.
  10. Liu, Xinyi & Margaritis, Dimitris & Wang, Peiming, 2012. "Stock market volatility and equity returns: Evidence from a two-state Markov-switching model with regressors," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 483-496.
  11. Patrick Assonken & G. S. Ladde, 2015. "Option Pricing With A Levy-Type Stochastic Dynamic Model For Stock Price Process Under Semi-Markovian Structural Perturbations," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 18(08), pages 1-72, December.
  12. Vlad Stefan Barbu & Guglielmo D’Amico & Thomas Gkelsinis, 2021. "Sequential Interval Reliability for Discrete-Time Homogeneous Semi-Markov Repairable Systems," Mathematics, MDPI, vol. 9(16), pages 1-18, August.
  13. Hugh Christensen & Simon Godsill & Richard E Turner, 2020. "Hidden Markov Models Applied To Intraday Momentum Trading With Side Information," Papers 2006.08307, arXiv.org.
  14. Laurie Davies & Walter Kramer, 2016. "Stylized Facts and Simulating Long Range Financial Data," Papers 1612.05229, arXiv.org.
  15. Holzmann, Hajo & Schwaiger, Florian, 2016. "Testing for the number of states in hidden Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 318-330.
  16. Liu, Zhenya & Wang, Shixuan, 2017. "Decoding Chinese stock market returns: Three-state hidden semi-Markov model," Pacific-Basin Finance Journal, Elsevier, vol. 44(C), pages 127-149.
  17. Biswas, Arunangshu & Goswami, Anindya & Overbeck, Ludger, 2018. "Option pricing in a regime switching stochastic volatility model," Statistics & Probability Letters, Elsevier, vol. 138(C), pages 116-126.
  18. Arunangshu Biswas & Anindya Goswami & Ludger Overbeck, 2017. "Option Pricing in a Regime Switching Stochastic Volatility Model," Papers 1707.01237, arXiv.org, revised Jan 2018.
  19. Jan Bulla & Sascha Mergner & Ingo Bulla & André Sesboüé & Christophe Chesneau, 2011. "Markov-switching asset allocation: Do profitable strategies exist?," Journal of Asset Management, Palgrave Macmillan, vol. 12(5), pages 310-321, November.
  20. Apergis, Nicholas & Gozgor, Giray & Lau, Chi Keung Marco & Wang, Shixuan, 2019. "Decoding the Australian electricity market: New evidence from three-regime hidden semi-Markov model," Energy Economics, Elsevier, vol. 78(C), pages 129-142.
  21. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
  22. Luca De Angelis & Leonard J. Paas, 2013. "A dynamic analysis of stock markets using a hidden Markov model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1682-1700, August.
  23. Carlos A. Abanto‐Valle & Roland Langrock & Ming‐Hui Chen & Michel V. Cardoso, 2017. "Maximum likelihood estimation for stochastic volatility in mean models with heavy‐tailed distributions," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(4), pages 394-408, August.
  24. Elliott, Robert & Limnios, Nikolaos & Swishchuk, Anatoliy, 2013. "Filtering hidden semi-Markov chains," Statistics & Probability Letters, Elsevier, vol. 83(9), pages 2007-2014.
  25. Anindya Goswami & Omkar Manjarekar & Anjana R, 2018. "Option Pricing in a Regime Switching Jump Diffusion Model," Papers 1811.11379, arXiv.org, revised Oct 2019.
  26. Elizabeth Fons & Paula Dawson & Jeffrey Yau & Xiao-jun Zeng & John Keane, 2019. "A novel dynamic asset allocation system using Feature Saliency Hidden Markov models for smart beta investing," Papers 1902.10849, arXiv.org.
  27. Roland Langrock & Timo Adam & Vianey Leos‐Barajas & Sina Mews & David L. Miller & Yannis P. Papastamatiou, 2018. "Spline‐based nonparametric inference in general state‐switching models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 179-200, August.
  28. Andrea Arfè & Stefano Peluso & Pietro Muliere, 2021. "The semi-Markov beta-Stacy process: a Bayesian non-parametric prior for semi-Markov processes," Statistical Inference for Stochastic Processes, Springer, vol. 24(1), pages 1-15, April.
  29. Jo~ao Pedro Rodrigues do Carmo, 2018. "Modeling stock markets through the reconstruction of market processes," Papers 1803.06653, arXiv.org.
  30. Maruotti, Antonello & Petrella, Lea & Sposito, Luca, 2021. "Hidden semi-Markov-switching quantile regression for time series," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
  31. Lau, Marco Chi Keung & Vigne, Samuel A. & Wang, Shixuan & Yarovaya, Larisa, 2017. "Return spillovers between white precious metal ETFs: The role of oil, gold, and global equity," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 316-332.
  32. Guglielmo D'Amico & Filippo Petroni, 2020. "A micro-to-macro approach to returns, volumes and waiting times," Papers 2007.06262, arXiv.org.
  33. Milan Kumar Das & Anindya Goswami & Sharan Rajani, 2019. "Inference of Binary Regime Models with Jump Discontinuities," Papers 1910.10606, arXiv.org, revised Mar 2022.
  34. Bulla, Jan & Bulla, Ingo & Nenadic, Oleg, 2010. "hsmm -- An R package for analyzing hidden semi-Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 611-619, March.
  35. Guglielmo D’Amico & Ada Lika & Filippo Petroni, 2019. "Change point dynamics for financial data: an indexed Markov chain approach," Annals of Finance, Springer, vol. 15(2), pages 247-266, June.
  36. Ingmar Visser & Maarten Speekenbrink, 2014. "Comments on: Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 478-483, September.
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