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How Persistent is Stock Return Volatility? An Answer with Markov Regime Switching Stochastic Volatility Models

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  • Soosung Hwang
  • Steve E. Satchell
  • Pedro L. Valls Pereira

Abstract

We propose generalised stochastic volatility models with Markov regime changing state equations (SVMRS) to investigate the important properties of volatility in stock returns, specifically high persistence and smoothness. The model suggests that volatility is far less persistent and smooth than the conventional GARCH or stochastic volatility. Persistent short regimes are more likely to occur when volatility is low, while far less persistence is likely to be observed in high volatility regimes. Comparison with different classes of volatility supports the SVMRS as an appropriate proxy volatility measure. Our results indicate that volatility could be far more difficult to estimate and forecast than is generally believed. Copyright 2007 The Authors Journal compilation (c) 2007 Blackwell Publishing Ltd.

Suggested Citation

  • Soosung Hwang & Steve E. Satchell & Pedro L. Valls Pereira, 2007. "How Persistent is Stock Return Volatility? An Answer with Markov Regime Switching Stochastic Volatility Models," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 34(5-6), pages 1002-1024.
  • Handle: RePEc:bla:jbfnac:v:34:y:2007-06:i:5-6:p:1002-1024
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    Citations

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    Cited by:

    1. Gilles Dufrenot & Dominique Guegan & Anne Peguin-Feissolle, 2008. "Changing-regime volatility: a fractionally integrated SETAR model," Applied Financial Economics, Taylor & Francis Journals, vol. 18(7), pages 519-526.
    2. Alexander Subbotin & Thierry Chauveau & Kateryna Shapovalova, 2009. "Volatility Models : from GARCH to Multi-Horizon Cascades," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00390636, HAL.
    3. repec:kap:rqfnac:v:49:y:2017:i:4:d:10.1007_s11156-017-0619-z is not listed on IDEAS
    4. 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.
    5. Korkmaz, Turhan & Cevik, Emrah Ismail & Birkan, Elif & Özataç, Nesrin, 2010. "Testing CAPM using Markov switching model: the case of coal firms," MPRA Paper 71479, University Library of Munich, Germany, revised 2010.
    6. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    7. Subbotin, Alexandre, 2009. "Volatility Models: from Conditional Heteroscedasticity to Cascades at Multiple Horizons," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 15(3), pages 94-138.
    8. Pan, Qi & Li, Yong, 2013. "Testing volatility persistence on Markov switching stochastic volatility models," Economic Modelling, Elsevier, vol. 35(C), pages 45-50.
    9. repec:eee:reveco:v:51:y:2017:i:c:p:36-59 is not listed on IDEAS
    10. Gulten Mero & Serge Darolles & Gaëlle Le Fol, 2015. "Financial Market Liquidity: Who Is Acting Strategically?," THEMA Working Papers 2015-14, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.

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