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Volatility dynamics under duration-dependent mixing

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  • Maheu, John M.
  • McCurdy, Thomas H.

Abstract

This paper proposes a new approach to modeling volatility changes and clustering. In particular, we use a parsimonious high-order Markov chain which allows for duration dependence. As in the standard 1st-order Markov-switching model, this structure can capture turning points and shifts in volatility due, for example, to policy changes or news events. However, unlike the 1st-order model, the duration-dependent Markov switching model is suited to exploiting the persistence associated with volatility clustering. To highlight the features of our model, we compare it to a popular benchmark, the GARCH model. Unlike the latter, the proposed parameterization allows time-varying persistence, includes a stochastic component for volatility, and incorporates anticipated discrete changes in the level of volatility. The empirical distribution generated by our proposed structure works well for the samples of data used in this paper. Implications for forecasts relevant for risk management are emphasized.
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Suggested Citation

  • Maheu, John M. & McCurdy, Thomas H., 2000. "Volatility dynamics under duration-dependent mixing," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 345-372, November.
  • Handle: RePEc:eee:empfin:v:7:y:2000:i:3-4:p:345-372
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    Cited by:

    1. Lunde A. & Timmermann A., 2004. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 253-273, July.
    2. Laurent Calvet & Adlai Fisher, 2003. "Regime-Switching and the Estimation of Multifractal Processes," NBER Working Papers 9839, National Bureau of Economic Research, Inc.
    3. Suhejla Hoti & Esfandiar Maasoumi & Michael McAleer & Daniel Slottje, 2009. "Measuring the Volatility in U.S. Treasury Benchmarks and Debt Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 522-554.
    4. repec:exl:2manag:v:17:y:2016:i:2:p:241-260 is not listed on IDEAS
    5. John M. Maheu & Thomas H. McCurdy & Yong Song, 2012. "Components of Bull and Bear Markets: Bull Corrections and Bear Rallies," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 391-403, February.
    6. Henryk Gurgul & Robert Syrek & Christoph Mitterer, 2016. "Price duration versus trading volume in high-frequency data for selected DAX companies," Managerial Economics, AGH University of Science and Technology, vol. 17(2), pages 241-260, December.
    7. Jeff Fleming & Chris Kirby, 2013. "Component-Driven Regime-Switching Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 11(2), pages 263-301, March.

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