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Volatility estimation via hidden Markov models

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  • Rossi, Alessandro
  • Gallo, Giampiero M.

Abstract

In this paper we suggest a convenient way to obtain parameter estimates of a discrete state hidden Markov volatility process within a framework consistent with observed option prices and stochastic volatility. Relative to similar proposals, we simplify the model estimation by resorting to some parametric approximation of the model in a maximum likelihood context. We show how correlation between returns and volatility innovations can be easily accommodated within this framework. Empirical applications illustrate model search strategies for the SP500 stock index, comparing the performances to a standard GARCH model.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Empirical Finance.

Volume (Year): 13 (2006)
Issue (Month): 2 (March)
Pages: 203-230

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Handle: RePEc:eee:empfin:v:13:y:2006:i:2:p:203-230

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References

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Citations

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Cited by:
  1. Frömmel, Michael, 2006. "Volatility Regimes in Central and Eastern European Countries' Exchange Rates," Hannover Economic Papers (HEP) dp-333, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  2. L. Grossi & G. Morelli, 2006. "Robust volatility forecasts and model selection in financial time series," Economics Department Working Papers 2006-SE02, Department of Economics, Parma University (Italy).
  3. repec:onb:oenbwp:y:2010:i:2:b:1 is not listed on IDEAS
  4. 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.
  5. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 7(2), pages 174-196, Spring.
  6. Thomas Lux & Leonardo Morales-Arias & Cristina Sattarhoff, 2011. "A Markov-switching Multifractal Approach to Forecasting Realized Volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy.

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