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Overlaying Time Scales in Financial Volatility Data

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Author Info

  • Eric Hillebrand

    (Louisiana State University, Department of Economics)

Abstract

Apart from the well-known, high persistence of daily financial volatility data, there is also a short correlation structure that reverts to the mean in less than a month. We find this short correlation time scale in six different daily financial time series and use it to improve the short-term forecasts from GARCH models. We study different generalizations of GARCH that allow for several time scales. On our holding sample, none of the considered models can fully exploit the information contained in the short scale. Wavelet analysis shows a correlation between fluctuations on long and on short scales. Models accounting for this correlation as well as long memory models for absolute returns appear to be promising.

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File URL: http://128.118.178.162/eps/em/papers/0501/0501015.pdf
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Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 0501015.

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Length: 40 pages
Date of creation: 31 Jan 2005
Date of revision:
Handle: RePEc:wpa:wuwpem:0501015

Note: Type of Document - pdf; pages: 40
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Web page: http://128.118.178.162

Related research

Keywords: GARCH; volatility persistence; spurious high persistence; long memory; fractional integration; change-points; wavelets; time scales;

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References

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  1. Elena Andreou & Eric Ghysels, 2002. "Detecting multiple breaks in financial market volatility dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600.
  2. Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 115-158, June.
  3. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  4. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
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Cited by:
  1. Jean-Pierre Fouque & Sebastian Jaimungal & Matthew Lorig, 2010. "Spectral Decomposition of Option Prices in Fast Mean-Reverting Stochastic Volatility Models," Papers 1007.4361, arXiv.org, revised Apr 2012.
  2. Vyacheslav Abramov & Fima Klebaner, 2007. "Estimation and Prediction of a Non-Constant Volatility," Asia-Pacific Financial Markets, Springer, vol. 14(1), pages 1-23, March.
  3. Matthew Lorig, 2010. "Time-Changed Fast Mean-Reverting Stochastic Volatility Models," Papers 1010.5203, arXiv.org, revised Apr 2012.

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