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Overlaying Time Scales in Financial Volatility Data

In: Econometric Analysis of Financial and Economic Time Series

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  • Eric Hillebrand

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 generalized auto-regressive conditional heteroskedasticity (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.

Suggested Citation

  • Eric Hillebrand, 2006. "Overlaying Time Scales in Financial Volatility Data," Advances in Econometrics, in: Econometric Analysis of Financial and Economic Time Series, pages 153-178, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-9053(05)20025-7
    DOI: 10.1016/S0731-9053(05)20025-7
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