Overlaying Time Scales in Financial Volatility Data

Eric Hillebrand
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Eric Hillebrand: Louisiana State University, Department of Economics

Econometrics from University Library of Munich, Germany

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.

Keywords: GARCH; volatility persistence; spurious high persistence; long memory; fractional integration; change-points; wavelets; time scales (search for similar items in EconPapers)
JEL-codes: C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2005-01-31
New Economics Papers: this item is included in nep-bec, nep-ecm and nep-ets
Note: Type of Document - pdf; pages: 40
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0501015

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