Asset returns and volatility clustering in financial time series
AbstractAn analysis of the stylized facts in financial time series is carried out. We find that, instead of the heavy tails in asset return distributions, the slow decay behaviour in autocorrelation functions of absolute returns is actually directly related to the degree of clustering of large fluctuations within the financial time series. We also introduce an index to quantitatively measure the clustering behaviour of fluctuations in these time series and show that big losses in financial markets usually lump more severely than big gains. We further give examples to demonstrate that comparing to conventional methods, our index enables one to extract more information from the financial time series.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1002.0284.
Date of creation: Feb 2010
Date of revision: Apr 2011
Publication status: Published in Physica A 390, 1300 - 1314 (2011)
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Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-02-13 (All new papers)
- NEP-ECM-2010-02-13 (Econometrics)
- NEP-FMK-2010-02-13 (Financial Markets)
- NEP-MST-2010-02-13 (Market Microstructure)
- NEP-RMG-2010-02-13 (Risk Management)
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- Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2009. "Econophysics: Empirical facts and agent-based models," Papers 0909.1974, arXiv.org, revised Jun 2010.
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