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Modeling stylized facts for financial time series

  • M. I. Krivoruchenko
  • E. Alessio
  • V. Frappietro
  • L. J. Streckert
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    Multivariate probability density functions of returns are constructed in order to model the empirical behavior of returns in a financial time series. They describe the well-established deviations from the Gaussian random walk, such as an approximate scaling and heavy tails of the return distributions, long-ranged volatility-volatility correlations (volatility clustering) and return-volatility correlations (leverage effect). The model is tested successfully to fit joint distributions of the 100+ years of daily price returns of the Dow Jones 30 Industrial Average.

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    File URL: http://arxiv.org/pdf/cond-mat/0401009
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    Paper provided by arXiv.org in its series Papers with number cond-mat/0401009.

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    Date of creation: Jan 2004
    Date of revision: Nov 2004
    Publication status: Published in Physica A 344, 263-266 (2004)
    Handle: RePEc:arx:papers:cond-mat/0401009
    Contact details of provider: Web page: http://arxiv.org/

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