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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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Abstract

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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M. I. Krivoruchenko, E. Alessio, V. Frappietro, L. J. Streckert. 2004-11-03. Modeling stylized facts for financial time series. https://doi.org/10.1016/j.physa.2004.06.129

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