Modeling stylized facts for financial time series

M.I. Krivoruchenko, E. Alessio, V. Frappietro and L.J. Streckert

Physica A: Statistical Mechanics and its Applications, 2004, vol. 344, issue 1, 263-266

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.

Keywords: Time series; Scaling; Heavy tails; Volatility clustering; Leverage effect (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:344:y:2004:i:1:p:263-266

DOI: 10.1016/j.physa.2004.06.129

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