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Modeling stylized facts for financial time series

✍ Scribed by M.I. Krivoruchenko; E. Alessio; V. Frappietro; L.J. Streckert

Publisher: Elsevier Science
Year: 2004
Tongue: English
Weight: 173 KB
Volume: 344
Category: Article
ISSN: 0378-4371
DOI: 10.1016/j.physa.2004.06.129

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✦ Synopsis

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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