Modeling stylized facts for financial time series
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.
|Date of creation:||Jan 2004|
|Date of revision:||Nov 2004|
|Publication status:||Published in Physica A 344, 263-266 (2004)|
|Contact details of provider:|| Web page: http://arxiv.org/|
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