Multivariate distribution of returns in financial time series

Details Multivariate distribution of returns in financial time series Multivariate distribution of returns in financial time series

2003-10-14

arxiv.org/abs/cond-mat/0310300v1

Journal of Computational Methods in Sciences and Engineering, Volume 6, Number 5-6, pp. 315 - 324 (2006).

Physics

Condensed Matter

Talk given by M. I. Krivoruchenko at the International Conference of Computational Methods in Sciences and Engineering 2003 (I

Scientific paper

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). Free parameters of the model are fixed over the long term by fitting 100+ years of daily prices of the Dow Jones 30 Industrial Average. The multivariate probability density functions which we have constructed can be used for pricing derivative securities and risk management.

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