On collective non-gaussian dependence patterns in high frequency financial data
Physics and Society
2008-12-02 v3 Statistical Finance
Abstract
The analysis of observed conditional distributions of both lagged and simultaneous intraday price increments of a basket of stocks reveals phenomena of dependence - induced volatility smile and kurtosis reduction. A model based on multivariate t-Student distribution shows that the observed effects are caused by colelctive non-gaussian dependence properties of financial time series.
Keywords
Cite
@article{arxiv.physics/0506072,
title = {On collective non-gaussian dependence patterns in high frequency financial data},
author = {Andrei Leonidov and Vladimir Trainin and Alexander Zaitsev},
journal= {arXiv preprint arXiv:physics/0506072},
year = {2008}
}
Comments
misprints corrected