On collective non-gaussian dependence patterns in high frequency financial data

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.