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

Andrei Leonidov; Vladimir Trainin; Alexander Zaitsev

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

Andrei Leonidov·Vladimir Trainin·Alexander Zaitsev

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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.

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Andrei Leonidov, Vladimir Trainin, Alexander Zaitsev. 2006-06-26. On collective non-gaussian dependence patterns in high frequency financial data. https://arxiv.org/abs/physics/0506072

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