English

Correlation structure of extreme stock returns

Disordered Systems and Neural Networks 2008-12-02 v2 Statistical Finance

Abstract

It is commonly believed that the correlations between stock returns increase in high volatility periods. We investigate how much of these correlations can be explained within a simple non-Gaussian one-factor description with time independent correlations. Using surrogate data with the true market return as the dominant factor, we show that most of these correlations, measured by a variety of different indicators, can be accounted for. In particular, this one-factor model can explain the level and asymmetry of empirical exceedance correlations. However, more subtle effects require an extension of the one factor model, where the variance and skewness of the residuals also depend on the market return.

Keywords

Cite

@article{arxiv.cond-mat/0006034,
  title  = {Correlation structure of extreme stock returns},
  author = {Pierre Cizeau and Marc Potters and Jean-Philippe Bouchaud},
  journal= {arXiv preprint arXiv:cond-mat/0006034},
  year   = {2008}
}

Comments

Substantial rewriting. Added exceedance correlations, removed some confusing material. To appear in Quantitative Finance

R2 v1 2026-07-22T10:03:29.050Z