Correlation structure of extreme stock returns

Thumbnail Image

Date

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Description

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

Keywords

Disordered Systems and Neural Networks, Statistical Finance

Citation

URI

http://salesiana.dossiersoluciones.com/handle/123456789/208658

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/cond-mat/0006034
 http://arxiv.org/abs/cond-mat/0006034
 Quantitative Finance 1 217-222 (2001)

Collections

arXiv