Testing the Gaussian copula hypothesis for financial assets dependences

• Published in: Quantitative finance Vol. 3; no. 4; pp. 231 - 250
• Main Authors: Malevergne, Y, Sornette, D
• Format: Journal Article
• Language: English
• Published: Routledge 01.08.2003; Taylor and Francis Journals; Taylor & Francis (Routledge)
• Series: Quantitative Finance
• Subjects: General Finance; Quantitative Finance; Copulas; Tail Dependence; Risk Management; Dependence Modelisation
• ISSN: 1469-7688; 1469-7696
• DOI: 10.1088/1469-7688/3/4/301

Using one of the key properties of copulas that they remain invariant under an arbitrary monotonic change of variable, we investigate the null hypothesis that the dependence between financial assets can be modelled by the Gaussian copula. We find that most pairs of currencies and pairs of major stocks are compatible with the Gaussian copula hypothesis, while this hypothesis can be rejected for the dependence between pairs of commodities (metals). Notwithstanding the apparent qualification of the Gaussian copula hypothesis for most of the currencies and the stocks, a non-Gaussian copula, such as the Student copula, cannot be rejected if it has sufficiently many 'degrees of freedom'. As a consequence, it may be very dangerous to embrace blindly the Gaussian copula hypothesis, especially when the coefficient of correlation between the pairs of assets is too high, such that the tail dependence neglected by the Gaussian copula can became large, leading to the ignoring of extreme events which may occur in unison.