Optimization with Tail-Dependence and Tail Risk: A Copula Based Approach for Strategic Asset Allocation

30 Pages Posted: 5 Nov 2006

See all articles by Francesco Paolo Natale

Francesco Paolo Natale

Università degli Studi di Milano-Bicocca

Date Written: November 3, 2006

Abstract

This paper proposes a method to overcome the classical drawbacks of the Monte Carlo methods for the asset allocation, namely resampling, deeply dependent upon the multinormal assumption. The proposed approach allows to set a barrier against joint extreme negative returns (tail-dependence) and extreme (negative) returns (univariate tail risk) not included in the multivariate normal distribution. The dangerous tail-dependence between asset returns is considered by using a copula based approach instead of the multinormal Monte Carlo simulation. Then the proposed model has been applied on a sample of eleven euro-denominated asset classes with historical inputs and the consequent asset weights have been tested on multivariate Student's t returns and on a set of out-of-the sample real returns. The results of this model provide evidence of a barrier against extreme negative returns occurring simultaneously. The proposed model is distribution-free and therefore it does not involve any a priori decision on the marginal distributions for asset returns.

Keywords: copula, simulation, tail index, EVT, asset allocation

JEL Classification: G11, C14, C15, C62

Suggested Citation

Natale, Francesco Paolo, Optimization with Tail-Dependence and Tail Risk: A Copula Based Approach for Strategic Asset Allocation (November 3, 2006). Available at SSRN: https://ssrn.com/abstract=942275 or http://dx.doi.org/10.2139/ssrn.942275

Francesco Paolo Natale (Contact Author)

Università degli Studi di Milano-Bicocca ( email )

Piazza dell'Ateneo Nuovo, 1
Milano, Milan 20126
Italy

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