VaR stress tests for highly non‐linear portfolios

Abstract

Purpose

It is the purpose of this article to improve existing methods for risk management, in particular stress testing, for derivative portfolios. The method is explained and compared with other methods, using hypothetical portfolios.

Design/methodology/approach

Closed form option pricing formulas are used for valuation. To assess the risk, future price movements are modeled by an empirical distribution in conjunction with a semi‐parametrically estimated tail. This approach captures the non‐linearity of the portfolio risk and it is possible to estimate the extreme risk adequately.

Findings

It is found that this method gives excellent results and that it clearly outperforms the standard approach based on a quadratic approximation and the normal distribution. Especially for very high confidence levels, the improvement is dramatic.

Practical implications

In applications of this type the present method is highly preferable to the classical Delta‐Gamma cum normal distribution approach.

Originality/value

This paper uses a “statistics of extremes” approach to stress testing. With this approach it is possible to estimate the far tail of a derivative portfolio adequately.

Citation

Einmahl, J.H.J., Foppen, W.N., Laseroms, O.W. and de Vries, C.G. (2005), "VaR stress tests for highly non‐linear portfolios", Journal of Risk Finance, Vol. 6 No. 5, pp. 382-387. https://doi.org/10.1108/15265940510633451