Downside Risk Control of Derivative Portfolios with Mean-Reverting Underlyings

Abstract

We carry out a Monte-Carlo simulation of a standard portfolio management strategy involving derivatives, to estimate the sensitivity of its downside risk to a change of mean-reversion of the underlyings. We find that the higher the intensity of mean-reversion, the lower the probability of reaching a pre-determined loss level. This phenomenon appears of large statistical significance for large enough loss levels. We also find that the higher the mean-reversion intensity of the underlyings, the longer the expected time to reach those loss levels. The simulations suggest that selecting underlyings with high mean-reversion effect is a natural way to reduce the downside risk of those widely traded assets.