The Maximization of the Joint Probability in a Liability-Driven Investment Framework

Résumé du livre

In the wide panorama of investment strategies, the Liability-Driven one aims at creating an optimal portfolio by beating a chosen liability. In this paper we will extend the problem by considering as utility function, to be maximized, the joint probability that the Funding Ratio is above a predetermined threshold at different times, or that both the Funding Ratio and the portfolio value exceed such limits, or the two requests together. To do so, we propose a technique to maximize the joint probability without actually computing it, and we compare the results with the Cox's Approximation for the joint probability: what we find is that our method leads empirically to the same argmax of the joint probability computed through the Cox's Approximation for the bivariate and trivariate case, and we claim that is preferable to use our approach, being more general.