Exploring Limitations of Return-Based Exposure Estimation for Hedge Funds

Abstract

Return-based methods are frequently used by risk managers to estimate the exposures of hedge funds due to limited transparency. This article proposes a method to assess the limitations of such methods using the posterior Cramer-Rao bound (PCRB) concept. This PCRB methodology allows one to quantify the maximum achievable accuracy of exposure estimates without having to compare computed estimates to actual exposures. This is particularly useful in situations where exposure data are unavailable. The main determinants of the PCRB are shown to be the variance of the hedge fund exposures and the ratio of market variance to idiosyncratic error variance. To illustrate the application of the methodology, the authors provide five examples in which they compare the PCRB to the computed estimation error using real hedge fund data.