Data Envelopment Analysis (DEA) Integrated Risk Assessment Technique on Hedge Funds Investment: Theory and Practical Application

Abstract

This paper discusses Hedge funds' risks, in particular the leverage risk, as it has the greater effect when applied both to derivatives or other asset classes alike. Evaluation of the effect of leverage could become complicated as this effect could be escalated by the liquidity and credit risks underlying the invested assets. Unlike market risk, these are the risks that are not easy to hedge and need constant closed monitoring. Moreover, market risks could also evolve over time. This reinforced the importance of correlation in estimating the eventual effect, especially for complex portfolios and structured products. Under most cases, by segregating risks geographically and at a granular positional level, Hedge fund managers can also have more transparency to estimate direct or indirect relationships between strategies and correlations can still be calculated.

The proposed Data Envelopment Analysis (DEA) method in this paper, shows how the use of correlations of returns, and the consideration of the distributional characteristics of the Hedge funds, by suitably using appropriate risk and returns measures, is able to rank Hedge funds' performance. By further assessing the statistical properties of the performance and the ranked positions of Hedge funds, the proposed method aims to provide a reliable tool to assess risk of Hedge funds appropriately, which should support the Hedge funds selections process for the Funds of Hedge funds managers.

Keywords: Data Envelopment Analysis, Hedge funds, bootstrapping, Leverage Risk

JEL Classification: C15, C61, D81