A First Approach to Hedge Fund Replication – Linear Factor Models and Time Series Replication Models
Academic research in recent years has provided insight into hedge funds' systematic risk exposures and return sources. The current method of choice for analyzing and modeling hedge fund returns is broadly known as ‘linear factor-based analysis’. In this chapter I will present the merits and pitfalls of applying linear factor models to hedge fund returns. The question of how successful is not just academic; investment companies have stepped in to deliver these models in investable format. Linear factor analysis is the approach employed in the ‘first generation’ of hedge fund replication products.
This chapter also provides a practical understanding of the risk factor exposure of single hedge fund strategies. First-hand examples of actual models will clearly illustrate the merits and limitations of this approach and show that the explanatory power of available linear factor models is much greater for some hedge fund strategies than for others.
6.1 REVISITING SHARPE'S APPROACH
Multi-factor models are the simplest method for modeling the linear dependencies of a variable from other variables – in our case modeling the returns of a hedge fund from its systematic risk factors. These models are based on the statistical method of multilinear regression analysis.1
W. Sharpe introduced a unifying framework for such style models in 1992, in an effort to describe active management strategies ...