A rules-based framework can optimize hedge fund–style allocation. The authors construct four hedge fund–style indices and use them to develop technical and fundamental indicators. The indicators generate recommendations to allocate available funds across the four hedge fund styles. The results suggest outperformance of more than 1% per year.
The authors develop a systematic hedge fund–style allocation model that captures the relevant hedge fund return drivers. Using these drivers, they develop technical and fundamental indicators to generate trading recommendations to optimize a portfolio consisting of four main hedge fund–style indices. The optimized portfolio delivers statistically significant outperformance against a benchmark of an equal-weighted hedge fund–style portfolio.
How Is This Research Useful to Practitioners?
The academic hedge fund literature has focused on an exploration of the return and risk characteristics of hedge fund styles and the added value these investments bring in a traditional equity and fixed-income portfolio context. There has been relatively little published about the optimal style allocation of hedge fund portfolios.
The four hedge fund–style indices that the authors construct are equity hedge, event driven, relative value, and tactical trading. They also develop a style allocation model to provide an allocation methodology and conduct an empirical study using the model’s best-fit specification. They present results that suggest annual outperformance of more than 1% over the period of January 1995–September 2010 against a benchmark of equal-weighted allocation across the four indices.
They show that the returns generated by this best-fit portfolio also exhibit superior risk–return characteristics and downside protection. In addition, the authors provide evidence that the outperformance is realized steadily over the sample period. The net asset value of the best-fit portfolio never falls behind that of the equal-weighted portfolio over the sample period.
It is possible, the authors conclude, to enhance hedge fund portfolio returns by using a systematic hedge fund–style allocation approach. They argue that their model, which incorporates financial market return factors and other technical and fundamental indicators, highlights the importance and validity of the approach.
How Did the Authors Conduct This Research?
The authors use January 1995-September 2010 as the sample period for their empirical analysis. They retrieve data from the refined Lipper TASS database and, after making some adjustments, create a database of 6,088 funds. They then categorize hedge funds into four major styles according to investment process and technique: equity hedge, event driven, relative value, and tactical trading.
To create a framework that offers an allocation methodology across the four style indices, the authors develop a hedge fund–style allocation model. The allocation model has three parts. First, they construct technical indicators that generate trading signals for targeting hedge fund exposures. Technical market analysis allows investors to allocate across fund styles in a manner more correlated with equity markets. The authors’ model uses the indices’ short-term and long-term simple moving averages.
Second, they incorporate a group of fundamental indicators to account for systematic and macroeconomic risks. Five fundamental indicators—hedge fund–style correlation, equity market correlation with hedge fund styles, market liquidity, business cycle volatility, and financial market volatility—are used. These five indicators contribute to a statistically significant aggregated outperformance across the four style indices.
Third, they combine both indicator groups with a rules-based portfolio construction mechanism. The mechanism contains two parameters: X (gross signal impact) and Y (relative weight of signals). The authors show that increases in X and Y enhance the performance of the model but also lead to increasingly extreme portfolio weights. They consider return performance, portfolio turnover, and weight distribution in defining the best-fit portfolio.
The authors’ study is a step forward for the literature and is relevant for many hedge fund investors. They demonstrate the value of a framework for hedge fund allocation and, by using widely available information and simple indicators, show that statistically significant outperformance can be achieved. This research provides an initial foundation for subsequent studies on the same subject. As the authors mention, the subsequent studies could develop an allocation framework at the hedge fund–strategy level because the risk exposures could be more refined at the strategy level. Also, the subsequent studies could use advanced technical indicators and fundamental indicators to refine the model further.