Evaluating Hedge Funds with Pooled Benchmarks

Michael S. O’Doherty (), N. E. Savin () and Ashish Tiwari ()
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Michael S. O’Doherty: Department of Finance, Trulaske College of Business, University of Missouri, Columbia, Missouri 65211
N. E. Savin: Department of Economics, Tippie College of Business, University of Iowa, Iowa City, Iowa 52242
Ashish Tiwari: Department of Finance, Tippie College of Business, University of Iowa, Iowa City, Iowa 52242

Management Science, 2016, vol. 62, issue 1, 69-89

Abstract: The evaluation of hedge fund performance is challenging given the flexible nature of hedge funds’ strategies and their lack of operational transparency. As a result, inference about skill is inevitably contaminated by the error in the benchmark model. To address this concern, we propose a model pooling approach to develop a fund-specific benchmark obtained by pooling a set of diverse attribution models. The weights assigned to the individual models in the pool are based on the log score criterion, an information-theoretic measure of the conditional performance of a model. We illustrate the advantages of a pooled benchmark over alternative approaches, including the Fung and Hsieh [Fung W, Hsieh DA (2004) Hedge fund benchmarks: A risk-based approach. Financial Analysts J. 60:65–80] model, stepwise regression methods, and style-adjusted methods in the contexts of a real-time investment strategy, hedge fund replication, and fund failure prediction. This paper was accepted by Wei Jiang, finance .

Keywords: hedge funds; performance evaluation; model pooling; model combination; hedge fund replication; log score (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (9)

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