Model selection, i.e., the choice of an asset pricing model to the exclusion of competing models, is an inherently misguided strategy when the true model is unavailable to the researcher. This paper illustrates the advantages of a model pooling approach in characterizing the cross section of...

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...

This paper re-examines the tests of the Sharpe-Lintner Capital Asset Pricing Model (CAPM). The null that the CAPM intercepts are zero is tested for ten size-based stock portfolios and for twenty five book-to-market sorted portfolios using five-year, ten-year and longer sub-periods during...

We use the pattern recognition algorithm of Lo et al. (2000) with some modifications to determine whether quot;head-and-shouldersquot; price patterns have predictive power for future stock returns. The modifications include the use of filters based on typical price patterns identified by a...

Recent studies link mutual fund performance to measures of active management, and this evidence often takes the form of large spreads in unconditional alphas for characteristic-sorted portfolios. Unconditional benchmarks can, however, produce misleading inferences on managerial skill for...

This paper examines statistical problems which arise in empirical applications of the partial adjustment model with autoregressive errors when the model is nearly nonidentified. The results of Monte Carlo experiments show that the NLS estimation criterion function is multipeaked with high...

Recent years have seen increased demand from institutional investors for passive replication products that track the performance of hedge fund strategies using liquid investable assets such as futures contracts. In practice, linear replication methods suffer from poor tracking performance and...