A striking feature of private equity (PE) is that performance is persistent, with many PE firms consistently producing high (or low) returns net of fees. We use a new variance decomposition model to isolate three components of performance persistence. We find a large amount of long-term...

The Sharpe ratio is the most widely used metric for comparing performance across investment managers and strategies, and the information ratio is as commonly used to evaluate performance relative to a benchmark. Although it is widely recognized that non-linearities arising from the inclusion of...

Financial analysts typically estimate volatilities and correlations from monthly or higher frequency returns when determining the optimal composition of a portfolio. Although it is widely acknowledged that these measures are not necessarily stationary across samples, most analysts assume...

For the popular mean-variance portfolio choice problem in the case without a risk-free asset, we develop a new portfolio strategy to mitigate estimation risk. We show that in both calibrations and real datasets, optimally combining the sample global minimum variance portfolio with a sample...

Estimates of standard performance measures can be improved by using returns on assets not used to define those measures. Alpha, the intercept in a regression of a fund's return on passive benchmark returns, can be estimated more precisely by using information in returns on nonbenchmark passive...

This paper develops an asset allocation framework that incorporates prior beliefs about the extent of stock return predictability explained by asset pricing models. We find that when prior beliefs allow even minor deviations from pricing model implications, the resulting asset allocations depart...

This paper develops a return forecasting methodology that allows for instability in the relationship between stock returns and predictor variables, for model uncertainty, and for parameter estimation uncertainty. The predictive regression specification that is put forward allows for occasional...

We propose a method for optimal portfolio selection using a Bayesian decision theoretic framework that addresses two major shortcomings of the Markowitz approach: the ability to handle higher moments and estimation error. We employ the skew normal distribution which has many attractive features...

This paper studies hedge fund return predictability in a multivariate setting. Our research design and analysis is motivated by the empirical observations that a specific forecasting model that is going to perform well is not known ex-ante and that modelling time varying return...