Building on insights from the economics of superstars, I develop an efficient method for estimating the skill of mutual fund managers. “Outliers” are helpful for distinguishing skill from luck in this framework — informative rather than spurious. Forecasted performance is dramatically...

We demonstrate that fund investors employ a heuristic benchmark model to estimate alphas and allocate capital. This can result in observational equivalence to CAPM driven investment decisions. The benchmark estimator trades off bias against precision, accommodating finite sample constraints. The...

We evaluate popular measures of hedge fund tail risk such as maximum drawdown (MDD) and worst one-period loss, and prove theoretically that realized tail risk is a downward-biased estimator of true tail risk. The bias can be almost 100% using a reasonable calibration. That is, true tail risk can...