The outcomes of many activities depend upon both skill and luck. We analyze stock analysts' forecasts of companies' earnings per share under market conditions that vary in volatility and thus imply different levels of luck in outcomes. Noting that making forecasts that deviate widely from the...

We develop an approach that combines the estimation of monthly firm-level expected returns with an assignment of firms to (possibly) latent groups, both based upon observable characteristics, using machine learning principles with linear models. The best performing methods are flexible two-stage...