We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance---in terms of SDF Sharpe ratio and test asset pricing errors---is improving in model parameterization (or "complexity''). Our empirical findings verify the...

Lotto demand modeling typically focuses on a single game and evaluates whether estimated “effective price” (expected loss from buying one ticket) elasticity is consistent with net revenue maximization. However, a portfolio of several different lottery games is now usually offered to players...

Active fee is the ratio between the excess cost of active management over the index alternative and the fund's activity level. We suggest a simple model that explains active capital allocations in the presence of time-varying active fee. We show that investors respond in accordance with the...