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...

US money market funds (MMFs) play an important role in short-term markets as large investors of Treasury bills (T-bills) and repurchase agreements (repos) with banks and the Federal Reserve, some of the world’s safest and most liquid assets. We build a theoretical model in which MMFs’...

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...

We introduce a new channel through which US money market funds (MMFs) affect the pricing of near-money assets and measured convenience yields. Our theoretical model reveals that MMFs' strategic interactions create frictions that are exacerbated by T-bill market illiquidity. Using instrumental...

Firms in emerging markets borrow more in foreign currency when the local currency actually provides a better hedge in downturns. Motivated by this fact, we develop an international corporate finance model in which firms facing adverse selection choose the foreign currency share of their debt. In...