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...

Blockchains, the technology underlying cryptocurrencies, face large fluctuations in user demand and marginal costs. These fluctuations make effective fee policies necessary to manage transaction service allocation. This paper models the conflict between the blockchain designer and validators...