We develop and implement methods for determining whether introducing new securities or relaxing investment constraints improves the investment opportunity set for prospect investors. We formulate a new testing procedure for prospect spanning for two nested portfolio sets based on subsampling and...

We consider parametric portfolio policies of any complexity using deep neural networks to optimize investor utility. Risk aversion acts as an economic regularization mechanism, with higher risk aversion constraining model complexity. Empirically, Deep Parametric Portfolio Policies (DPPP)...

We generalize the parametric portfolio policy framework to learning portfolio weights via deep neural networks. We find that network-based portfolio policies result in an increase of investor utility of between 30 and 100 percent over a comparable linear portfolio policy, depending on whether...

Ethanol has been the subject of intense debate following the adoption of the Energy Policy Act of 2005 (EPAct) which established that the gasoline supply in the United States (U.S.) must contain 10% ethanol. This work seeks to identify hedging ratios using dynamic multivariate GARCH to best...

This paper analyzes competition between mutual funds in a multiple funds version of the model of Hugonnier and Kaniel. We characterize the set of equilibria for this delegated portfolio management game and show that there exists a unique Pareto optimal equilibrium. The main result of this paper...