In this paper, I build a model where financial intermediation slows the flow of capital. Investors optimally learn from intermediary performance to allocate capital toward profitable intermediaries. Intermediaries reach for yield, i.e invest in high tail risk assets, in an attempt to drive flows...

Text data is ultra-high dimensional, which makes machine learning techniques indispensable for textual analysis. Text is often selected--journalists, speechwriters, and others craft messages to target their audiences' limited attention. We develop an economically motivated high dimensional...

We study disruptions in debt markets during the COVID-19 crisis. The safer end of the credit spectrum experienced significant losses that are hard to fully reconcile with standard default or risk premium channels. Corporate bonds traded at a large discount to their corresponding CDS, and this...

Managed portfolios that take less risk when volatility is high produce large alphas, substantially increase factor Sharpe ratios, and produce large utility gains for mean-variance investors. We document this for the market, value, momentum, profitability, return on equity, and investment factors...

At the announcement of a new policy, agents form a view of state-contingent policy actions and impact. We develop a method to estimate this state-contingent perception and implement it for many asset-purchase interventions worldwide. Expectations of larger support in bad states--"policy...