Many modern macro finance models imply that excess returns on arbitrary assets are predictable via the price-dividend ratio and the variance risk premium of the aggregate stock market. We propose a simple empirical test for the ability of such a model to explain the cross-section of expected...

We examine the pricing of tail risk in international stock markets. We find that the tail risk of different countries is highly integrated. Introducing a new World Fear index, we find that local and global aggregate market returns are mainly driven by global tail risk rather than local tail...

Using a structural model of default, we construct a measure of systemic default defined as the probability that many firms default at the same time. We account for correlations in defaults between firms through exposures to common shocks. The systemic default measure spikes during recession...

I argue that academic research often inadequately accounts for alpha decay. As an anomaly's alpha (i.e., the risk-adjusted expected excess return) and realized returns are negatively related, alpha decay coincides with positive realized returns. If the alpha decays at publication, observers may...

We examine the predictability of expected stock returns across horizons using machine learning. We use neural networks, and gradient boosted regression trees on the U.S. and international equity datasets. We find that predictability of returns using neural networks models decreases with longer...

This paper provides global evidence supporting the hypothesis that expected return models are enhanced by the inclusion of variables that describe the evolution of book-to-market-changes in book value, changes in price, and net share issues. This conclusion is supported using data representing...