We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premia. We demonstrate large economic gains to investors using machine learning forecasts, in some cases doubling the performance of leading regression-based...

How should an investor value financial data? The answer is complicated because it depends on the characteristics of all investors. We develop a sufficient statistics approach that uses equilibrium asset return moments to summarize all relevant information about others' characteristics. It can...

Optimal portfolios differ according to the length of time they are held without being rebalanced. For the case in which asset returns are identically and independently distributed, it has been shown that optimal portfolios become less diversified as the holding period lengthens.We show that the...

We present a dynamic model that links characteristic-based return predictability to systematic factors that determine the evolution of firm fundamentals. In the model, an economy-wide disruption process reallocates profits from existing businesses to new projects and thus generates a source of...

We study stock returns over the period of the global financial crisis of 2007-2008 and identify three crisis "shock factors" related to unique features of the crisis: (1) the collapse of global demand, (2) the contraction of credit supply, and (3) selling pressure on firms' equity. All three of...

In the finance literature, a common practice is to create factor-portfolios by sorting on characteristics (such as book-to-market, profitability or investment) associated with average returns. The goal of this exercise is to create a parsimonious set of factor-portfolios that explain the...

Recent theories suggest that both risk and mispricing are associated with commonality in security returns, and that the loadings on characteristic-based factors can be used to predict future returns. We supplement the market factor with two mispricing factors which capture long- and...

Rare events (RE) and long-run risks (LRR) are complementary elements for understanding asset-pricing patterns, including the average equity premium and the volatility of equity returns. We construct a model with RE (temporary and permanent parts) and LRR (including stochastic volatility) and...

A four-factor model with two "mispricing" factors, in addition to market and size factors, accommodates a large set of anomalies better than notable four- and five-factor alternative models. Moreover, our size factor reveals a small-firm premium nearly twice usual estimates. The mispricing...