We develop a continuous-time asset price model to capture short-run momentum and long-run reversal. By studying a dynamic asset allocation problem, we derive the optimal investment strategy in closed form and show that the combined momentum and reversal strategies are optimal. We then estimate...

We show that the pattern of positive pre-announcement market drift is present not only for FOMC announcements, as documented by Lucca and Moench (2015), but also for other major macroeconomic announcements such as Nonfarm Payroll, ISM and GDP. This commonality in pre-announcement returns leads...

Prior literature in accounting and financial economics measures asset growth as year-over-year growth in total assets. Such growth estimates are upward biased when firms engage in mergers and acquisitions. We decompose asset growth into merger-related and organic growth components, and find that...

Using four different asset pricing models to estimate the residual returns, I show empirically that there are no material differences in the statistical and economic significance between idiosyncratic momentum strategies based on different asset-pricing models. I also show that idiosyncratic...

In this paper, I develop a model in which risk-averse investors possess private information regarding both a stock's expected payoff and its risk. These investors trade in the stock and a derivative whose payoff is driven by the stock's risk. In equilibrium, the derivative is used to speculate...

Sentiment should exhibit its strongest effects on asset prices at times when valuations are most subjective. Consistent with this hypothesis, we show that a one-standard-deviation increase in aggregate uncertainty amplifies the predictive ability of sentiment for market returns by two to four...

Cross-predictability denotes the fact that some assets can predict other assets' returns. I propose a novel performance-based measure that disentangles the economic value of cross-predictability into two components: the predictive power of one asset's signal for other assets' returns...

Recent empirical evidence has shown that the relationship between idiosyncratic volatility and a stock's expected return depends on the pricing of the stock: it is negative among overvalued stocks and positive among undervalued ones. We provide both theoretical and numerical evidence that this...

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 average pricing errors—is improving in model parameterization (or “complexity”). Our results predict that the best...

We provide a short and selected review of the vast literature on cross-section predictability. We focus on the state of art methods used to forecast the cross-section of stock returns with major predictors and are primarily interested in the ideas, methods, and their applications. To understand...