Our objective is to understand the trading strategy that would allow an investor to take advantage of quot;excessivequot; stock price volatility and quot;sentimentquot; fluctuations. We construct a general equilibrium model of sentiment. In it, there are two classes of agents and stock prices...

This paper analyses the links between advances in financial technology, investors’ sophistication, and the composition and returns of their financial portfolios. We develop a simple portfolio choice model under asymmetric information and derive some theoretical predictions. Using detailed...

We show that options written on stocks with low prices are over-priced. This effect is robust to a variety of tests, controlling for common stock- and option- risk characteristics, and to reasonable transaction costs. Natural experiments corroborate this finding; options tend to become...

Average skewness, which is defined as the average of monthly skewness values across firms, performs well at predicting future market returns. This result still holds after controlling for the size or liquidity of the firms or for current business cycle conditions. We also find that average...

We compare the performance of time-series (TS) and cross-sectional (CS) strategies based on past returns. While CS strategies are zero-net investment long/short strategies, TS strategies take on a time-varying net-long investment in risky assets. For individual stocks, the difference between the...

We build a macroeconomic model for Switzerland, the Euro Area, and the USA that drives the dynamics of several asset classes and the liabilities of a representative Swiss (defined-contribution) pension fund. This encompassing approach allows us to generate correlations between returns on assets...

We propose a new asset-pricing framework in which all securities' signals are used to predict each individual return. While the literature focuses on each security's own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes...

Donald Trump's election and his nomination of Scott Pruitt, a climate skeptic, to lead the Environmental Protection Agency drastically downshifted expectations on US climate-change policy. We study firms' stock-price reactions and institutional investors' portfolio adjustments after these...

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...

This article analyzes the effect of liquidity risk on the performance of various hedge fund portfolio strategies. Similarly to Avramov et al. (2007), we find that, before accounting for the effect of liquidity risk, hedge fund portfolios that incorporate predictability in managerial skills...