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...

Corporate bonds with large increases in implied volatility over the past month underperform those with large decreases in implied volatility by 0.6% per month. In contrast to An, Ang, Bali, and Cakici (2014) who show that implied volatility changes carry information about fundamental news, our...

We use information from over two million trading strategies that are randomly generated using real data, and from strategies that survive the publication process to infer the statistical properties of the set of strategies that could have been studied by researchers. Using this set, we compute...

We study the relation between order imbalance and past returns and firm characteristics and test a number of hypothesis including the disposition effect, momentum and contrarian trading, tax-loss selling and flight-to-quality hypothesis. These hypotheses make predictions about investors buy or...

We study the selection of private equity managers (GPs) for over 100,000 capital commitments between 1990 and 2019 by global institutional investors (LPs) choosing from a plausible contemporaneous opportunity set. In addition to chasing GPs with high prior performance, LPs have large...

We study how plan sponsors choose investment management firms from their opportunity set when delegating $1.6 trillion in assets between 2002 and 2017. Two factors play an influential role in choice: pre-hiring returns, and pre-existing personal connections between personnel at the plan (or...

We provide a comprehensive study on the cross-sectional predictability of corporate bond returns using big data and machine learning. We examine whether a large set of equity and bond characteristics drive the expected returns on corporate bonds. Using either set of characteristics, we find that...

We propose a unified set of distance-based performance metrics that address the power and extreme-error problems inherent in traditional measures for asset-pricing tests. From a Bayesian perspective, the distance metrics coherently incorporate both pricing errors and their standard errors....

We find that single-name options trading increases the absolute level of information content of prices (stock price informativeness). We confirm our results through instrumental variable approach to control for potential endogeneity. We further show causality by using a difference-in-difference...

Return anomalies are most pronounced among distressed stocks. We attribute this finding to the role of misvaluation and investors' inability to value distressed stocks correctly. We treat distressed stocks as options and construct a valuation model that explicitly takes into account the value of...