Research
Working Papers
Abstract
Due to positive skewness in the distribution of monthly stock returns, a few stocks play a disproportionally outsized role in the performance of factors. Because skewed stocks can end up in either the long or short leg of the portfolio, their impact depends on how skewness is related to the characteristic used to create the anomaly. Anomalies that long skewed stocks benefit, while those short lose. In a sample of anomalies underlying recent factor models, a skewness managed strategy that seeks skewness in the long leg while avoiding it in the short leg improves the average return by five to ten percentage points per year. Factor models fail to price skewness managed versions of their own factors, resulting in alphas that are up to as large as the original anomaly premium.
Abstract
Anomaly strategies generate positive and significant CAPM alphas post-publication. Existing explanations include non-market risks, trading costs, and investment frictions. This paper introduces a complementary channel: when a new anomaly strategy is published, investors face uncertainty in identifying the optimal weight to allocate to the anomaly in order to achieve a positive alpha post-publication, making the strategy less appealing. Empirically, we find that the average post-publication alpha of anomaly strategies is close to zero when optimal weights are estimated out-of-sample using pre-publication data. This finding is robust across specifications, including those using empirical Bayesian shrinkage and machine learning to estimate weights. Conceptually, this suggests investors have little incentive to add a new anomaly strategy to their portfolios. While investors can generate positive out-of-sample alphas by combining multiple anomaly strategies via shrinkage methods, we show the demand from such investors is insufficient to eliminate alphas in equilibrium.
Abstract
This paper provides comprehensive tests for the presence of demand-side risks in investment and profitability premiums. Consumption risk, intermediary risk, macroeconomic risk, and investor sentiment are all considered as potential demand-side drivers of return. Factors based on the consumption and macroeconomic risk models have only a limited ability to price portfolios sorted on size and investment and are unable to price portfolios based on size and profitability. Of the two intermediary models, only the broker-dealer leverage factor succeeds in pricing both premiums, but this performance disappears with an updated version of the underlying data for broker-dealer leverage. Sentiment is unable to price either set of portfolios. All in all, the demand models considered are unlikely to explain empirically the supply-based premiums.
Published and Forthcoming
Abstract
Our paper sheds light on the complexity of liquidity injection programs by showing unintended consequences that arise when firm heterogeneity is overlooked. Utilizing firm-level data from the Paycheck Protection Program, we find government lending effectively reduced closures, particularly if received during the first two weeks. However, we find significant heterogeneity in the effectiveness of funds, resulting from broad-brush eligibility guidelines and differences in how firms process information. The implementation relied on the banking system, which exacerbated the distributional effects by favoring firms with stronger customer capital. Our findings highlight the importance of thoughtful liquidity distribution design to maximize its benefits.