We show that idiosyncratic jumps are a key determinant of mean stock returns from both an ex post and ex ante perspective. Ex post, the entire annual average return of a typical stock accrues on the four days on which its price jumps. Ex ante, idiosyncratic jump risk earns a premium: a value-weighted weekly long-short portfolio that buys (sells) stocks with high (low) predicted jump probabilities earns annualized mean returns of 9.4% and four-factor alphas of 8.1%. This strategy’s returns are larger when there are greater limits to arbitrage. These results are consistent with investor aversion to idiosyncratic jump risk

We examine net arbitrage trading (NAT) measured by the difference between quarterly abnormal hedge fund holdings and abnormal short interest. NAT strongly predicts stock returns in the cross-section. Across ten well-known stock anomalies, abnormal returns are realized only among stocks experiencing large NAT. Exploiting Regulation SHO, which facilitated short selling for a random group of stocks, we present causal evidence that NAT has stronger return predictability among stocks facing greater limits to arbitrage. We also find large returns for anomalies that arbitrageurs chose to exploit despite capital constraints during the 2007–09 financial crisis. We confirm our findings using daily data. Received September 1, 2016; editorial decision May 28, 2018 by Editor Andrew Karolyi

We are the first to document the cross-sectional return seasonality effect in international government bonds. Using a variety of tests, we examine fixed-income securities from 22 countries for the years 1980–2018. The bonds with high (low) returns in the same-calendar month in the past continue to overperform (underperform) in the future. The effect is robust to many considerations, including controlling for established predictors of bond returns. Our results support the behavioural story of the anomaly, demonstrating its highest profitability in the periods of elevated investor sentiment and in the market segments of strong limits to arbitrage. Nonetheless, investment application of bond seasonality might be challenging due to high trading costs and the required short holding periods

We study the value premium using the multiples‐based market‐to‐book decomposition of Rhodes‐Kropf, Robinson, and Viswanathan (2005). The market‐to‐value component drives all of the value strategy return, while the value‐to‐book component exhibits no return predictability in either portfolio sorts or firm‐level regressions. Existing results linking market‐to‐book to operating leverage, duration, exposure to investment‐specific technology shocks, and analysts’ risk ratings derive from the unpriced value‐to‐book component. In contrast, results on expectation errors, limits to arbitrage, and certain types of cash flow risk and consumption risk exposure are due to the market‐to‐value component. Overall, our evidence casts doubt on several value premium theories