Gambling Preferences, Options Markets, and Volatility [link](with Ben Blau and Ryan Whitby)Journal of Financial and Quantitative Analysis, 2016, 51(2): 515-540
This study examines whether the gambling behavior of investors affects volume and volatility in financial markets. Focusing on the options market, we find that the ratio of call option volume relative to total option volume is greatest for stocks with return distributions that resemble lotteries. Consistent with the theoretical predictions of Stein (1987), we demonstrate that gambling-motivated trading in the options market influences future spot price volatility. These results not only identify a link between lottery preferences in the stock market and the options market, but they also suggest that lottery preferences can lead to destabilized stock prices.
We provide evidence that arbitrageurs face a complex signal processing problem that delays the elimination of mispricing. Using a powerful database containing the precise timing of information announcements, we find that returns to many anomalies are concentrated in the 30 days after announcements and disappear soon thereafter. We find that prices incorporate information more quickly when portfolio rebalancing is less complex. Moreover, anomaly profits vanish more quickly and arbitrageurs trade more quickly as signal processing costs decline. Our evidence shows the timing of anomaly returns yields important insights about their existence, magnitudes, and relation to computational costs.
Institutional Investors, Short-Selling Constraints, and Information Acquisition(with Jesse Davis)
This paper highlights an important interaction between short-sale prohibitions and information acquisition. Investors faced with a short-sale prohibition acquire less information when the likelihood of trading is low. Unconstrained investors react to their competitors' constraint and acquire more information. Equilibrium prices are non-linear in fundamentals and price informativeness is asymmetric as a result of the short-sale prohibition. The novel predictions of the model are tested using unique measures of information acquisition from sophisticated market participants. When likely bound by their short-selling prohibition, investors decrease their information acquisition activity by up to 16%.
Not Everybody's Working for the Weekend: A Study of Mutual Fund Manager Effort(with Richard B. Evans)
By focusing on observable work activity on weekends and holidays, we provide a novel measure of mutual fund effort. We find considerable heterogeneity in mutual fund effort: larger, more expensive, better performing mutual funds tend to work harder, as do those that have recently experienced outflows. We also show that effort leads to better future performance, especially for families with low turnover and high active share. Finally, we show that effort is closely tied to managerial incentives as fund families with more competitive incentives put in more effort and reap the largest rewards from within-family increases effort.
Failures-to-Deliver, Limited Arbitrage, and Anomaly Returns(with Jeremiah Green and Edward Swanson)
We study the impact of Failures-to-Deliver (FTD) on price efficiency and future returns. When a stock experiences high FTDs, this (i) predicts high future FTDs, (ii) reduces price efficiency, such as increasing bid-ask spreads and price-impacts, and (iii) predicts lower future abnormal returns. We show that among a large set of anomalies, high FTDs result in higher future anomaly returns, driven primarily in the short-leg. Further, we show the effect of FTDs on anomaly returns is time-variant; high FTDs do not effect anomaly returns immediately, but instead lengthen the period of time in which anomaly returns are earned. Our results all suggest that FTDs represent a limit to arbitrage driven by illiquidity in the equity lending market.
Anomaly Returns and Information Acquisition
Using conventional methods (i.e., annual rebalancing) to study anomaly returns shows no relationship between abnormal returns and information acquisition. However, using a more focused event-time approach to measure anomaly returns following precise information release dates, we show that abnormal returns are drastically reduced by increased levels of information acquisition from sophisticated investors. This result is robust across a large subset of anomalies, controlling for confounding factors such as size, and even within recent time-periods. Our results suggest that anomaly returns are not entirely spurious or the result of data-mining and are not wholly driven by omitted risk-factors. Instead, a large portion of anomaly returns are the result of mispricing and the slow-diffusion of value-relevant information.