This paper examines the use of derivatives and its relation with risk taking in the hedge fund industry. In a large sample of hedge funds, 71% of the funds trade derivatives. After controlling for fund strategies and characteristics, derivatives users on average exhibit lower fund risks (e.g., market risk, downside risk, and event risk), such risk reduction is especially pronounced for directional-style funds. Further, derivatives users engage less in risk shifting and are less likely to liquidate in a poor market state. However, the flow-performance relation suggests that investors do not differentiate derivatives users when making investing decisions.

We develop an estimation approach based on a modified expectation-maximization (EM) algorithm and a mixture of normal distributions associated with skill groups to assess performance in hedge funds. By allowing luck to affect both skilled and unskilled funds, we estimate the number of skill groups, the fraction of funds from each group, and the mean and variability of skill within each group. For each individual fund, we propose a performance measure combining the fund’s estimated alpha with the cross-sectional distribution of fund skill. In out-of-sample tests, an investment strategy using our performance measure outperforms those using estimated alpha and t -statistic.

This paper examines whether self-described market timing hedge funds have the ability to time the U.S. equity market. We propose a new measure for timing return and volatility jointly that relates fund returns to the squared Sharpe ratio of the market portfolio. Using a sample of 221 market timing funds during 1994–2005, we find evidence of timing ability at both the aggregate and fund levels. Timing ability appears relatively strong in bear and volatile market conditions. Our findings are robust to other explanations, including public information-based strategies, options trading, and illiquid holdings. Bootstrap analysis shows that the evidence is unlikely to be attributed to luck.

This paper evaluates the ability of bond funds to “market time” nine common factors related to bond markets. Timing ability generates nonlinearity in fund returns as a function of common factors, but there are several non-timing-related sources of nonlinearity. Controlling for the non-timing-related nonlinearity is important. Funds’ returns are more concave than benchmark returns, and this would appear as poor timing ability in naive models. With controls, the timing coefficients appear neutral to weakly positive. Adjusting for nonlinearity, the performance of many bond funds is significantly negative on an after-cost basis, but significantly positive on a before-cost basis.

Stock exchange operators compete for order flow by setting “make” fees for limit orders and “take” fees for market orders. When traders can quote continuous prices, exchange operators compete on total fee, because traders can choose prices that perfectly neutralize any fee division. The 1-cent minimum tick size, however, prevents traders from neutralizing fee division. The nonneutrality of division between make and take fees (1) allows an exchange operator to establish exchanges that differ in fee structure to engage in second-degree price discrimination and (2) destroys the Bertrand equilibrium, leads to frequent fee changes, and encourages entries of new exchanges. Received May 29, 2016; editorial decision April 19, 2018 by Editor Robin Greenwood.

Short interest is currently required to be disclosed twice per month, but regulators have sought to increase this frequency. Meanwhile, short interest information from private third‐party vendors has emerged to meet investor demand on a daily basis. We find that daily private‐sector data strongly predict bimonthly regulatory disclosure. Furthermore, private‐sector data help price discovery, albeit with modest economic magnitude. Investors tend to underreact to the information content of private‐sector data mainly due to limits to arbitrage rather than market inattention. Despite the costly access to private‐sector data, we find no evidence that retail investors are harmed in their trades. Overall, our findings highlight the interplay between private‐sector and regulatory solutions in enhancing financial market transparency.

Short selling efficiency (SSE), measured each month by the slope coefficient of cross-sectionally regressing abnormal short interest on a mispricing score, significantly and negatively predicts stock market returns both in-sample and out-of-sample, suggesting that mispricing gets corrected after short sales are executed on the right stocks. We show conceptually and empirically that SSE has favorable predictive ability over aggregate short interest, as SSE reduces the effect of noises in short interest and better captures the amount of aggregate short selling capital devoted to overpricing. The predictive power is stronger during the periods of recession, high volatility, and low public information. In addition, low SSE precedes the months when the CAPM performs well and signals an efficient market. Overall, our evidence highlights the importance of the disposition of short sales in stock markets.

We study how sophisticated investors, when faced with shocks to information environment, change their information acquisition and trading behavior, and how these changes in turn affect market efficiency. We find that, after exogenous reductions of analyst coverage due to closures and mergers of brokerage firms, hedge funds scale up information acquisition, trade more aggressively, and earn higher abnormal returns on the affected stocks. The hedge fund participation also mitigates the impairment of market efficiency caused by coverage reductions. Overall, in a causal framework, our findings suggest a substitution effect between sophisticated investors and public information providers in facilitating market efficiency.

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.