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.

We identify a parsimonious set of factors from a large pool of candidates for explaining hedge fund returns, ranging from equity market, anomaly, and trend-following factors to macroeconomic factors. The resulting 9-factor model, including five anomaly factors, outperforms existing hedge fund models both in sample and out of sample, with a significant reduction in alphas while showing substantial cross sectional performance heterogeneity. Further analysis based on fund holdings confirms the model’s ability to capture returns from arbitrage trading. Overall, the anomaly factors help quantify hedge fund strategies and risk exposures and improve fund performance evaluation.