Working Papers
Eponymous Hedge Funds (with V. Agarwal and T. Trinh)
We investigate whether eponymous hedge funds—those named after their founder/manager—signal managerial ability or ethical behavior. While such funds do not outperform non-eponymous peers, they exhibit lower operational and fraud risks. Survey evidence supports these findings. Eponymous funds that violate regulations and breach investors' trust experience reduced investor flows despite strong performance. Offsetting these costs, eponymous fund managers benefit from lower failure rates and better contractual terms such as higher incentive fees and greater share restrictions. These results suggest that eponymy serves as a credible signal of ethical behavior and personal commitment, valued by investors beyond performance alone.
Quantile Regressions: Estimating Moments of the Stock Return Distribution
This paper offers a simple yet effective way of estimating the moments of a stock's return distribution. The methodology is based on quantile regression, which is able to effectively summarize a stock's return moments by using a rich set of information about different parts of the stock's return distribution. Using recursively estimated monthly panel data quantile regressions, the proposed methodology first estimates the conditional quantiles of the stock return distribution as a linear function of exogenous variables that are found to be important in return predictability literature. Next, combining the estimates from quantile regressions with the values of the predictor variables measured at the end of the estimation window, the methodology generates forward-looking estimates of stocks' return quantiles at different return horizons ranging from 1 day to 2 years. Finally, our methodology calculates stocks' expected physical moments based on a discrete approximation of the return distribution calculated via the fitted return quintiles. Potential application areas of the proposed methodology are discussed and an example in variance forecasting is offered.