Working Papers

Eponymous Hedge Funds (with V. Agarwal and T. Trinh)  

We examine if eponymy in the hedge fund industry, i.e., naming a fund after the founder/manager, is associated with managers signaling their ability and/or ethical behavior. Our results are consistent with the latter, i.e., eponymous managers are neither skilled nor outperform their non-eponymous peers but exhibit lower operational and fraud risks. If eponymous funds commit regulatory violations and breach investors’ trust, they receive lower flows despite performing well. However, they receive higher flows if they do not violate. Our findings suggest that eponymy serves as a useful signal to investors who value a fund manager's ethical behavior besides performance.

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.