In this paper, we examine the ability of hedge funds and funds of hedge funds to generate absolute returns using fund level data. Based on the comparison of the empirical distributions of the holding period returns of hedge funds, a U.S. stock index and a U.S. bond index, we classify hedge funds...

This paper analyses gender differences in hedge fund (HF) performance persistence using parametric and non-parametric risk-adjusted-performance persistence indicators. We find evidence consistent with performance persistence, which in relative (risk-adjusted) terms, is more pronounced amongst...

We give explicit algorithms and source code for extracting factors underlying Treasury yields using (unsupervised) machine learning (ML) techniques, such as nonnegative matrix factorization (NMF) and (statistically deterministic) clustering. NMF is a popular ML algorithm (used in computer...

I assess time-series return predictability using a weighted least squares estimator that is around 25% more efficient than ordinary least squares (OLS) because it incorporates time-varying volatility into its point estimates. Traditional predictors, such as the dividend yield, perform better in-...