Forecasting stock returns is extremely challenging in general, and this task becomes even more difficult given the turbulent nature of the Chinese stock market. We address the stock selection process as a statistical learning problem and build cross-sectional forecast models to select individual...

This paper investigates bond return predictability and its economic value. Using regression models, we first examine both the statistical and economic significance of bond return predictability in the Chinese market, and analyze the non-Markov and stochastic volatility properties of bond yields....

We apply four machine learning methods to cross-sectional return prediction for hedge fund selection. We equip the forecast model with a set of idiosyncratic features, which are derived from historical returns of a hedge fund and capture a variety of fund-specific information. Evaluating the...