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...

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 study considers a (partially privatized) semi-public firm in a mixed duopoly and examines the welfare effects of discriminatory output subsidies under R&D competition. We find that the government grants higher subsidies to the private firm than to the semi-public firm, which induces the...

This study considers a mixed duopoly with research spillovers and examines the interplay between firms’ R&D decisions and government’s output subsidies. We investigate and compare the timing of the game between ex-ante R&D and ex-post R&D decisions where the R&D decisions are chosen before...

This paper considers time-inconsistent output subsidy/tax policies in free-entry mixed markets and compares committed and non-committed regimes under different competition modes. In a committed regime where the subsidy is determined before the private firms enter the market, the optimal rate is...

This paper investigates strategic choices between duopolistic firms’ R&D investments and government’s output subsidies in an endogenous timing game with research spillovers. We show that a simultaneous-move game among three players appears at equilibrium if the spillovers are very low while...

This study compares Cournot and Bertrand firms with research and development (R&D) competition under government policies between output and R&D subsidies. We demonstrate that firms invest more (less) in R&D and the government grants more (less) subsidies under Cournot than Bertrand competition...

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...

Many hedge funds attempt to achieve high returns by employing leverage. However, it is difficult to track the degree of leverage used by hedge funds over time because detailed timely information about their positions in asset markets is generally unavailable. This paper discusses how to combine...