Better Predictions, Fewer Ideas: The Alpha Agent's Exploration Problem
TL;DR for operators An automated quantitative researcher can improve its predictions while becoming less effective at discovering different sources of predictive information. Better factor scores, more formulas, and broader productive research are not interchangeable measures of success. AlphaDiverse addresses this problem by training local agents to select complementary economic hypotheses and implement them as executable factors. Its reinforcement-learning objective rewards both predictive improvement and contributions that existing signals do not already provide. ...