Factor Factory: How LLMs Are Reinventing Sparse Portfolio Optimization
TL;DR for operators Portfolio teams do not usually fail because they have no models. They fail because the models age, the signals decay, and the process of discovering new sparse selection logic is slow, expensive, and wonderfully allergic to market regime shifts. The paper behind EFS — Evolutionary Factor Search — proposes a useful change in framing: stop asking the LLM to “pick stocks” and ask it to generate executable alpha-factor formulas that can be backtested, filtered, evolved, and used to rank assets under sparse portfolio constraints.1 That distinction matters. The LLM is not the portfolio manager. It is the factor-factory intern with suspicious stamina. The backtest loop is still the adult in the room. ...