AlphaRLM: Aligning Language Models for Literature-Grounded Symbolic Factor Discovery
arXiv:2610.14959v3 Announce Type: replace Abstract: Formulaic alpha mining seeks to discover executable expressions that capture predictive market signals in a vast, noisy search space. Recent LLM-based approaches use prompting, iterative search, or seed-factor evolution, leaving direct factor construction through policy learning less explored. To address this, we introduce AlphaRLM, a reinforcement-learning framework that trains LLMs to construct executable symbolic factors from financial lite…