Researchers have developed AlphaSchema, a novel framework for LLM-based alpha mining that structures the exploration of trading semantics. Unlike previous methods that implicitly delegate factor construction and search to LLMs, AlphaSchema explicitly defines a semantic space composed of Event, Context, Qualities, Direction, and Output. This approach decouples exploration from implementation, allowing LLMs to translate schema plans into executable factors while a surrogate model guides the search for optimal factors. Experiments on the Chinese stock market demonstrate that AlphaSchema discovers factor pools with strong predictive and portfolio performance, showing robustness across different LLMs. AI
IMPACT This framework could enhance systematic exploration and optimization in LLM-driven financial factor discovery.
RANK_REASON The cluster describes a research paper detailing a new framework for LLM-based alpha mining.
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