arXiv AI
FactorEngine: A Program-level Knowledge-Infused Factor Mining Framework for Quantitative Investment
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FaVOR: LLM-Based Agentic Framework for Factor Mining via Empirical Validation
arXiv:2608.30192v1 Announce Type: new Abstract: Traditional finance relies on experts to hand-craft factors through a principled process grounded in economic rationale. Recent LLM-based multi-agent s...
arXiv AI
Jul 31
AlphaSchema: Exploring the Space of Trading Semantics for LLM-Based Alpha Mining
arXiv:2607. 26642v1 Announce Type: new Abstract: Automated alpha mining has increasingly adopted large language model (LLM) agents for factor generation and iterative discovery.
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AlphaSchema: Exploring the Space of Trading Semantics for LLM-Based Alpha Mining
Automated alpha mining has increasingly adopted large language model (LLM) agents for factor generation and iterative discovery. However, existing LLM-based systems often delegate both factor construction and search decisions to the agent itself, without an explicit exploration space or a principled mechanism for navigating that space.
arXiv AI
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Alpha-R1: Alpha Screening with LLM Reasoning via Reinforcement Learning
Alpha‑R1 introduces a reinforcement‑learning aligned large language model framework that performs context‑aware alpha screening by semantically gating candidate factors against a dynamic market state description. The model, trained with group relative policy optimization using realized portfolio returns as reward, selects a sparse subset of factors whose economic rationale matches current market conditions. In a 12‑month out‑of‑sample test, Alpha‑R1 achieved annualized returns of 47.87% on the S&P 500 and 40.57% on the CSI 300, with Sharpe ratios of 1.62 and 2.23, demonstrating the effectiveness of semantic factor reranking in non‑stationary markets.
arXiv AI
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AQuA: Recursively Self-Improving Quantitative Trading Research Agents
arXiv:2608. 12841v1 Announce Type: cross Abstract: We study recursive self-improvement at the level of quantitative-investment research: whether an autonomous system can use evidence from earlier experiments to improve the hypotheses and candidates proposed in later iterations.
arXiv AI
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AlphaEval: A Comprehensive and Efficient Evaluation Framework for Formula Alpha Mining
arXiv:2508. 13174v2 Announce Type: replace Abstract: Formula alpha mining, which generates predictive signals from financial data, is critical for quantitative investment.