Social sciences · OECD FoS 5.2 · China MoE 020204 金融学
Finance
金融学
L2Local breakthroughs → Steady Score 2.45 · Last reviewed 2026-10-21 · Next review 2027-01-19
BIGGEST BREAKTHROUGH 2020-02-26 AI · majorField · major
Gu, Kelly & Xiu: Empirical asset pricing via ML (RFS) ↗
ML roughly doubles Sharpe ratios; a method advance, not a new theory
Why this level
ML asset pricing (Gu, Kelly & Xiu, RFS 2020) is a mainstream empirical method; quant and risk use is widespread, while LLMs remain assistive.
S = 0.30·method + 0.35·discovery + 0.25·adoption + 0.10·education (education scores 0 when there is no evidence; if empty, the other weights are renormalised)
Sources
Composite 1.5–2.49: at least one peer-reviewed/officially verified AI-key result, or one dimension at 3; routine workflow largely unchanged. All levels →
Research directions
ML asset pricingAlternative dataFinancial LLMs
Papers
- Deep Learning in Asset Pricing
Embeds no-arbitrage in deep nets; representative ML asset-pricing work
2024-02 · Management Science
- The Virtue of Complexity in Return Prediction
Theory and evidence that highly over-parameterised models improve return prediction
2023-12-21 · The Journal of Finance
- Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models
LLM headline reading predicts returns; heavily followed up
2023-04-15 · arXiv
- BloombergGPT: A Large Language Model for Finance
First large finance-specific LM
2023-03-30 · arXiv
- Empirical Asset Pricing via Machine Learning
ML roughly doubles Sharpe ratios; a method advance, not a new theory
2020-02-26 · The Review of Financial Studies
- Lineage-Aware Search Control for LLM-Based Evolutionary Factor Mining
Lineage-aware search control for LLM-driven evolutionary alpha-factor mining avoids collapsing onto similar factors.
2026-10-21 · arXiv · Xintong Liu, Chenkai Zhang, Yanzhao Ma, Peng Yang
- AuDQ: Auditable Data Quality through Agentic Rule Discovery
An auditable, governance-linked data-quality layer with agentic rule discovery for regulated tabular pipelines.
2026-10-19 · arXiv · Jacopo Biggiogera, Nicolas Colombo, Krati Saxena, Bhaskarjit Sarmah
- More Mentions, Less Information? Diagnosing Identity and Alignment in Reddit Embeddings for Volatility Forecasting
LLM embeddings of WallStreetBets posts reach out-of-sample R² 0.13 for log realised variance; the study diagnoses its source.
2026-10-18 · arXiv · Zhiyu Zheng
- How Well Do LLMs Perform in Peer Review? Evidence from Finance and Accounting
GPT-4o scores for 2024 AFA/NBER papers: +1 SD predicts 44% higher odds of top-three finance publication.
2026-10-13 · arXiv · Hai Lu, Yichen Luo, Luping Yu
- AlphaRLM: Aligning Language Models for Literature-Grounded Symbolic Factor Discovery
RL-trained LLMs construct executable symbolic alpha factors grounded in financial literature.
2026-10-10 · arXiv · Jie Huang, Yuecheng Hong, Yao Chen, Hao Zhong
- A Distributional Framework for Behavioral Characterization and Risk Management of Large Language Models
A distributional, Monte Carlo framework for characterising and managing LLM behavioural risk (e.g. borrower classification).
2026-10-08 · arXiv · David García-Lorite, Raul Merino
- Deep Learning vs. Statistical Models for Multi-Horizon Price Forecasting of Second-Hand Electronics: A Systematic Benchmark
First multi-horizon benchmark of statistical vs deep-learning models for used-electronics price forecasting.
2026-10-07 · arXiv · Mateusz Buczyński, Michał Woźniak, Konrad Kaczyński, Anna Wróblewska
- FactorBench: A Portfolio-Aware Benchmark for Automated Factor Mining
A portfolio-aware benchmark comparing automated factor-mining paradigms on generalisation, distinctness and economic value.
2026-10-03 · arXiv · Zhuohan Wang, Carmine Ventre
- From arXiv, bioRxiv, medRxiv and OpenAlex (last ~30 days); summaries written by AIMap from the abstract.
- BizAgentBench: Unveiling Hidden Challenges in Deploying Long-Horizon Agents for Real-World Business 2026-10-14
- LiveMACE: Process-Aware Evaluation of LLM Agent Capabilities in Evolving Markets 2026-10-07
- Learning Meta-Skills for Agent Harness Design in Test-Time AI4AI 2026-09-29
- IndicBankBench: Evaluating Safety and Reliability of Language Model Assistants in Indian Retail Banking 2026-09-24
- All related papers in the archive →
Milestones 6
Big glowing nodes are leaps: AI leap cool · Field leap warm · double ring = both
-
Industry
FCA: joint survey with the Bank of England shows 86% of financial firms now use AI (75% in 2024)Regulator-measured adoption; full report pending
FCA -
Paper
Chen, Pelger & Zhu: Deep Learning in Asset Pricing (Management Science)Embeds no-arbitrage in deep nets; representative ML asset-pricing work
Management ScienceTo be verified -
Paper
Kelly, Malamud & Zhou: The Virtue of Complexity in Return Prediction (J. Finance)Theory and evidence that highly over-parameterised models improve return prediction
The Journal of Finance -
Paper
Can ChatGPT forecast stock price movements? (arXiv 2304.07619)LLM headline reading predicts returns; heavily followed up
arXivPreprint -
Paper
Gu, Kelly & Xiu: Empirical asset pricing via ML (RFS)ML roughly doubles Sharpe ratios; a method advance, not a new theory
Review of Financial Studies
No milestones match this filter.
More papers & repos 5
| Type | Title | Date |
|---|---|---|
| Paper | Deep Learning in Asset Pricing To be verified | 2024-02 |
| Paper | The Virtue of Complexity in Return Prediction | 2023-12-21 |
| Paper | Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models Preprint | 2023-04-15 |
| Paper | BloombergGPT (arXiv 2303.17564) PreprintTo be verified | 2023-03 |
| Paper | Empirical Asset Pricing via Machine Learning | 2020-02-26 |
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