--- title: ML-Quant url: https://www.ml-quant.com/ site: ML-Quant (https://www.ml-quant.com) updated: 2026-10-09 license: Summaries CC BY 4.0; links go to the original sources index: https://www.ml-quant.com/llms.txt --- # ML-Quant: Quant research, ranked weekly Every Friday ML-Quant screens every new arXiv, SSRN and RePEc paper on machine learning and quantitative finance, ranks the best 30 per venue with a one-sentence summary and the paper's key figure, and tracks what happens to each pick. 134 issues and 6,576 featured papers so far; 222 of them have since passed 100 citations. ## This week's top picks (issue No. 134, 2026-10-09) - [Agentic AI and Systemic Financial Risk](https://arxiv.org/abs/2610.08806): The study shows that agentic AI systems sharing a foundation model create non-diversifiable common exposure whose systemic risk floor does not shrink as the fleet grows, shifting concern from individual model risk to population-level contagion. - [Quantitative Equity Evolution: Constraints and Alpha Decay](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7566701): Surveys fifty years of quantitative investing as a history of changing implementation boundaries from diversification through machine learning, emphasizing alpha decay and the gap between research and production systems. - [Risk Appetite and Monetary Transmission](https://econpapers.repec.org/RePEc:fip:fedfwp:103796): The research shows Fed policy affects risk asset prices primarily through risk appetite shifts, not interest rates; transmission via risk appetite dwarfs rate-channel effects. - [FactorBench: Benchmarking Automated Factor Mining](https://arxiv.org/abs/2610.06947): A portfolio-aware benchmark comparing five thousand factors from nine automated mining methods across five equity markets finds that no discovery paradigm consistently dominates in signal quality or portfolio performance. - [LLM Factor Discovery and Evidence Scarcity](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7555699): An autonomous agent evolved 940 factors over 17 days and finds that reusing backtest data inflates edge by a quarter to a third and in-sample improvement predicts worse performance. Full issue: https://www.ml-quant.com/issues/2026-10-09/index.md ## What's rising - Housing: 4.6% of this week's 776 new papers, 1.8x its share over the previous 2 weeks (2.6%). - ETFs and funds: 4.4% of this week's 776 new papers, 1.6x its share over the previous 2 weeks (2.8%). - Volatility forecasting: 2.6% of this week's 776 new papers, 1.5x its share over the previous 2 weeks (1.8%). ## GitHub radar: what quant developers starred this week - [jarrodwatts/jev-trader](https://github.com/jarrodwatts/jev-trader) (3 quants): AI trading agent executing trades on Monad blockchain. - [Yijia-Xiao/FinanceHarness](https://github.com/Yijia-Xiao/FinanceHarness) (2 quants): Autonomous financial deep research framework. - [TNT-Likely/PanWatch](https://github.com/TNT-Likely/PanWatch) (2 quants): AI stock monitoring for A-shares, HK and US markets. - [morluto/rea](https://github.com/morluto/rea) (35 quants): Reverse engineer apps and binaries using AI agents. - [storytold/photocraft](https://github.com/storytold/photocraft) (22 quants): Open-source Rust reimplementation of Adobe Photoshop. - [openai/math](https://github.com/openai/math) (21 quants): Mathematics library in Lean. - [Niko1221/Strata](https://github.com/Niko1221/Strata) (13 quants): Run Qwen3.8-Flash on consumer hardware with local APIs. - [tester-army/e2e](https://github.com/tester-army/e2e) (7 quants): End-to-end testing framework for web and mobile apps. - [boykopovar/AnyPS5](https://github.com/boykopovar/AnyPS5) (7 quants): Tool for porting PS5 executables to Linux and Windows. ## We called it: most-cited papers we featured within two weeks of release - [FinGPT: Open-Source Financial Large Language Models](https://arxiv.org/abs/2306.06031): 509 citations, featured 2023-06-14 - [FinMem: A Performance-Enhanced LLM Trading Agent With Layered Memory and Character Design](https://arxiv.org/abs/2311.13743): 266 citations, featured 2023-11-29 - [HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction](https://arxiv.org/abs/2408.04948): 237 citations, featured 2024-08-15 - [TradingAgents: Multi-Agents LLM Financial Trading Framework](http://arxiv.org/abs/2412.20138v1): 234 citations, featured 2025-01-01 - [TKAN: Temporal Kolmogorov-Arnold Networks](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4825654): 191 citations, featured 2024-05-15 - [Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models](https://arxiv.org/abs/2306.12659): 143 citations, featured 2023-06-28 ## Topics - [Crypto & DeFi](https://www.ml-quant.com/topics/crypto-defi/index.md): 303 papers - [LLMs & Text](https://www.ml-quant.com/topics/llms-text/index.md): 584 papers - [Derivatives & Volatility](https://www.ml-quant.com/topics/derivatives-volatility/index.md): 883 papers - [Trading, Microstructure & Execution](https://www.ml-quant.com/topics/trading-microstructure-execution/index.md): 559 papers - [Portfolio & Allocation](https://www.ml-quant.com/topics/portfolio-allocation/index.md): 628 papers - [Risk, Credit & Banking](https://www.ml-quant.com/topics/risk-credit-banking/index.md): 381 papers - [Asset Pricing & Factors](https://www.ml-quant.com/topics/asset-pricing-factors/index.md): 269 papers - [Macro-Finance & Rates](https://www.ml-quant.com/topics/macro-finance-rates/index.md): 283 papers - [Econometrics & Forecasting](https://www.ml-quant.com/topics/econometrics-forecasting/index.md): 315 papers - [ML & AI Methods](https://www.ml-quant.com/topics/ml-ai-methods/index.md): 1135 papers - [Corporate Finance](https://www.ml-quant.com/topics/corporate-finance/index.md): 170 papers - [Other](https://www.ml-quant.com/topics/other/index.md): 1066 papers ## Recent issues - [No. 134: October 2026, Week 2](https://www.ml-quant.com/issues/2026-10-09/index.md) (2026-10-09) - [No. 133: October 2026, Week 1](https://www.ml-quant.com/issues/2026-10-02/index.md) (2026-10-02) - [No. 132: September 2026, Week 4](https://www.ml-quant.com/issues/2026-09-25/index.md) (2026-09-25) - [No. 131: May 2026, Week 3](https://www.ml-quant.com/issues/2026-05-20/index.md) (2026-05-20) - [No. 130: April 2026, Week 3](https://www.ml-quant.com/issues/2026-04-16/index.md) (2026-04-16) - [No. 129: April 2026, Week 1](https://www.ml-quant.com/issues/2026-04-03/index.md) (2026-04-03) ## For agents - Index: https://www.ml-quant.com/llms.txt - API: https://www.ml-quant.com/api/v1/index.json - RSS: https://www.ml-quant.com/feed.xml