Quantitative Finance

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Overview

Quantitative finance applies mathematical and computational methods to asset pricing, forecasting, portfolio allocation, risk measurement, derivatives, and market microstructure. Common approaches include factor models, econometric time-series methods, deep learning, graph models, and reinforcement learning, alongside tools such as stochastic volatility models and no-arbitrage constraints. Newer work also uses generative models and LLM agents to discover trading signals, simulate markets, and automate research, with evaluation spanning equity panels, options, order books, and portfolio backtests. A central challenge is turning predictive gains into reliable returns after transaction costs and across changing regimes, while preventing leakage and backtest overfitting; simpler econometric baselines often remain difficult to beat.

Latest papers

CardsList

192 papers30 papers in the last four weeks, up 58% on the four weeks before. 0.2% of all new papers.

  1. Quant-Arena: Benchmarking LLM Agents for Quantitative Trading Research

    Oct 21, 2026Houde Qian, Zheng Jiang, Wenyi Li +9Financial Language Model EvaluationAlgorithmic Trading

    Navers Lab, Einsia.AI

  2. Understanding the Inner Workings of a State-Space Foundation Model for Limit Order Books

    Oct 20, 2026Valentin Mohl, Alexandre Bismuth, Aramis Marti-Shahandeh +6Limit Order Book ModelingState Representation Learning

    British Open-ended Learning and Discovery Lab (BOLD), Department of Computer Science, University of Oxford, Oxford, United Kingdom · Harvard University, Cambridge, MA, United States · British Open-ended Learning and Discovery Lab (BOLD), Department of Engineering Science, University of Oxford, Oxford, United Kingdom +3

  3. Deep catastrophic-risk-aware reinforcement learning

    Oct 19, 2026Carlos Octavio Pérez Mendoza, Frédéric GodinRisk-Sensitive RLConditional Value-at-Risk

    Concordia University, Department of Mathematics and Statistics, Montréal, Canada · Quantact Laboratory, Centre de Recherches Mathématiques, Montréal, Canada

  4. Arbitrage-Free Implied Volatility Surface Reconstruction via Additive Martingales

    Oct 19, 2026Haochen Luo, Sifan Lin, Xiaolong Luo +3Quantitative Finance

    City University of Hong Kong · Shanghai University of Finance and Economics

  5. Adversarial Post-Training of Foundation Models for High-Frequency Trading

    Oct 19, 2026Alexandre Bismuth, Kang Li, Aramis Marti-Shahandeh +3Limit Order Book ModelingAdversarial Training

    British Open-ended Learning and Discovery Lab (BOLD), Department of Computer Science, University of Oxford, Oxford, United Kingdom · Harvard University, Cambridge, MA, United States · British Open-ended Learning and Discovery Lab (BOLD), Department of Statistics, University of Oxford, Oxford, United Kingdom +1

  6. StochLOB: Heavy-Tailed Score Matching for Robust Limit Order Book Trend Prediction

    Oct 15, 2026Arshia Abolghasemi, Seyed Reza Tavakoli, Parsa Naderi +7Limit Order Book ForecastingScore Matching

    Dataism Laboratory for Quantitative Finance · Sharif University of Technology · Amirkabir University of Technology +3

  7. What Do Foundation Models for Market Microstructure Learn? A Controlled Study with Synthetic Limit Order Books

    Oct 14, 2026Fernando AceroLimit Order Book ModelingTime-Series Foundation Models

    J.P. Morgan QTR AI Research, United Kingdom

  8. Beyond Time Induction: Structured Conditional Neural Solvers for Parametric Stochastic-Volatility Pricing

    Oct 13, 2026Jose Miguel Lara Rangel, Mixtli Vazquez MendozaNeural PDE SolversPhysics-Informed ML

    University College London, UK · Aicraft, Mexico

  9. When and How Order-Flow Interventions Work After Dealers Adapt

    Oct 13, 2026Guanghao Wu, Zhuo Cai, Zhidong Li +1Quantitative FinanceAlgorithmic Trading

    University of Technology Sydney Sydney, NSW, Australia

  10. EvoQuantLab: Training-Free Dual-Loop Evolution for Auditable Quantitative Research

    Oct 12, 2026Haolin Yang, Zhiqiang Qian, Chutian Chen +7Alpha Factor DiscoveryQuantitative Finance

    The Hong Kong University of Science and Technology · Microsoft · Tsinghua University +1

  11. AlphaPilot: Multi-Turn Tool-Using LLM Agents for Adaptive Alpha Mining with Reinforcement Learning

    Oct 11, 2026Peiqi Jiang, Fan Zhang, Xin Xu +2Alpha Factor DiscoveryQuantitative Finance

    Department of Mathematics, Hong Kong University of Science and Technology

  12. AlphaRLM: Aligning Language Models for Literature-Grounded Symbolic Factor Discovery

    Oct 10, 2026Jie Huang, Yuecheng Hong, Yao Chen +6Quantitative FinanceAlgorithmic Trading

    Harbin Institute of Technology · Independent Researcher · University of Science and Technology of China

  13. Exact Phase-Type Point Processes for Certified Measurement and Prediction of Event Streams

    Oct 10, 2026Sayak DuttaHawkes ProcessesTemporal Point Processes

  14. CorrFlow: Exact and Permutation-Equivariant Flow Matching on the Correlation Elliptope

    Oct 9, 2026Gautier MartiPermutation-Equivariant Neural NetworksConstrained Generative Modeling

    Abu Dhabi Investment Authority (ADIA), Abu Dhabi, United Arab Emirates

  15. L0L_0 Feature Selection via Monte Carlo Tree Search in High-Dimensional Financial Regression

    Oct 9, 2026Cameron Mouangue, Tristan CazenaveFeature SelectionQuantitative Finance

    LAMSADE, Université Paris Dauphine-PSL, CNRS Paris, France

  16. Market Impact Estimation via Causal Foundation Models

    Oct 8, 2026Dennis Thumm, Ying ChenQuantitative FinanceAlgorithmic Trading

    National University of Singapore Singapore, Singapore

  17. SOTA: Stock Options Trading Agents Guided by Option-Implied Return Distributions

    Oct 7, 2026Yizhen Xie, Mengyang LiuAlgorithmic TradingQuantitative Finance

    Carnegie Mellon University · Amazon

  18. Q-PhotoMarket: A Design Space Exploration Framework for Photonic Hybrid Quantum Neural Networks in Financial Market Prediction

    Oct 7, 2026Alberto Marchisio, Hanzalah Mohamed Siraj, Muhammad Kashif +2Quantum Neural NetworksHybrid Quantum-Classical ML

    eBrain Lab, Division of Engineering, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, UAE · Center for Quantum and Topological Systems, NYUAD Research Institute, New York University Abu Dhabi, UAE · SDU Microelectronics, Institute of Mechanical and Electrical Engineering, University of Southern Denmark, Odense, Denmark +1

  19. Residual Learning in Empirical Asset Pricing

    Oct 7, 2026Dexin Peng, Xiaoyu WangQuantitative FinanceResidual Learning

    FinTech Thrust, Hong Kong University of Science and Technology (Guangzhou)

  20. On the Boundary of Admission Gates: An Injected-Truth Study of Falsification-First Selection in Quantitative Strategy Research

    Oct 6, 2026Tianlun ZhengQuantitative FinanceFDR Control

    Fudan University

  21. Adversarial Training for Deep Hedging in Nonstationary Markets

    Oct 5, 2026Philipp J. Schneider, Lukas Looser, Antoine Garin +2Adversarial TrainingQuantitative Finance

    Risk Analytics and Optimization Chair, EPFL, Lausanne, Switzerland · University of Waterloo, Waterloo, Canada

  22. STOCK-JEPA: Prior-Anchored Latent Revision Representation Learning in Equity Markets

    Oct 4, 2026Yizhi Luo, Jiahe Yi, Jianhui Zhang +1Quantitative FinanceJoint-Embedding Predictive Architecture

    The Hong Kong University of Science and Technology · Shanghai Jiaotong University · Beijing Zhongguancun Academy

  23. How Execution Assumptions Change Short-Horizon Sharpe Rankings: Evidence from a Synthetic Trading Benchmark

    Oct 4, 2026Weicheng XueQuantitative FinanceLLM Agent Evaluation

    Virginia Tech

  24. FactorBench: A Portfolio-Aware Benchmark for Automated Factor Mining

    Oct 3, 2026Zhuohan Wang, Carmine VentreAlpha Factor DiscoveryQuantitative Finance

    Department of Informatics King’s College London London, UK

  25. BAIBAICHUCHU at the NTCIR-19 FinArg-3 Task: When Is Maximum Possible Profit Predictable from Investor Text?

    Oct 2, 2026Zong-Han Bai, Po-Yen ChuFinancial ForecastingLearning to Rank

    National Tsing Hua University Hsinchu, Taiwan · Stanford University Stanford, CA, USA

  26. Expected Utility Regret Rule: Minimax and Bayes Optimal Portfolio Choice

    Oct 1, 2026Masahiro KatoPortfolio OptimizationQuantitative Finance

    The University of Tokyo

  27. Say, Echo, Do: Strategic Narratives and Revealed Positioning in Financial Markets

    Sep 29, 2026Ali Atiah AlzahraniQuantitative FinanceFinancial Forecasting

    Riyadh, Saudi Arabia

  28. Retrieval-Augmented Diffusion Modeling for Stochastic Discount Factor Portfolios

    Sep 28, 2026Kelvin J. L. Koa, Xinyang Li, Ke-Wei HuangQuantitative FinancePortfolio Optimization

    National University of Singapore Asian Institute of Digital Finance

  29. Deep kernel hedging

    Sep 28, 2026Jean-Loup Dupret, Donatien Hainaut, Edouard MotteDeep Kernel LearningQuantitative Finance

    University of Amsterdam, Amsterdam School of Economics · ETH Zurich, Department of Mathematics, RiskLab · Université Catholique de Louvain, LIDAM–ISBA

  30. AlphaPareto: Formulaic Alpha Discovery with LLM-Guided Multi-Objective Reinforcement Learning

    Sep 28, 2026Yingbo Zhao, Zeyu Yang, Zhoufan ZhuMulti-Objective Reinforcement LearningNon-Stationary RL

    School of Economics Xiamen University Fujian, China · Paula and Gregory Chow Institute for Studies in Economics Xiamen University Fujian, China · School of Economics & Wang Yanan Institute for Studies in Economics Xiamen University Fujian, China