Key papers

• Deterministic Policy Gradient for Learning Equilibrium in Time-Inconsistent Control Problems (2026)
  Xin Guo et al.
  4.95
• VAIOM: Continuous-Input, Discrete-Output Decoder-Only Financial Sequence Modeling (2026)
  Yiming Ma et al.
  4.39
• AI Trading: Evaluating Large Language Models for Technical Market Analysis (2026)
  Geofrey Ntale
  3.51
• Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning (2024)
  Maximilian N\"agele et al.
  2.21
• TT-DAC-PS: Twin-Target Deterministic Actor-Critic with Policy Smoothing for Optimal Trade Execution (2026)
  Ilia Zaznov et al.
  1.94
• Multi-Dimensional Behavioral Evaluation of Agentic Stock Prediction Systems Using Large Language Model Judges with Closed-Loop Reinforcement Learning Feedback (2026)
  Mohammad Al Ridhawi et al.
  1.89
• SNAPO: Smooth Neural Adjoint Policy Optimization for Optimal Control via Differentiable Simulation (2026)
  Dmitri Goloubentsev and Natalija Karpichina
  1.89
• Memory-Induced Supra-Competitive Outcomes Between Deep Reinforcement Learning Agents in Optimal Trade Execution (2026)
  Christos Spyridon Koulouris and Carlo Campajola
  1.89
• Reinforcement Learning for Speculative Trading under Exploratory Framework (2026)
  Yun Zhao et al.
  1.83
• Autonomous AI Agents for Option Hedging: Enhancing Financial Stability through Shortfall Aware Reinforcement Learning (2026)
  Minxuan Hu et al.
  1.78
• Variational Quantum Circuit-Based Reinforcement Learning for Dynamic Portfolio Optimization (2026)
  Vincent Gurgul et al.
  1.67
• Continuous-time reinforcement learning for optimal switching over multiple regimes (2025)
  Yijie Huang et al.
  1.61
• Deep reinforcement learning for optimal trading with partial information (2025)
  Andrea Macr\`i et al.
  1.56
• Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy (2025)
  Hongyang Yang et al.
  1.56
• Cryptocurrency Portfolio Management with Reinforcement Learning: Soft Actor--Critic and Deep Deterministic Policy Gradient Algorithms (2025)
  Kamal Paykan (Department of Mathematics et al.
  1.56
• Diffusion-Augmented Reinforcement Learning for Robust Portfolio Optimization under Stress Scenarios (2025)
  Himanshu Choudhary et al.
  1.50
• Application of Deep Reinforcement Learning to At-the-Money S&P 500 Options Hedging (2025)
  Zofia Bracha et al.
  1.50
• Integrating Large Language Models and Reinforcement Learning for Sentiment-Driven Quantitative Trading (2025)
  Wo Long et al.
  1.50
• FinFlowRL: An Imitation-Reinforcement Learning Framework for Adaptive Stochastic Control in Finance (2025)
  Yang Li et al.
  1.50
• News-Aware Direct Reinforcement Trading for Financial Markets (2025)
  Qing-Yu Lan et al.
  1.50
• Right Place, Right Time: Market Simulation-based RL for Execution Optimisation (2025)
  Ollie Olby et al.
  1.50
• FinZero: Launching Multi-modal Financial Time Series Forecast with Large Reasoning Model (2025)
  Yanlong Wang et al.
  1.44
• Comparing Normalization Methods for Portfolio Optimization with Reinforcement Learning (2025)
  Caio de Souza Barbosa Costa and Anna Helena Reali Costa
  1.39
• QTMRL: An Agent for Quantitative Trading Decision-Making Based on Multi-Indicator Guided Reinforcement Learning (2025)
  Jingfeng Pan and Jiahao Chen
  1.39
• Accelerated Portfolio Optimization and Option Pricing with Reinforcement Learning (2025)
  Hadi Keramati and Samaneh Jazayeri
  1.33
• Can Artificial Intelligence Trade the Stock Market? (2025)
  J\k{e}drzej Maskiewicz et al.
  1.28
• Quantum Reinforcement Learning Trading Agent for Sector Rotation in the Taiwan Stock Market (2025)
  Chi-Sheng Chen et al.
  1.28
• Deep Reinforcement Learning Algorithms for Option Hedging (2025)
  Andrei Neagu et al.
  1.17
• Predicting Liquidity-Aware Bond Yields using Causal GANs and Deep Reinforcement Learning with LLM Evaluation (2025)
  Jaskaran Singh Walia et al.
  1.06
• Adaptive Nesterov Accelerated Distributional Deep Hedging for Efficient Volatility Risk Management (2025)
  Lei Zhao et al.
  1.06
• Off-Policy Evaluation and Counterfactual Methods in Dynamic Auction Environments (2025)
  Ritam Guha and Nilavra Pathak
  1.00
• Improving DeFi Accessibility through Efficient Liquidity Provisioning with Deep Reinforcement Learning (2025)
  Haonan Xu and Alessio Brini
  1.00
• Robust Reinforcement Learning with Dynamic Distortion Risk Measures (2024)
  Anthony Coache et al.
  0.83
• Reinforcement Learning for Credit Index Option Hedging (2023)
  Francesco Mandelli et al.
  —
• Applying Reinforcement Learning to Option Pricing and Hedging (2023)
  Zoran Stoiljkovic
  —
• Combining Deep Learning on Order Books with Reinforcement Learning for Profitable Trading (2023)
  Koti S. Jaddu and Paul A. Bilokon
  —
• Onflow: a model free, online portfolio allocation algorithm robust to transaction fees (2023)
  Gabriel Turinici and Pierre Brugiere
  —
• Data-Driven Merton's Strategies via Policy Randomization (2023)
  Min Dai et al.
  —
• CNN-DRL with Shuffled Features in Finance (2024)
  Sina Montazeri et al.
  —
• Modelling crypto markets by multi-agent reinforcement learning (2024)
  Johann Lussange et al.
  —
• Deep Hedging with Market Impact (2024)
  Andrei Neagu and Fr\'ed\'eric Godin and Clarence Simard and Leila Kosseim
  —
• Continuous-time Risk-sensitive Reinforcement Learning via Quadratic Variation Penalty (2024)
  Yanwei Jia
  —
• Markowitz Meets Bellman: Knowledge-distilled Reinforcement Learning for Portfolio Management (2024)
  Gang Hu and Ming Gu
  —
• Reinforcement Learning for Corporate Bond Trading: A Sell Side Perspective (2024)
  Samuel Atkins et al.
  —
• $\text{Alpha}^2$: Discovering Logical Formulaic Alphas using Deep Reinforcement Learning (2024)
  Feng Xu et al.
  —
• Reinforcement Learning Pair Trading: A Dynamic Scaling approach (2024)
  Hongshen Yang et al.
  —
• QuantFactor REINFORCE: Mining Steady Formulaic Alpha Factors with Variance-bounded REINFORCE (2024)
  Junjie Zhao et al.
  —
• A Deep Reinforcement Learning Framework For Financial Portfolio Management (2024)
  Jinyang Li
  —
• Solving The Dynamic Volatility Fitting Problem: A Deep Reinforcement Learning Approach (2024)
  Emmanuel Gnabeyeu and Omar Karkar and Imad Idboufous
  —
• Reinforcement Learning Framework for Quantitative Trading (2024)
  Alhassan S. Yasin and Prabdeep S. Gill
  —
• Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making (2024)
  Jian Guo et al.
  —
• A Review of Reinforcement Learning in Financial Applications (2024)
  Yahui Bai et al.
  —
• Joint Combinatorial Node Selection and Resource Allocations in the Lightning Network using Attention-based Reinforcement Learning (2024)
  Mahdi Salahshour et al.
  —