{"total":86,"rows":[{"id":"2112.04553","title":"Recent Advances in Reinforcement Learning in Finance","created":"2021-12-08","cited_by_count":110,"area":null},{"id":"2401.11641","title":"Revolutionizing Finance with LLMs: An Overview of Applications and Insights","created":"2024-01-22","cited_by_count":90,"area":null},{"id":"2111.09395","title":"FinRL: Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance","created":"2021-11-07","cited_by_count":58,"area":null},{"id":"2106.08900","title":"Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality","created":"2021-06-14","cited_by_count":34,"area":null},{"id":"2305.18901","title":"Policy Optimization for Continuous Reinforcement Learning","created":"2023-05-30","cited_by_count":31,"area":null},{"id":"2103.16409","title":"Deep Hedging of Derivatives Using Reinforcement Learning","created":"2021-03-29","cited_by_count":30,"area":null},{"id":"2110.13287","title":"Towards Realistic Market Simulations: a Generative Adversarial Networks Approach","created":"2021-10-25","cited_by_count":29,"area":null},{"id":"2109.03582","title":"Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes","created":"2021-09-08","cited_by_count":27,"area":null},{"id":"2101.08837","title":"Time-Correlated Sparsification for Communication-Efficient Federated Learning","created":"2021-01-21","cited_by_count":26,"area":null},{"id":"2201.13094","title":"Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer","created":"2022-01-31","cited_by_count":22,"area":null},{"id":"2303.16585","title":"Quantum Deep Hedging","created":"2023-03-29","cited_by_count":22,"area":null},{"id":"2304.05093","title":"Generative modeling for time series via Schr{\\\"o}dinger bridge","created":"2023-04-11","cited_by_count":18,"area":null},{"id":"2112.06823","title":"Multi-Asset Spot and Option Market Simulation","created":"2021-12-13","cited_by_count":17,"area":null},{"id":"2206.05134","title":"Distributionally Robust End-to-End Portfolio Construction","created":"2022-06-10","cited_by_count":17,"area":null},{"id":"2207.07467","title":"Deep Hedging: Continuous Reinforcement Learning for Hedging of General Portfolios across Multiple Risk Aversions","created":"2022-07-15","cited_by_count":13,"area":null},{"id":"2111.07844","title":"Deep Hedging: Learning to Remove the Drift under Trading Frictions with Minimal Equivalent Near-Martingale Measures","created":"2021-11-15","cited_by_count":11,"area":null},{"id":"2209.10166","title":"Chaotic Hedging with Iterated Integrals and Neural Networks","created":"2022-09-21","cited_by_count":10,"area":null},{"id":"2210.10443","title":"Deep neural network expressivity for optimal stopping problems","created":"2022-10-19","cited_by_count":9,"area":null},{"id":"2303.15216","title":"Robust Risk-Aware Option Hedging","created":"2023-03-27","cited_by_count":9,"area":null},{"id":"2312.11797","title":"Data-Driven Merton's Strategies via Policy Randomization","created":"2023-12-19","cited_by_count":8,"area":null},{"id":"2105.09264","title":"Robo-Advising: Enhancing Investment with Inverse Optimization and Deep Reinforcement Learning","created":"2021-05-19","cited_by_count":7,"area":null},{"id":"2110.02742","title":"A Quantum Generative Adversarial Network for distributions","created":"2021-10-04","cited_by_count":7,"area":null},{"id":"2310.13369","title":"SigFormer: Signature Transformers for Deep Hedging","created":"2023-10-20","cited_by_count":7,"area":null},{"id":"2408.03320","title":"Hedge Fund Portfolio Construction Using PolyModel Theory and iTransformer","created":"2024-08-06","cited_by_count":7,"area":null},{"id":"2508.14995","title":"Generative Neural Operators of Log-Complexity Can Simultaneously Solve Infinitely Many Convex Programs","created":"2025-08-20","cited_by_count":7,"area":null},{"id":"2103.11435","title":"A deep learning approach to data-driven model-free pricing and to martingale optimal transport","created":"2021-03-21","cited_by_count":6,"area":null},{"id":"2110.04752","title":"How Robust are Limit Order Book Representations under Data Perturbation?","created":"2021-10-10","cited_by_count":6,"area":null},{"id":"2204.11231","title":"Do ReLU Networks Have An Edge When Approximating Compactly-Supported Functions?","created":"2022-04-24","cited_by_count":6,"area":null},{"id":"2301.04020","title":"Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligence","created":"2022-12-13","cited_by_count":6,"area":null},{"id":"2303.00859","title":"FuNVol: A Multi-Asset Implied Volatility Market Simulator using Functional Principal Components and Neural SDEs","created":"2023-03-01","cited_by_count":6,"area":null},{"id":"2410.22568","title":"Fast Deep Hedging with Second-Order Optimization","created":"2024-10-29","cited_by_count":6,"area":null},{"id":"2202.11606","title":"Pricing options on flow forwards by neural networks in Hilbert space","created":"2022-02-17","cited_by_count":5,"area":null},{"id":"2210.13193","title":"Langevin dynamics based algorithm e-TH$\\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient","created":"2022-10-24","cited_by_count":5,"area":null},{"id":"2307.13217","title":"Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling","created":"2023-07-25","cited_by_count":5,"area":null},{"id":"2102.05313","title":"Conditional Loss and Deep Euler Scheme for Time Series Generation","created":"2021-02-10","cited_by_count":4,"area":null},{"id":"2203.03179","title":"Detecting data-driven robust statistical arbitrage strategies with deep neural networks","created":"2022-03-07","cited_by_count":4,"area":null},{"id":"2307.04957","title":"Reinforcement Learning with Non-Cumulative Objective","created":"2023-07-11","cited_by_count":4,"area":null},{"id":"2208.07158","title":"Asset Allocation: From Markowitz to Deep Reinforcement Learning","created":"2022-07-14","cited_by_count":3,"area":null},{"id":"2307.07657","title":"Machine learning for option pricing: an empirical investigation of network architectures","created":"2023-07-14","cited_by_count":3,"area":null},{"id":"2509.12753","title":"DeltaHedge: A Multi-Agent Framework for Portfolio Options Optimization","created":"2025-09-16","cited_by_count":3,"area":null},{"id":"2102.06274","title":"Hedging of Financial Derivative Contracts via Monte Carlo Tree Search","created":"2021-02-11","cited_by_count":2,"area":null},{"id":"2106.04114","title":"Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction","created":"2021-06-08","cited_by_count":2,"area":null},{"id":"2202.07148","title":"Estimating risks of option books using neural-SDE market models","created":"2022-02-15","cited_by_count":2,"area":null},{"id":"2202.13996","title":"Risk-Neutral Market Simulation","created":"2022-02-28","cited_by_count":2,"area":null},{"id":"2205.15991","title":"Hedging option books using neural-SDE market models","created":"2022-05-31","cited_by_count":2,"area":null},{"id":"2212.12018","title":"Langevin algorithms for Markovian Neural Networks and Deep Stochastic control","created":"2022-12-22","cited_by_count":2,"area":null},{"id":"2407.21138","title":"Enhancing Deep Hedging of Options with Implied Volatility Surface Feedback Information","created":"2024-07-30","cited_by_count":2,"area":null},{"id":"2407.21791","title":"Deep Learning for Options Trading: An End-To-End Approach","created":"2024-07-31","cited_by_count":2,"area":null},{"id":"2412.11257","title":"Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variate","created":"2024-12-15","cited_by_count":2,"area":null},{"id":"2505.23215","title":"A Jump-Diffusion Framework for Irregular Time Series Generation","created":"2025-05-29","cited_by_count":2,"area":null},{"id":"2508.14757","title":"Distributional Adversarial Attacks and Training in Deep Hedging","created":"2025-08-20","cited_by_count":2,"area":null},{"id":"2110.15133","title":"Deep Calibration of Interest Rates Model","created":"2021-10-28","cited_by_count":1,"area":null},{"id":"2111.03477","title":"Data-driven Hedging of Stock Index Options via Deep Learning","created":"2021-11-05","cited_by_count":1,"area":null},{"id":"2307.12703","title":"Policy Gradient Optimal Correlation Search for Variance Reduction in Monte Carlo simulation and Maximum Optimal Transport","created":"2023-07-24","cited_by_count":1,"area":null},{"id":"2310.04336","title":"Applying Reinforcement Learning to Option Pricing and Hedging","created":"2023-10-06","cited_by_count":1,"area":null},{"id":"2407.19367","title":"Enhancing Black-Scholes Delta Hedging via Deep Learning","created":"2024-07-28","cited_by_count":1,"area":null},{"id":"2411.15002","title":"A New Way: Kronecker-Factored Approximate Curvature Deep Hedging and its Benefits","created":"2024-11-22","cited_by_count":1,"area":null},{"id":"2506.07299","title":"Uncertainty-Aware Strategies: A Model-Agnostic Framework for Robust Financial Optimization through Subsampling","created":"2025-06-08","cited_by_count":1,"area":null},{"id":"2506.13113","title":"Dynamic Reinsurance Treaty Bidding via Multi-Agent Reinforcement Learning","created":"2025-06-16","cited_by_count":1,"area":null},{"id":"2510.01874","title":"Deep Hedging Under Non-Convexity: Limitations and a Case for AlphaZero","created":"2025-10-02","cited_by_count":1,"area":null},{"id":"2606.05138","title":"Generating Financial Time Series by Matching Random Convolutional Features","created":"2026-06-03","cited_by_count":1,"area":null},{"id":"2608.12587","title":"DYSANOS Generative Dynamic Smooth Arbitrage-free Non-parametric Option Surfaces","created":"2026-08-12","cited_by_count":1,"area":null},{"id":"2103.11948","title":"Deep Hedging: Learning Risk-Neutral Implied Volatility Dynamics","created":"2021-03-22","cited_by_count":0,"area":null},{"id":"2307.09844","title":"Reinforcement Learning for Credit Index Option Hedging","created":"2023-07-19","cited_by_count":0,"area":null},{"id":"2310.02402","title":"On the Parallel Complexity of Multilevel Monte Carlo in Stochastic Gradient Descent","created":"2023-10-03","cited_by_count":0,"area":null},{"id":"2404.09462","title":"Experimental Analysis of Deep Hedging Using Artificial Market Simulations for Underlying Asset Simulators","created":"2024-04-15","cited_by_count":0,"area":null},{"id":"2502.17757","title":"Robust and Efficient Deep Hedging via Linearized Objective Neural Network","created":"2025-02-25","cited_by_count":0,"area":null},{"id":"2503.13056","title":"Deep Hedging of Green PPAs in Electricity Markets","created":"2025-03-17","cited_by_count":0,"area":null},{"id":"2504.04300","title":"Generative Market Equilibrium Models with Stable Adversarial Learning via Reinforcement","created":"2025-04-05","cited_by_count":0,"area":null},{"id":"2505.03789","title":"A new architecture of high-order deep neural networks that learn martingales","created":"2025-05-01","cited_by_count":0,"area":null},{"id":"2505.05121","title":"Error Analysis of Deep PDE Solvers for Option Pricing","created":"2025-05-08","cited_by_count":0,"area":null},{"id":"2508.16001","title":"Mean-Field Generalisation Bounds for Learning Controls in Stochastic Environments","created":"2025-08-21","cited_by_count":0,"area":null},{"id":"2510.03129","title":"Signature-Informed Transformer for Asset Allocation","created":"2025-10-03","cited_by_count":0,"area":null},{"id":"2510.16938","title":"A Topological Approach to Parameterizing Deep Hedging Networks","created":"2025-10-19","cited_by_count":0,"area":null},{"id":"2510.24074","title":"Deep Learning-Enhanced Calibration of the Heston Model: A Unified Framework","created":"2025-10-28","cited_by_count":0,"area":null},{"id":"2511.06451","title":"A Risk-Neutral Neural Operator for Arbitrage-Free SPX-VIX Term Structures","created":"2025-11-09","cited_by_count":0,"area":null},{"id":"2511.20837","title":"Constrained deep learning for pricing and hedging european options in incomplete markets","created":"2025-11-25","cited_by_count":0,"area":null},{"id":"2512.11530","title":"Parametric Numerical Integration with (Differential) Machine Learning","created":"2025-12-12","cited_by_count":0,"area":null},{"id":"2604.21993","title":"When Quotes Crumble: Detecting Transient Mechanical Liquidity Erosion in Limit Order Books","created":"2026-04-23","cited_by_count":0,"area":null},{"id":"2605.13998","title":"Synthetic American Option Pricing via Jump-HMM-Driven Heston Implied Volatility","created":"2026-05-13","cited_by_count":0,"area":null},{"id":"2605.27113","title":"High-Quality Synthetic Financial Time-Series using a GAN-Diffusion Framework","created":"2026-05-26","cited_by_count":0,"area":null},{"id":"2606.17065","title":"PIVOT: Bridging Black-Scholes Implied-Volatility and Price Objectives via Differentiable J\\\"ackel Operator","created":"2026-06-04","cited_by_count":0,"area":null},{"id":"2608.02343","title":"Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection","created":"2026-08-03","cited_by_count":0,"area":null},{"id":"2608.04832","title":"Robust Control under Stationary Ambiguity","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2609.33767","title":"Taming the Greeks: Option Portfolios with Inductive Biases","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2609.34474","title":"Deep kernel hedging","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}