mlsanityData to 7 Oct 2026

Neural networks for option pricing and hedging: a literature review

arXiv 1911.05620 ↗First posted 13 Nov 2019q-fin.CP cs.LG q-fin.RMcited by 38

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Abstract (arXiv)

Neural networks have been used as a nonparametric method for option pricing and hedging since the early 1990s. Far over a hundred papers have been published on this topic. This note intends to provide a comprehensive review. Papers are compared in terms of input features, output variables, benchmark models, performance measures, data partition methods, and underlying assets. Furthermore, related work and regularisation techniques are discussed.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Nov 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 6; 2023: 5; 2024: 6; 2025: 9; 2026: 3.

38 papers.

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  1. 2021AI in Finance: Challenges, Techniques and Opportunitiescited by 81
  2. 2021Exponential Convergence of Deep Operator Networks for Elliptic Partial Differential Equationscited by 44
  3. 2021Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionalitycited by 34
  4. 2021Multi-Asset Spot and Option Market Simulationcited by 17
  5. 2024Non-convergence of Adam and other adaptive stochastic gradient descent optimization methods for non-vanishing learning ratescited by 14
  6. 2022Chaotic Hedging with Iterated Integrals and Neural Networkscited by 10
  7. 2022Deep neural network expressivity for optimal stopping problemscited by 9
  8. 2023Robust Risk-Aware Option Hedgingcited by 9
  9. 2021A Quantum Generative Adversarial Network for distributionscited by 7
  10. 2021Backdoor Attack and Defense for Deep Regressioncited by 6
  11. 2024An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learningcited by 6
  12. 2024Fast Deep Hedging with Second-Order Optimizationcited by 6
26 more
  1. 2025Non-convergence to the optimal risk for Adam and stochastic gradient descent optimization in the training of deep neural networkscited by 6
  2. 2021Interpretability in deep learning for finance: a case study for the Heston modelcited by 5
  3. 2022Pricing options on flow forwards by neural networks in Hilbert spacecited by 5
  4. 2025Applying Informer for Option Pricing: A Transformer-Based Approachcited by 5
  5. 2022Solving the optimal stopping problem with reinforcement learning: an application in financial option exercisecited by 3
  6. 2023Machine learning for option pricing: an empirical investigation of network architecturescited by 3
  7. 2022Hedging option books using neural-SDE market modelscited by 2
  8. 2024Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variatecited by 2
  9. 2025Hedging with memory: shallow and deep learning with signaturescited by 2
  10. 2025Distributional Adversarial Attacks and Training in Deep Hedgingcited by 2
  11. 2023Deep Calibration With Artificial Neural Network: A Performance Comparison on Option Pricing Modelscited by 1
  12. 2024Limit Order Book Simulation and Trade Evaluation with K-Nearest-Neighbor Resamplingcited by 1
  13. 2021Advances in Electron Microscopy with Deep Learningcited by 0
  14. 2021Trading Signals In VIX Futurescited by 0
  15. 2022Beyond Surrogate Modeling: Learning the Local Volatility Via Shape Constraintscited by 0
  16. 2023Pricing European Options with Google AutoML, TensorFlow, and XGBoostcited by 0
  17. 2023American Option Pricing using Self-Attention GRU and Shapley Value Interpretationcited by 0
  18. 2024Experimental Analysis of Deep Hedging Using Artificial Market Simulations for Underlying Asset Simulatorscited by 0
  19. 2025Robust and Efficient Deep Hedging via Linearized Objective Neural Networkcited by 0
  20. 2025Deep Learning vs. Black-Scholes: Option Pricing Performance on Brazilian Petrobras Stockscited by 0
  21. 2025Option Pricing Using Ensemble Learningcited by 0
  22. 2025Application of Deep Reinforcement Learning to At-the-Money S&P 500 Options Hedgingcited by 0
  23. 2025Deep Learning-Enhanced Calibration of the Heston Model: A Unified Frameworkcited by 0
  24. 2026Inverse Learning of Latent Risk-Neutral Densities from Irregular Option Quotescited by 0
  25. 2026Asymptotically-informed neural networks for Black-Scholes implied volatility computationcited by 0
  26. 2026Learning to Detect Symbolic Failure: Machine Learning and the Limits of Black-Scholescited by 0