Cover Image

Finance-Informed Neural Network: Learning the Geometry of Option Pricing

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Aboussalah, Amine M., Li, Xuanze, Chi, Cheng, Patel, Raj
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computational Finance
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Neural Network Learning of Black-Scholes Equation for Option Pricing
by: Santos, Daniel de Souza, et al.
Published: (2024)

Quantum-Inspired Tensor Neural Networks for Option Pricing
by: Patel, Raj G., et al.
Published: (2022)

Neural Term Structure of Additive Process for Option Pricing
by: Lin, Jimin, et al.
Published: (2024)

Pricing American Options using Machine Learning Algorithms
by: Djagba, Prudence, et al.
Published: (2024)

Application of Tensor Neural Networks to Pricing Bermudan Swaptions
by: Patel, Raj G., et al.
Published: (2023)

A Market-Rule-Informed Neural Network for Efficient Imbalance Electricity Price Forecasting
by: Yu, Runyao, et al.
Published: (2026)

Synthetic American Option Pricing via Jump-HMM-Driven Heston Implied Volatility
by: Sun, Julia, et al.
Published: (2026)

Accelerated Portfolio Optimization and Option Pricing with Reinforcement Learning
by: Keramati, Hadi, et al.
Published: (2025)

MLP, XGBoost, KAN, TDNN, and LSTM-GRU Hybrid RNN with Attention for SPX and NDX European Call Option Pricing
by: Ter-Avanesov, Boris, et al.
Published: (2024)

Predicting Price Movements in High-Frequency Financial Data with Spiking Neural Networks
by: Ezinwoke, Brian, et al.
Published: (2025)

Hidformer: Transformer-Style Neural Network in Stock Price Forecasting
by: Szydłowski, Kamil Ł., et al.
Published: (2024)

GARCH-Informed Neural Networks for Volatility Prediction in Financial Markets
by: Xu, Zeda, et al.
Published: (2024)

Machine Learning vs. Randomness: Challenges in Predicting Binary Options Movements
by: Arantes, Gabriel M., et al.
Published: (2025)

Geometry-Induced Long-Range Correlations in Recurrent Neural Network Quantum States
by: Ayub, Asif Bin, et al.
Published: (2026)

Mathematics of Differential Machine Learning in Derivative Pricing and Hedging
by: Gomes, Pedro Duarte
Published: (2024)

Physics-Informed Neural Networks for Shell Structures
by: Bastek, Jan-Hendrik, et al.
Published: (2022)

Error Propagation in Dynamic Programming: From Stochastic Control to Option Pricing
by: Della Vecchia, Andrea, et al.
Published: (2025)

Regret-Optimal Federated Transfer Learning for Kernel Regression with Applications in American Option Pricing
by: Yang, Xuwei, et al.
Published: (2023)

Error Analysis of Deep PDE Solvers for Option Pricing
by: Rou, Jasper
Published: (2025)

Shallow Representation of Option Implied Information
by: Lin, Jimin
Published: (2026)

Deep Learning vs. Black-Scholes: Option Pricing Performance on Brazilian Petrobras Stocks
by: Gueiros, Joao Felipe, et al.
Published: (2025)

KANHedge: Efficient Hedging of High-Dimensional Options Using Kolmogorov-Arnold Network-Based BSDE Solver
by: Handal, Rushikesh, et al.
Published: (2026)

STN-GPR: A Singularity Tensor Network Framework for Efficient Option Pricing
by: Gribben, Dominic, et al.
Published: (2026)

Enhancing Price Prediction in Cryptocurrency Using Transformer Neural Network and Technical Indicators
by: Khaniki, Mohammad Ali Labbaf, et al.
Published: (2024)

American Call Options Pricing With Modular Neural Networks
by: Unnikrishnan, Ananya
Published: (2024)

DeepSVM: Learning Stochastic Volatility Models with Physics-Informed Deep Operator Networks
by: Malandain, Kieran A., et al.
Published: (2025)

CNN-DRL with Shuffled Features in Finance
by: Montazeri, Sina, et al.
Published: (2024)

Quantum Adaptive Self-Attention for Financial Rebalancing: An Empirical Study on Automated Market Makers in Decentralized Finance
by: Chen, Chi-Sheng, et al.
Published: (2025)

Gradient Reduction Convolutional Neural Network Policy for Financial Deep Reinforcement Learning
by: Montazeri, Sina, et al.
Published: (2024)

Scale-PINN: Learning Efficient Physics-Informed Neural Networks Through Sequential Correction
by: Chiu, Pao-Hsiung, et al.
Published: (2026)

Deep Learning-Based Electricity Price Forecast for Virtual Bidding in Wholesale Electricity Market
by: Wang, Xuesong, et al.
Published: (2024)

Beyond the Black Box: Interpretability of LLMs in Finance
by: Tatsat, Hariom, et al.
Published: (2025)

Feature Mapping in Physics-Informed Neural Networks (PINNs)
by: Zeng, Chengxi, et al.
Published: (2024)

Multimodal Stock Price Prediction: A Case Study of the Russian Securities Market
by: Khubiev, Kasymkhan, et al.
Published: (2025)

UAMM: Price-oracle based Automated Market Maker
by: Im, Daniel Jiwoong, et al.
Published: (2023)

Application of Deep Reinforcement Learning to At-the-Money S&P 500 Options Hedging
by: Bracha, Zofia, et al.
Published: (2025)

PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks
by: Zhao, Zhiyuan, et al.
Published: (2023)

Chaotic Hedging with Iterated Integrals and Neural Networks
by: Neufeld, Ariel, et al.
Published: (2022)

Evolutionary Optimization of Physics-Informed Neural Networks: Evo-PINN Frontiers and Opportunities
by: Wong, Jian Cheng, et al.
Published: (2025)

Stock Price Prediction and Traditional Models: An Approach to Achieve Short-, Medium- and Long-Term Goals
by: Alamu, Opeyemi Sheu, et al.
Published: (2024)