:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Kichler, Neil, Afghan, Sher, Naumann, Uwe
Format:	Preprint
Publié:	2023
Sujets:	Machine Learning Computational Finance
Accès en ligne:	https://arxiv.org/abs/2312.03510
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Matrix-Free Jacobian Chaining
par: Naumann, Uwe
Publié: (2024)

Seasons's Greetings by AD
par: Naumann, Uwe
Publié: (2023)

Differential Inversion of the Implicit Euler Method: Symbolic Analysis
par: Naumann, Uwe
Publié: (2024)

On the Detection of Internal Defects in Structured Media
par: Ong, Bryl Nico M., et autres
Publié: (2025)

Exploiting Supply Chain Interdependencies for Stock Return Prediction: A Full-State Graph Convolutional LSTM
par: Liu, Chang
Publié: (2023)

Automated regime classification in multidimensional time series data using sliced Wasserstein k-means clustering
par: Luan, Qinmeng, et autres
Publié: (2023)

A three-step machine learning approach to predict market bubbles with financial news
par: Atsiwo, Abraham
Publié: (2025)

Transfer Learning Across Fixed-Income Product Classes
par: Camenzind, Nicolas, et autres
Publié: (2025)

Leave-one-out least squares Monte Carlo algorithm for pricing Bermudan options
par: Woo, Jeechul, et autres
Publié: (2018)

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

Stock Price Prediction and Traditional Models: An Approach to Achieve Short-, Medium- and Long-Term Goals
par: Alamu, Opeyemi Sheu, et autres
Publié: (2024)

Enhancing Black-Scholes Delta Hedging via Deep Learning
par: Qiao, Chunhui, et autres
Publié: (2024)

Nansde-net: A neural sde framework for generating time series with memory
par: Ozai, Hiromu, et autres
Publié: (2026)

MCI-GRU: Stock Prediction Model Based on Multi-Head Cross-Attention and Improved GRU
par: Zhu, Peng, et autres
Publié: (2024)

Predictive Accuracy versus Interpretability in Energy Markets: A Copula-Enhanced TVP-SVAR Analysis
par: Pokou, Fredy, et autres
Publié: (2026)

Multimodal Stock Price Prediction: A Case Study of the Russian Securities Market
par: Khubiev, Kasymkhan, et autres
Publié: (2025)

Non-Parametric Estimation of Multi-dimensional Marked Hawkes Processes
par: Joseph, Sobin, et autres
Publié: (2024)

Quantifying Cryptocurrency Unpredictability: A Comprehensive Study of Complexity and Forecasting
par: Puoti, Francesco, et autres
Publié: (2025)

GenCP: Towards Generative Modeling Paradigm of Coupled Physics
par: Gao, Tianrun, et autres
Publié: (2026)

UAMM: Price-oracle based Automated Market Maker
par: Im, Daniel Jiwoong, et autres
Publié: (2023)

Financial Wind Tunnel: A Retrieval-Augmented Market Simulator
par: Cao, Bokai, et autres
Publié: (2025)

Optimizing Portfolio Management and Risk Assessment in Digital Assets Using Deep Learning for Predictive Analysis
par: Cheng, Qishuo, et autres
Publié: (2024)

Decoding RWA Tokenized U.S. Treasuries: Functional Dissection and Address Role Inference
par: Luo, Junliang, et autres
Publié: (2025)

Diffusion-Augmented Reinforcement Learning for Robust Portfolio Optimization under Stress Scenarios
par: Choudhary, Himanshu, et autres
Publié: (2025)

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

Towards Financially Inclusive Credit Products Through Financial Time Series Clustering
par: Bester, Tristan, et autres
Publié: (2024)

Towards Causal Market Simulators
par: Thumm, Dennis, et autres
Publié: (2025)

Chaotic Hedging with Iterated Integrals and Neural Networks
par: Neufeld, Ariel, et autres
Publié: (2022)

Towards Foundation Model for Chemical Reactor Modeling: Meta-Learning with Physics-Informed Adaptation
par: Wang, Zihao, et autres
Publié: (2024)

Toward Developing Machine-Learning-Aided Tools for the Thermomechanical Monitoring of Nuclear Reactor Components
par: Machado, Luiz Aldeia, et autres
Publié: (2025)

Towards a Generalizable AI for Materials Discovery: Validation through Immersion Coolant Screening
par: Kim, Hyunseung, et autres
Publié: (2025)

Physics-Informed Machine Learning Towards A Real-Time Spacecraft Thermal Simulator
par: Oddiraju, Manaswin, et autres
Publié: (2024)

Towards a Real-Time Simulation of Elastoplastic Deformation Using Multi-Task Neural Networks
par: Schmeitz, Ruben, et autres
Publié: (2024)

AhmedML: High-Fidelity Computational Fluid Dynamics Dataset for Incompressible, Low-Speed Bluff Body Aerodynamics
par: Ashton, Neil, et autres
Publié: (2024)

DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting
par: Zhao, Lifan, et autres
Publié: (2023)

FairTune: A Bias-Aware Fine-Tuning Framework Towards Fair Heart Rate Prediction from PPG
par: Panchumarthi, Lovely Yeswanth, et autres
Publié: (2025)

Peer-induced Fairness: A Causal Approach for Algorithmic Fairness Auditing
par: Fang, Shiqi, et autres
Publié: (2024)

Toward AI-Driven Digital Twins for Metropolitan Floods: A Conditional Latent Dynamics Network Surrogate of the Shallow Water Equations
par: Si, Phillip, et autres
Publié: (2026)

Toward data-driven research: preliminary study to predict surface roughness in material extrusion using previously published data with Machine Learning
par: García-Martínez, Fátima, et autres
Publié: (2024)

SusGen-GPT: A Data-Centric LLM for Financial NLP and Sustainability Report Generation
par: Wu, Qilong, et autres
Publié: (2024)