Image de couverture de livre

A High-Level Framework for Practically Model-Independent Pricing

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Airoldi, Marco
Format:	Preprint
Publié:	2025
Sujets:	Computational Finance
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A Prior-Predictive Monte Carlo Framework for Pricing Complex Data Products in Data-Poor Markets
par: Siemiatkowski, Adam L., et autres
Publié: (2026)

KANOP: A Data-Efficient Option Pricing Model using Kolmogorov-Arnold Networks
par: Handal, Rushikesh, et autres
Publié: (2024)

Leveraging Machine Learning for High-Dimensional Option Pricing within the Uncertain Volatility Model
par: Goudenege, Ludovic, et autres
Publié: (2024)

Beyond Black-Scholes: A Computational Framework for Option Pricing Using Heston, GARCH, and Jump Diffusion Models
par: Sidhu, Karmanpartap Singh, et autres
Publié: (2026)

Machine Learning Methods for Pricing Financial Derivatives
par: Fan, Lei, et autres
Publié: (2024)

Stochastic Approaches to Asset Price Analysis
par: Sekatchev, Michael, et autres
Publié: (2024)

An Efficient Machine Learning Framework for Option Pricing via Fourier Transform
par: Zhang, Liying, et autres
Publié: (2025)

Pricing Options on Forwards in Function-Valued Affine Stochastic Volatility Models
par: He, Jian, et autres
Publié: (2025)

Deep Learning for Conditional Asset Pricing Models
par: Liu, Hongyi
Publié: (2025)

A Unifying Approach for the Pricing of Debt Securities
par: Vachon, Marie-Claude, et autres
Publié: (2024)

European Option Pricing in Regime Switching Framework via Physics-Informed Residual Learning
par: Pande, Naman Krishna, et autres
Publié: (2024)

A Gaussian Process Based Method with Deep Kernel Learning for Pricing High-dimensional American Options
par: Zhuang, Jirong, et autres
Publié: (2023)

PriceFM: Foundation Model for Probabilistic Electricity Price Forecasting
par: Yu, Runyao, et autres
Publié: (2025)

Tokenizing Stock Prices for Enhanced Multi-Step Forecast and Prediction
par: Zhu, Zhuohang, et autres
Publié: (2025)

On Pricing of Discrete Asian and Lookback Options under the Heston Model
par: Perotti, Leonardo, et autres
Publié: (2022)

Price predictability at ultra-high frequency: Entropy-based randomness test
par: Shternshis, Andrey, et autres
Publié: (2023)

A Modular LLM Framework for Explainable Price Outlier Detection
par: Sartipi, Shadi, et autres
Publié: (2026)

Pricing Barrier Options with DeepBSDEs
par: Ganesan, Narayan, et autres
Publié: (2020)

Can Machine Learning Algorithms Outperform Traditional Models for Option Pricing?
par: Milyushkov, Georgy
Publié: (2025)

QUEENS: An Open-Source Python Framework for Solver-Independent Analyses of Large-Scale Computational Models
par: Biehler, Jonas, et autres
Publié: (2025)

A Novel Decision Ensemble Framework: Customized Attention-BiLSTM and XGBoost for Speculative Stock Price Forecasting
par: Din, Riaz Ud, et autres
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)

Multivariate Simulation-based Forecasting for Intraday Power Markets: Modelling Cross-Product Price Effects
par: Hirsch, Simon, et autres
Publié: (2023)

DFT: A Dual-branch Framework of Fluctuation and Trend for Stock Price Prediction
par: Dong, Chengqi, et autres
Publié: (2024)

Stochastic Expansion for the Pricing of Asian and Basket Options
par: Floc'h, Fabien Le
Publié: (2024)

Quantum Speedups for Derivative Pricing Beyond Black-Scholes
par: Herman, Dylan, et autres
Publié: (2026)

Pricing American Parisian Options under General Time-Inhomogeneous Markov Models
par: Liu, Yuhao, et autres
Publié: (2025)

An Advanced Ensemble Deep Learning Framework for Stock Price Prediction Using VAE, Transformer, and LSTM Model
par: Sarkar, Anindya, et autres
Publié: (2025)

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

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

Feynman-Kac Derivatives Pricing on the Full Forward Curve
par: Mott, Kevin
Publié: (2026)

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

A Path Integral Approach for Time-Dependent Hamiltonians with Applications to Derivatives Pricing
par: Stedman, Mark, et autres
Publié: (2024)

Hedonic Models Incorporating ESG Factors for Time Series of Average Annual Home Prices
par: Bailey, Jason R., et autres
Publié: (2024)

Implementing Dynamic Pricing Across Multiple Pricing Groups in Real Estate
par: Razumovskiy, Lev, et autres
Publié: (2024)

Option Pricing with Stochastic Volatility, Equity Premium, and Interest Rates
par: Hao, Nicole, et autres
Publié: (2024)

Quantum Advantage for Multi-option Portfolio Pricing and Valuation Adjustments
par: Han, Jeong Yu, et autres
Publié: (2022)

Pricing Lookback Options on a Quantum Computer
par: Paquette, Florence, et autres
Publié: (2026)

Pricing TARN Using a Finite Difference Method
par: Luo, Xiaolin, et autres
Publié: (2013)

American Call Options Pricing With Modular Neural Networks
par: Unnikrishnan, Ananya
Publié: (2024)