4 papers
Quantum computing for multidimensional option pricing: End-to-end pipeline
Julien Hok, Ãlvaro Leitao
This work introduces an end-to-end framework for multi-asset option pricing that combines market-consistent risk-neutral density recovery with quantum-accelerated numerical integra…
Parametric Numerical Integration with (Differential) Machine Learning
Ãlvaro Leitao, Jonatan Ráfales
In this work, we introduce a machine/deep learning methodology to solve parametric integrals. Besides classical machine learning approaches, we consider a differential learning fra…
Static and dynamic SABR stochastic volatility models: calibration and option pricing using GPUs
J. L. Fernández, A. M. Ferreiro, J. A. GarcÃa +3
For the calibration of the parameters in static and dynamic SABR stochastic volatility models, we propose the application of the GPU technology to the Simulated Annealing global op…
On Deep Learning for computing the Dynamic Initial Margin and Margin Value Adjustment
Joel P. Villarino, Ãlvaro Leitao
The present work addresses the challenge of training neural networks for Dynamic Initial Margin (DIM) computation in counterparty credit risk, a task traditionally burdened by the…