Application of Tensor Neural Networks to Pricing Bermudan Swaptions

no code implementations • 18 Apr 2023 • Raj G. Patel, Tomas Dominguez, Mohammad Dib, Samuel Palmer, Andrea Cadarso, Fernando De Lope Contreras, Abdelkader Ratnani, Francisco Gomez Casanova, Senaida Hernández-Santana, Álvaro Díaz-Fernández, Eva Andrés, Jorge Luis-Hita, Escolástico Sánchez-Martínez, Samuel Mugel, Roman Orus

The Cheyette model is a quasi-Gaussian volatility interest rate model widely used to price interest rate derivatives such as European and Bermudan Swaptions for which Monte Carlo simulation has become the industry standard.

Privacy-preserving machine learning with tensor networks

1 code implementation • 24 Feb 2022 • Alejandro Pozas-Kerstjens, Senaida Hernández-Santana, José Ramón Pareja Monturiol, Marco Castrillón López, Giannicola Scarpa, Carlos E. González-Guillén, David Pérez-García

Tensor networks, widely used for providing efficient representations of low-energy states of local quantum many-body systems, have been recently proposed as machine learning architectures which could present advantages with respect to traditional ones.

BIG-bench Machine Learning Privacy Preserving +1