4 citations · 15 across the 5 of their papers we have counts for
5 papers
Finance-Informed Neural Network: Learning the Geometry of Option Pricing
Amine M. Aboussalah, Xuanze Li, Cheng Chi +1
We propose a Finance-Informed Neural Network (FINN) for option pricing and hedging that integrates financial theory directly into machine learning. Instead of training on observed…
Application of Tensor Neural Networks to Pricing Bermudan Swaptions
Raj G. Patel, Tomas Dominguez, Mohammad Dib +12
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 s…
Quantum-Inspired Tensor Neural Networks for Option Pricing
Raj G. Patel, Chia-Wei Hsing, Serkan Sahin +12
Recent advances in deep learning have enabled us to address the curse of dimensionality (COD) by solving problems in higher dimensions. A subset of such approaches of addressing th…
Quantum-Inspired Tensor Neural Networks for Partial Differential Equations
Raj Patel, Chia-Wei Hsing, Serkan Sahin +11
Partial Differential Equations (PDEs) are used to model a variety of dynamical systems in science and engineering. Recent advances in deep learning have enabled us to solve them in…
Don't overfit the history -- Recursive time series data augmentation
Amine Mohamed Aboussalah, Min-Jae Kwon, Raj G Patel +2
Time series observations can be seen as realizations of an underlying dynamical system governed by rules that we typically do not know. For time series learning tasks, we need to u…