Quantum-inspired variational algorithms for partial differential equations: Application to financial derivative pricing
Numerical Analysis
2022-07-26 v1 Numerical Analysis
Mathematical Finance
Abstract
Variational quantum Monte Carlo (VMC) combined with neural-network quantum states offers a novel angle of attack on the curse-of-dimensionality encountered in a particular class of partial differential equations (PDEs); namely, the real- and imaginary time-dependent Schr\"odinger equation. In this paper, we present a simple generalization of VMC applicable to arbitrary time-dependent PDEs, showcasing the technique in the multi-asset Black-Scholes PDE for pricing European options contingent on many correlated underlying assets.
Keywords
Cite
@article{arxiv.2207.10838,
title = {Quantum-inspired variational algorithms for partial differential equations: Application to financial derivative pricing},
author = {Tianchen Zhao and Chuhao Sun and Asaf Cohen and James Stokes and Shravan Veerapaneni},
journal= {arXiv preprint arXiv:2207.10838},
year = {2022}
}