Reduced-Order Modeling for Heston Stochastic Volatility Model
Numerical Analysis
2025-01-03 v2 Numerical Analysis
Abstract
In this paper, we compare the intrusive proper orthogonal decomposition (POD) with Galerkin projection and the data-driven dynamic mode decomposition (DMD), for Heston's option pricing model. The full order model is obtained by discontinuous Galerkin discretization in space and backward Euler in time. Numerical results for butterfly spread, European and digital call options reveal that in general DMD requires more modes than the POD modes for the same level of accuracy. However, the speed-up factors are much higher for DMD than POD due to the non-intrusive nature of the DMD.
Cite
@article{arxiv.1611.06097,
title = {Reduced-Order Modeling for Heston Stochastic Volatility Model},
author = {Sinem Kozpınar and Murat Uzunca and Bülent Karasözen},
journal= {arXiv preprint arXiv:1611.06097},
year = {2025}
}
Comments
arXiv admin note: text overlap with arXiv:1606.08381