6533b857fe1ef96bd12b4581
RESEARCH PRODUCT
Reduced Order Models for Pricing European and American Options under Stochastic Volatility and Jump-Diffusion Models
Maciej BalajewiczJari Toivanensubject
Computational Engineering Finance and Science (cs.CE)FOS: Computer and information sciencesFOS: Economics and businessQuantitative Finance - Computational FinanceEuropean optionlinear complementary problemComputational Finance (q-fin.CP)reduced order modelAmerican optionComputer Science - Computational Engineering Finance and Scienceoption pricingdescription
European options can be priced by solving parabolic partial(-integro) differential equations under stochastic volatility and jump-diffusion models like the Heston, Merton, and Bates models. American option prices can be obtained by solving linear complementary problems (LCPs) with the same operators. A finite difference discretization leads to a so-called full order model (FOM). Reduced order models (ROMs) are derived employing proper orthogonal decomposition (POD). The early exercise constraint of American options is enforced by a penalty on subset of grid points. The presented numerical experiments demonstrate that pricing with ROMs can be orders of magnitude faster within a given model parameter variation range. peerReviewed
year | journal | country | edition | language |
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2016-12-01 |