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Autori principali: Duong, Hung, Fahim, Arash
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2406.06787
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author Duong, Hung
Fahim, Arash
author_facet Duong, Hung
Fahim, Arash
contents We introduce a generic numerical schemes for fully nonlinear parabolic PDEs on the full domain, where the nonlinearity is convex on the Hessian of the solution. The main idea behind this paper is reduction of a fully nonlinear problem to a class of simpler semilinear ones parameterized by the diffusion term. The contribution of this paper is to provide a directional maximum principle with respect to the diffusion coefficient for semilinear problems, which specifies how to modify the diffusion coefficient to approach to the solution of the fully nonlinear problem. While the objects of the study, diffusion coefficient, is infinite dimensional, the maximum direction of increase can be found explicitly. This also provides a numerical gradient ascent method for the fully nonlinear problem. To establish a proof-of-concept, we test our method in a numerical experiment on the fully nonlinear Hamilton-Jacobi-Bellman equation for portfolio optimization under stochastic volatility model.
format Preprint
id arxiv_https___arxiv_org_abs_2406_06787
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Gradient ascent method for fully nonlinear parabolic differential equations with convex nonlinearity
Duong, Hung
Fahim, Arash
Analysis of PDEs
49L20, 49M25, 93E20
G.1.8
We introduce a generic numerical schemes for fully nonlinear parabolic PDEs on the full domain, where the nonlinearity is convex on the Hessian of the solution. The main idea behind this paper is reduction of a fully nonlinear problem to a class of simpler semilinear ones parameterized by the diffusion term. The contribution of this paper is to provide a directional maximum principle with respect to the diffusion coefficient for semilinear problems, which specifies how to modify the diffusion coefficient to approach to the solution of the fully nonlinear problem. While the objects of the study, diffusion coefficient, is infinite dimensional, the maximum direction of increase can be found explicitly. This also provides a numerical gradient ascent method for the fully nonlinear problem. To establish a proof-of-concept, we test our method in a numerical experiment on the fully nonlinear Hamilton-Jacobi-Bellman equation for portfolio optimization under stochastic volatility model.
title Gradient ascent method for fully nonlinear parabolic differential equations with convex nonlinearity
topic Analysis of PDEs
49L20, 49M25, 93E20
G.1.8
url https://arxiv.org/abs/2406.06787