Iterative spectral methods for Hamilton-Jacobi-Bellman quasi-variational inequality in finance

Minlan Lei and Zhengyang Lu

PLOS ONE, 2026, vol. 21, issue 9, 1-22

Abstract: This study proposes a novel computational scheme for utility-maximization problems involving optimal stopping, formulated as Hamilton-Jacobi-Bellman quasi-variational inequalities. The methodology integrates Gauss-Lobatto-Legendre spectral discretization with a penalization method and is solved efficiently via policy iteration. We establish the convergence of the penalized scheme and verify the effectiveness and robustness of the framework through a series of numerical experiments.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0359303

DOI: 10.1371/journal.pone.0359303

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