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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한수학회 대한수학회지 대한수학회지 제59권 제2호
- 발행연도
- 2022.3
- 수록면
- 311 - 335 (25page)
- DOI
- 10.4134/JKMS.j210168
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초록· 키워드
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This paper treats Merton's classical portfolio optimization problem for a market participant who invests in safe assets and risky assets to maximize the expected utility. When the state process is a $d$-dimensional Markov diffusion, this problem is transformed into a problem of solving a Hamilton--Jacobi--Bellman (HJB) equation. The main purpose of this paper is to solve this HJB equation by a deep learning algorithm: the deep Galerkin method, first suggested by J. Sirignano and K. Spiliopoulos. We then apply the algorithm to get the solution to the HJB equation and compare with the result from the finite difference method.
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