Optimal Investment with Risk Controlled by Weighted Entropic Risk Measures

IF 1.4 4区经济学 Q3 BUSINESS, FINANCE

SIAM Journal on Financial Mathematics Pub Date : 2024-02-27 DOI:10.1137/22m152894x

Jianming Xia

引用次数: 0

Abstract

SIAM Journal on Financial Mathematics, Volume 15, Issue 1, Page 54-92, March 2024.
Abstract.A risk measure that is consistent with the second-order stochastic dominance and additive for sums of independent random variables can be represented as a weighted entropic risk measure (WERM). The expected utility maximization problem with risk controlled by WERM and a related risk minimization problem are investigated in this paper. The latter is equivalent to a problem of maximizing a weighted average of constant-absolute-risk-aversion certainty equivalents. The solutions of all the optimization problems are explicitly characterized, and an iterative method is provided to obtain the solutions numerically.

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用加权熵风险度量控制风险的最优投资

SIAM 金融数学期刊》第 15 卷第 1 期第 54-92 页，2024 年 3 月。摘要.符合二阶随机支配性且对独立随机变量之和具有可加性的风险度量可以表示为加权熵风险度量（WERM）。本文研究了由 WERM 控制风险的期望效用最大化问题和相关的风险最小化问题。后者等同于恒定-绝对-风险-反转确定性等价物的加权平均值最大化问题。本文明确描述了所有优化问题的解，并提供了一种迭代方法来数值求解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

SIAM Journal on Financial Mathematics MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-

CiteScore

2.30

自引率

10.00%

发文量

期刊介绍： SIAM Journal on Financial Mathematics (SIFIN) addresses theoretical developments in financial mathematics as well as breakthroughs in the computational challenges they encompass. The journal provides a common platform for scholars interested in the mathematical theory of finance as well as practitioners interested in rigorous treatments of the scientific computational issues related to implementation. On the theoretical side, the journal publishes articles with demonstrable mathematical developments motivated by models of modern finance. On the computational side, it publishes articles introducing new methods and algorithms representing significant (as opposed to incremental) improvements on the existing state of affairs of modern numerical implementations of applied financial mathematics.