简短交流：蒙特卡洛预期财富与风险度量权衡组合优化

IF 1.4 4区经济学 Q3 BUSINESS, FINANCE

SIAM Journal on Financial Mathematics Pub Date : 2024-06-03 DOI:10.1137/23m1624439

Raino A. E. Mäkinen, Jari Toivanen

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引用次数: 0

摘要

SIAM 金融数学期刊》，第 15 卷第 2 期，第 SC41-SC53 页，2024 年 6 月。摘要：在投资政策的现实约束条件下，用蒙特卡罗抽样风险资产路径描述了一种多期投资组合优化。所提出的方法可用于各种资产和风险模型。该方法无需动态编程或任何转换，因此非常灵活。以方差风险和半方差风险为例，分别考虑了均值方差公式和均值半方差公式。准牛顿方法与邻接梯度计算可以高效地解决由此产生的优化问题。数值示例显示了有效前沿，以及计算出的两种和五种资产的均值方差和均值-半方差投资组合的最优资产配置。

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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Short Communication: Monte Carlo Expected Wealth and Risk Measure Trade-Off Portfolio Optimization

SIAM Journal on Financial Mathematics, Volume 15, Issue 2, Page SC41-SC53, June 2024.
Abstract.A multiperiod portfolio optimization is described with Monte Carlo sampled risky asset paths under realistic constraints on the investment policies. The proposed approach can be used with various asset and risk models. It is flexible as it does not require dynamic programming or any transformations. As examples, the variance and semivariance risks are considered leading to mean-variance and mean-semivariance formulations, respectively. A quasi-Newton method with an adjoint gradient computation can solve the resulting optimization problems efficiently. Numerical examples show efficient frontiers together with optimal asset allocations computed for mean-variance and mean-semivariance portfolios with two and five assets.

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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.