沃瑟斯坦球中的投资组合优化

IF 1.4 4区 经济学 Q3 BUSINESS, FINANCE
Silvana M. Pesenti, Sebastian Jaimungal
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引用次数: 1

摘要

我们研究了主动投资组合管理的问题,其中投资者的目标是在不偏离基准策略太远的情况下优于基准策略的风险概况。具体来说,投资者会考虑一些替代策略,这些策略的最终财富位于围绕基准最终财富的沃瑟斯坦球内——在分布上是接近的——并且具有特定的依赖关系,将各州的结果与之联系起来。然后,投资者选择另一种策略,使终端财富的扭曲风险最小化。在一般完全市场模型中,我们证明了最优动态策略的存在,并利用等压投影的概念给出了最优动态策略的表征。我们进一步提出了一种模拟方法来计算最优策略的终端财富,使我们的方法适用于广泛的市场模型。最后,我们以尾部风险值、逆s形和上下尾扭曲风险度量为例,说明了具有不同关联关系和风险偏好的投资者如何投资并改进基准。我们发现,投资者的最优终端财富分布在相对于基准的风险度量降低且保持基准结构的区域具有更大的概率质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Portfolio Optimization within a Wasserstein Ball
We study the problem of active portfolio management where an investor aims to outperform a benchmark strategy’s risk profile while not deviating too far from it. Specifically, an investor considers alternative strategies whose terminal wealth lies within a Wasserstein ball surrounding a benchmark’s terminal wealth—being distributionally close—and that have a specified dependence/copula tying state-by-state outcomes to it. The investor then chooses the alternative strategy that minimizes a distortion risk measure of terminal wealth. In a general complete market model, we prove that an optimal dynamic strategy exists and provide its characterization through the notion of isotonic projections. We further propose a simulation approach to calculate the optimal strategy’s terminal wealth, making our approach applicable to a wide range of market models. Finally, we illustrate how investors with different copula and risk preferences invest and improve upon the benchmark using the Tail Value-at-Risk, inverse S-shaped, and lower- and upper-tail distortion risk measures as examples. We find that investors’ optimal terminal wealth distribution has larger probability masses in regions that reduce their risk measure relative to the benchmark while preserving the benchmark’s structure.
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来源期刊
SIAM Journal on Financial Mathematics
SIAM Journal on Financial Mathematics MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
2.30
自引率
10.00%
发文量
52
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.
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