Robust Bond Portfolio Construction via Convex–Concave Saddle Point Optimization

IF 1.6 3区 数学 Q2 MATHEMATICS, APPLIED
Eric Luxenberg, Philipp Schiele, Stephen Boyd
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引用次数: 0

Abstract

The minimum (worst case) value of a long-only portfolio of bonds, over a convex set of yield curves and spreads, can be estimated by its sensitivities to the points on the yield curve. We show that sensitivity based estimates are conservative, i.e., underestimate the worst case value, and that the exact worst case value can be found by solving a tractable convex optimization problem. We then show how to construct a long-only bond portfolio that includes the worst case value in its objective or as a constraint, using convex–concave saddle point optimization.

Abstract Image

通过凸凹鞍点优化构建稳健的债券投资组合
在收益率曲线和利差的凸集合上,一个纯长期债券投资组合的最小(最坏)价值可以通过其对收益率曲线上各点的敏感度来估算。我们的研究表明,基于敏感度的估算是保守的,即低估了最坏情况的价值,而准确的最坏情况价值可以通过求解一个简单的凸优化问题得到。然后,我们展示了如何利用凸凹鞍点优化,构建一个将最坏情况值作为目标或约束条件的纯长期债券投资组合。
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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
149
审稿时长
9.9 months
期刊介绍: The Journal of Optimization Theory and Applications is devoted to the publication of carefully selected regular papers, invited papers, survey papers, technical notes, book notices, and forums that cover mathematical optimization techniques and their applications to science and engineering. Typical theoretical areas include linear, nonlinear, mathematical, and dynamic programming. Among the areas of application covered are mathematical economics, mathematical physics and biology, and aerospace, chemical, civil, electrical, and mechanical engineering.
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