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Robust Bond Portfolio Construction via Convex-Concave Saddle Point Optimization

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  • Eric Luxenberg
  • Philipp Schiele
  • Stephen Boyd

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, \ie, 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.

Suggested Citation

  • Eric Luxenberg & Philipp Schiele & Stephen Boyd, 2022. "Robust Bond Portfolio Construction via Convex-Concave Saddle Point Optimization," Papers 2212.02570, arXiv.org, revised Jan 2024.
    • Handle: RePEc:arx:papers:2212.02570
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    References listed on IDEAS

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    1. Michael Puhle, 2008. "Bond Portfolio Optimization," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-540-76593-6, October.
    2. Damir Filipović & Markus Pelger & Ye Ye, 2022. "Stripping the Discount Curve - a Robust Machine Learning Approach," Swiss Finance Institute Research Paper Series 22-24, Swiss Finance Institute.
    3. R.H. Tütüncü & M. Koenig, 2004. "Robust Asset Allocation," Annals of Operations Research, Springer, vol. 132(1), pages 157-187, November.
    4. Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2014. "Recent Developments in Robust Portfolios with a Worst-Case Approach," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 103-121, April.
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