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World of Software > Computing > Worst-Case Portfolio Optimization & Hyperbolic Graph Clustering | HackerNoon
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Worst-Case Portfolio Optimization & Hyperbolic Graph Clustering | HackerNoon

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Last updated: 2026/02/21 at 12:22 PM
News Room Published 21 February 2026
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Worst-Case Portfolio Optimization & Hyperbolic Graph Clustering | HackerNoon
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Table of Links

Abstract and 1. Introduction

2. Financial Market Model and Worst-Case Optimization Problem

3. Solution to the Post-Crash Problem

4. Solution to the Pre-Crash Problem

5. A BSDE Characterization of Indifferences Strategies

6. The Markovian Case

7. Numerical Experiments

Acknowledgments and References

Appendix A. Proofs from Section 3

Appendix B. Proofs of BASDE Results from Section 5

Appendix C. Proofs of (CIR) Results from Section 6

2. Financial Market Model and Worst-Case Optimization Problem

A particularly important choice of those parameters leads to the following version of the Bates model [5] and Heston model [24], respectively:

In addition, we need the following integrability assumptions on the market coefficients λ and σ:

Admissible portfolio processes. We restrict our attention to admissible portfolio processes with continuous paths.

Note that the SDEs above are driven by the Brownian motion W with coefficients that are measurable w.r.t. a larger filtration than the one generated by W only.

The solution to the above SDE can then be given explicitly:

:::info
Authors:

(1) Sascha Desmettre;

(2) Sebastian Merkel;

(3) Annalena Mickel;

(4) Alexander Steinicke.

:::


:::info
This paper is available on arxiv under CC BY 4.0 DEED license.

:::

[1] This means we rule out short sales of the risky asset.

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