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Rearrangement algorithm and maximum entropy

Author

Listed:
  • Carole Bernard

    (Grenoble Ecole de Management
    Vrije Universiteit Brussel (VUB))

  • Oleg Bondarenko

    (University of Illinois at Chicago)

  • Steven Vanduffel

    (Vrije Universiteit Brussel (VUB))

Abstract

We study properties of the block rearrangement algorithm (BRA) in the context of inferring dependence among variables given their marginal distributions and the distribution of their sum. We show that when all distributions are Gaussian the BRA yields solutions that are “close to each other” and exhibit almost maximum entropy, i.e., the inferred dependence is Gaussian with a correlation matrix that has maximum possible determinant. We provide evidence that, when the distributions are no longer Gaussian, the property of maximum determinant continues to hold. The consequences of these findings are that the BRA can be used as a stable algorithm for inferring a dependence that is economically meaningful.

Suggested Citation

  • Carole Bernard & Oleg Bondarenko & Steven Vanduffel, 2018. "Rearrangement algorithm and maximum entropy," Annals of Operations Research, Springer, vol. 261(1), pages 107-134, February.
    • Handle: RePEc:spr:annopr:v:261:y:2018:i:1:d:10.1007_s10479-017-2612-2
    DOI: 10.1007/s10479-017-2612-2
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    2. Nabil Bouamara & Kris Boudt & S'ebastien Laurent & Christopher J. Neely, 2023. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Papers 2309.15705, arXiv.org.
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    4. Takaaki Koike & Liyuan Lin & Ruodu Wang, 2022. "Joint mixability and notions of negative dependence," Papers 2204.11438, arXiv.org, revised Jan 2024.
    5. Xu, Chi & Zheng, Chunling & Wang, Donghua & Ji, Jingru & Wang, Nuan, 2019. "Double correlation model for operational risk: Evidence from Chinese commercial banks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 327-339.

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