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Sensitivity and computational complexity in financial networks

Author

Listed:
  • Hemenway, Brett

    (Department of Computer Science, University of Pennsylvania)

  • Khanna, Sanjeev

    (Department of Computer Science, University of Pennsylvania)

Abstract

Determining the causes of instability and contagion in financial networks is necessary to inform policy and avoid future financial collapse. In the American Economic Review, Elliott, Golub and Jackson proposed a simple model for capturing the dynamics of complex financial networks. In Elliott, Golub and Jackson’s model, the institutions in the network are connected by linear dependencies (cross-holdings) and if any institution’s value drops below a critical threshold, its value suffers an additional failure cost. This work shows that even in this simple model there are fundamental barriers to understanding the risks that are inherent in a network. First, if institutions are not required to maintain a minimum amount of self-holdings, any change in investments by a single institution can have an arbitrarily magnified influence on the net worth of the institutions in the system. This implies that if institutions have small self-holdings, then estimating the market value of an institution requires almost perfect information about every cross-holding in the system . Second, even if a regulator has complete information about all cross-holdings in the system, it may be computationally intractable to estimate the number of failures that could be caused by a small shock to the system.

Suggested Citation

  • Hemenway, Brett & Khanna, Sanjeev, 2016. "Sensitivity and computational complexity in financial networks," Algorithmic Finance, IOS Press, vol. 5(3-4), pages 95-110.
  • Handle: RePEc:ris:iosalg:0052
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    Citations

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    Cited by:

    1. Nils Bertschinger & Martin Hoefer & Daniel Schmand, 2019. "Flow Allocation Games," Papers 1908.01714, arXiv.org, revised Dec 2023.
    2. Dylan Herman & Cody Googin & Xiaoyuan Liu & Alexey Galda & Ilya Safro & Yue Sun & Marco Pistoia & Yuri Alexeev, 2022. "A Survey of Quantum Computing for Finance," Papers 2201.02773, arXiv.org, revised Jun 2022.
    3. P'al Andr'as Papp & Roger Wattenhofer, 2020. "Default Ambiguity: Finding the Best Solution to the Clearing Problem," Papers 2002.07741, arXiv.org, revised Oct 2021.
    4. Beni Egressy & Roger Wattenhofer, 2021. "Bailouts in Financial Networks," Papers 2106.12315, arXiv.org.

    More about this item

    Keywords

    Financial contagion; computational complexity; network analysis; network stability; sensitivity;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General

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