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Optimal Network Compression

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  • Hamed Amini
  • Zachary Feinstein

Abstract

This paper introduces a formulation of the optimal network compression problem for financial systems. This general formulation is presented for different levels of network compression or rerouting allowed from the initial interbank network. We prove that this problem is, generically, NP-hard. We focus on objective functions generated by systemic risk measures under shocks to the financial network. We use this framework to study the (sub)optimality of the maximally compressed network. We conclude by studying the optimal compression problem for specific networks; this permits us to study, e.g., the so-called robust fragility of certain network topologies more generally as well as the potential benefits and costs of network compression. In particular, under systematic shocks and heterogeneous financial networks the robust fragility results of Acemoglu et al. (2015) no longer hold generally.

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  • Hamed Amini & Zachary Feinstein, 2020. "Optimal Network Compression," Papers 2008.08733, arXiv.org, revised Jul 2022.
    • Handle: RePEc:arx:papers:2008.08733
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    References listed on IDEAS

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    Cited by:

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    2. Amini, Hamed & Bichuch, Maxim & Feinstein, Zachary, 2023. "Decentralized payment clearing using blockchain and optimal bidding," European Journal of Operational Research, Elsevier, vol. 309(1), pages 409-420.
    3. Vikranth Lokeshwar Dhandapani & Shashi Jain, 2024. "Neural Networks for Portfolio-Level Risk Management: Portfolio Compression, Static Hedging, Counterparty Credit Risk Exposures and Impact on Capital Requirement," Papers 2402.17941, arXiv.org.

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