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Information networks in the financial sector and systemic risk

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  • Borochin, Paul
  • Rush, Stephen

Abstract

We create and test two novel network-based measures of interconnectedness in the financial industry during 1996 to 2013. A network based on informed trading in financial firms predicts firm-specific risk and performance, while one formed on financial firm returns predicts future macroeconomic risk. The measure of informed trading is robust to variable order arrival rates more common in modern algorithmic trading. A trading strategy based on informed trading network centrality in the financial sector delivers an annualized risk-adjusted return of 7.73%. This risk-adjusted return shows that the network centrality has an economic impact that is relevant beyond the statistical results of the paper.

Suggested Citation

  • Borochin, Paul & Rush, Stephen, 2022. "Information networks in the financial sector and systemic risk," Journal of Banking & Finance, Elsevier, vol. 134(C).
  • Handle: RePEc:eee:jbfina:v:134:y:2022:i:c:s0378426621002788
    DOI: 10.1016/j.jbankfin.2021.106327
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    More about this item

    Keywords

    Asset pricing; Network analysis; Systemic risk;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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