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Networks of causal relationships in the U.S. stock market

Author

Listed:
  • Shirokikh Oleg

    (Frontline Solver, Reno, NV, USA)

  • Pastukhov Grigory

    (CSX Transportation, Jacksonville, FL, USA)

  • Semenov Alexander

    (Department of Industrial & Systems Engineering, University of Florida, Gainesville, FL, USA)

  • Butenko Sergiy

    (Department of Industrial & Systems Engineering, Texas A&M University, College Station, TX, USA)

  • Veremyev Alexander
  • Boginski Vladimir

    (Department of Industrial Engineering & Management Systems, University of Central Florida, Orlando, FL, USA)

  • Pasiliao Eduardo L.

    (Munitions Directorate, Air Force Research Laboratory, Eglin AFB, FL, USA)

Abstract

We consider a network-based framework for studying causal relationships in financial markets and demonstrate this approach by applying it to the entire U.S. stock market. Directed networks (referred to as “causal market graphs”) are constructed based on publicly available stock prices time series data during 2001–2020, using Granger causality as a measure of pairwise causal relationships between all stocks. We consider the dynamics of structural properties of the constructed network snapshots, group stocks into network-based clusters, as well as identify the most “influential” market sectors via the PageRank algorithm. Interestingly, we observed drastic changes in the considered network characteristics in the years that corresponded to significant global-scale events, most notably, the financial crisis of 2008 and the COVID-19 pandemic of 2020.

Suggested Citation

  • Shirokikh Oleg & Pastukhov Grigory & Semenov Alexander & Butenko Sergiy & Veremyev Alexander & Boginski Vladimir & Pasiliao Eduardo L., 2022. "Networks of causal relationships in the U.S. stock market," Dependence Modeling, De Gruyter, vol. 10(1), pages 177-190, January.
    • Handle: RePEc:vrs:demode:v:10:y:2022:i:1:p:177-190:n:6
    DOI: 10.1515/demo-2022-0110
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    References listed on IDEAS

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    1. Wu, Fei & Zhang, Dayong & Zhang, Zhiwei, 2019. "Connectedness and risk spillovers in China’s stock market: A sectoral analysis," Economic Systems, Elsevier, vol. 43(3).
    2. Corsi, Fulvio & Lillo, Fabrizio & Pirino, Davide & Trapin, Luca, 2018. "Measuring the propagation of financial distress with Granger-causality tail risk networks," Journal of Financial Stability, Elsevier, vol. 38(C), pages 18-36.
    3. Granger, C. W. J., 1980. "Testing for causality : A personal viewpoint," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 329-352, May.
    4. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
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