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Unveiling True Connectedness in US State-Level Stock Markets: The Role of Common Factors

Author

Listed:
  • Massimiliano Caporin

    (Department of Statistical Sciences, University of Padova, Via Cesare Battisti 241, 35121 Padova, Italy)

  • Oguzhan Cepni

    (Ostim Technical University, Ankara, Turkiye; University of Edinburgh Business School, Centre for Business, Climate Change, and Sustainability; Department of Economics, Copenhagen Business School, Denmark)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Bertrand B. Maillet

    (University of La Reunion, Saint-Denis, France; Department of Economics, Università Ca’ Foscari di Venezia, Venice, Italy; Unversity of ChongQing, China, and Variances, Paris, France)

Abstract

The objective of this paper is to analyze the time-varying degree of interconnectedness of 50 state-level stock returns and their volatility of the United States (US) while filtering out common factors and insignificant coefficients using Least Absolute Shrinkage and Selection Operator (Lasso) regularization. Based on monthly data from February 1994 to November 2024, we find that not accounting for common factors is likely to result in relatively higher spillover indexes. Our findings, beyond their academic value, have important implications for investors and policymakers.

Suggested Citation

  • Massimiliano Caporin & Oguzhan Cepni & Rangan Gupta & Bertrand B. Maillet, 2025. "Unveiling True Connectedness in US State-Level Stock Markets: The Role of Common Factors," Working Papers 202509, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202509
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    References listed on IDEAS

    as
    1. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
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    4. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
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    6. Francis X. Diebold & Kamil Yilmaz, 2022. "On the Past, Present, and Future of the Diebold-Yilmaz Approach to Dynamic Network Connectedness," Koç University-TUSIAD Economic Research Forum Working Papers 2207, Koc University-TUSIAD Economic Research Forum.
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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