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Stock Returns’ Co-Movement: A Spatial Model with Convex Combination of Connectivity Matrices

Author

Listed:
  • Nadia Ben Abdallah

    (Department of Finance, Higher Institute of Management, University of Sousse, Sousse BN1 9RH, Tunisia)

  • Halim Dabbou

    (Department of Administration, Hearst University, Campus of Timmins, Timmins, ON P0L 1N0, Canada)

  • Mohamed Imen Gallali

    (Laboratory of Research in Innovative Management, Risk, Accounting and Finance, University of Manouba, Manouba LR21ES29, Tunisia)

  • Salem Hathroubi

    (Department of Economics, College of Business, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11564, Saudi Arabia)

Abstract

This paper examines the extent of stock-returns’ co-movements among firms in different countries and explores how various measures of closeness affect those co-movements by estimating a spatial autoregressive (SAR) convex combination model that merges four weight matrices—geographical distance, bilateral trade, sector similarity, and company size—into one global matrix. Our results reveal strong spatial stock-market dependence, show that spatial proximity is better captured by financial-distance measures than by pure geographical distance, and indicate that the weight matrix based on sector similarities outperforms the other linkages in explaining firms’ co-movements. Extending the traditional SAR model, the study simultaneously evaluated cross-country and within-country dependencies, providing insights valuable to investors building optimal portfolios and to policymakers monitoring contagion and systemic risk.

Suggested Citation

  • Nadia Ben Abdallah & Halim Dabbou & Mohamed Imen Gallali & Salem Hathroubi, 2025. "Stock Returns’ Co-Movement: A Spatial Model with Convex Combination of Connectivity Matrices," Risks, MDPI, vol. 13(6), pages 1-19, June.
    • Handle: RePEc:gam:jrisks:v:13:y:2025:i:6:p:110-:d:1672718
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    References listed on IDEAS

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