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Developing a Framework on Modeling Dependence across Stock Markets using Copulas: A Case of 5 SADC Stock Markets

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  • Brian Basvi

    (University of Zimbabwe)

Abstract

Selecting the right dependence measure is crucial for multivariate statistical modelling. Because correlation is based on the elliptical distributions assumption of normalcy, which breaks down when there are extreme endpoints in either marginal or higher dimension, correlation is fraught with dangers. Copulas provide an alternate dependence measure that gets over correlation’s drawbacks and can be used to identify if a reliance is linear, upper tail, or lower tail. In order to evaluate the efficacy of regional integration, this study investigates whether copulas are suitable for simulating bivariate reliance among five SADC stock markets. The research design used in the study was explanatory and descriptive. Because of their favourable characteristics, Archimedean copulas were investigated using both parametric and non-parametric methods. Because the markets were likely to boom concurrently, non-parametric estimate produced insightful results demonstrating the suitability of the Gumbel copula in dependence modelling and suggesting that investors have opportunities for portfolio diversification throughout the region.

Suggested Citation

  • Brian Basvi, 2024. "Developing a Framework on Modeling Dependence across Stock Markets using Copulas: A Case of 5 SADC Stock Markets," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 11(5), pages 785-807, May.
    • Handle: RePEc:bjc:journl:v:11:y:2024:i:5:p:785-807
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    References listed on IDEAS

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    1. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
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