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Studies in Nonlinear Dynamics & Econometrics

Ed. by Mizrach, Bruce

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Volume 21, Issue 3


Volume 24 (2020)

Detecting capital market convergence clubs

Fuat C. Beylunioglu / Thanasis Stengos / M. Ege Yazgan
Published Online: 2017-06-14 | DOI: https://doi.org/10.1515/snde-2016-0062


In this study, we propose a new method to find convergence clubs that combine pairwise method of testing convergence with maximal clique algorithm. Unlike many of those already developed in the literature, this new method aims to find convergence clubs endogenously without depending on priori classifications. We use our method to study convergence among different capital markets as captured by their respective indices. Stock market convergence would indicate the absence of arbitrage opportunities in moving between the different markets as they would all present investors with similar risks. Furthermore, stock market convergence would be a precursor to GDP convergence as these economies would be bound by similar (possibly unobservable) common factors that affect long run macroeconomic performance.

This article offers supplementary material which is provided at the end of the article.

Keywords: stock market convergence; convergence clubs; maximal clique algorithm

JEL Classification: C32; O47


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About the article

Published Online: 2017-06-14

Citation Information: Studies in Nonlinear Dynamics & Econometrics, Volume 21, Issue 3, 20160062, ISSN (Online) 1558-3708, DOI: https://doi.org/10.1515/snde-2016-0062.

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