Department of Economics Sciences, University Malaya, Kuala Lumpur, Malaysia
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Do Financial Crises Affect Nonlinear Exchange Rate and Stock Market Cointegration? A Heterogeneous Nonlinear Panel Data Model Using the PMG Approach
Author(s): Kaobing Peng*
The functional data displaying geographical dependency are the main focus of this work. Using the functional Moran's I statistic, classical
principal component analysis and functional areal spatial principal component analysis, the spatial autocorrelation of stock exchange returns for
exchanges in 69 countries was examined. This study focuses on the time when the global stock market sold off and established that there is spatial
autocorrelation among the stock exchanges under consideration. Before completing the traditional analysis, the stock exchange return data were
transformed into functional data. Results of the functional Monte Carlo test The worldwide market sell-off had a significant influence on the spatial
autocorrelation of stock exchanges, according to Moran's I statistics. Positive spatial autocorrelation is visible in the stock exchanges' principal
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DOI:
10.37421/2375-4389.2022.10.387
Journal of Global Economics received 1931 citations as per Google Scholar report