Testing the linkages of Arab stock markets: a multivariate GARCH approach

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The authors undertook to examine 720 monthly observations of activity in 15 Arab stock markets over four years (from 2014 to 2017) to identify the dynamic linkages among those markets. To achieve this, several forms of the Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) model were utilized. Both panel and individual stationarity, in addition to cointegration tests, were employed to highlight the interaction between these markets. The results suggest that Arab stock markets have weak linkages with the exception of those of the Gulf Cooperation Council (GCC). The authors also find out that the TARCH, EGARCH, PARCH, and Component GARCH (1,1) models are suitable in terms of passing the econometric analysis tests. Nevertheless, they conclude that the EGARCH model is the most appropriate for capturing the cross-market dynamic linkages, thereby outperforming the other GARCH specifications under study. The empirical findings bear special implications for economic literature regarding linkages of stock markets in the Arab world.

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    • Figure 1. Changes in monthly indices of Arab stock markets, 2014–2017
    • Table 1. Summary statistics of monthly prices of stock market indices, 2014M01–2017M12
    • Table 2. Results: panel unit root test
    • Table 3. Results: intermediate ADF unit root
    • Table 4. Summary results of panel cointegration
    • Table 5. Summary results of testing the cointegration
    • Table 6. Summary results of model estimation, Model 1: TARCH
    • Table 7. Summary results of model estimation, Model 2: EGARCH
    • Table 8. Summary results of model estimation, Model 3: PARCH
    • Table 9. Summary results of model estimation, Model 4: Component GARCH (1,1)