Are there long-run diversification gains from the Dow Jones Islamic finance index?

Abstract

We compare a nonlinear (time-varying) cointegration test with the standard cointegration test in studying the long-run relationship of the Dow Jones Islamic finance index with three other conventional global equity market indices. Our results show that there is a long-run nonlinear cointegrating relationship between the Dow Jones Islamic stock market index and other conventional stock market indices, which is not picked up by the linear cointegration test. Thus, Islamic markets seem to offer little, if any, long-run diversification to international investors.

Keywords:

• Islamic and conventional finance
• time-varying cointegration

JEL Classification:

• C5
• C12
• G1

Acknowledgements

We thank an anonymous referee for many helpful comments. However, any remaining errors are solely ours.

Notes

¹ Speculation using derivative markets and buying government debt that issues fixed coupons are prohibited, and investing in certain industries is not allowed (Hammoudeh et al., 2013).

² Other methods might support diversification despite the presence of dynamic cointegration (see Guidi and Ugur, 2014).

³ Failure to detect parameter shifts in econometric specifications when they exist implies that the model is misspecified, which could lead to poor forecasting performance (Gabriel and Martins, 2011).

⁴ The summary statistics show that for data in both log levels and log first difference, the null hypotheses of normality, no autocorrelation, and no ARCH effects are rejected.

⁵ These tests fail to reject the null of unit roots and also the null of no cointegration (results available upon request) for the log levels of the series.

⁶ This is supported by the Park and Hahn (1999) tests. The null hypothesis of fixed coefficient cointegration is rejected at the 1% level, favouring the alternative that the fixed coefficients model is not cointegrated. We were unable to reject the null hypothesis of cointegration in the TVC model.

⁷ Following the suggestions of an anonymous referee, we also followed the approach of Guidi and Ugur (2014) in using bivariate (which included the DJIM and one conventional stock market in turn) symmetric and asymmetric dynamic conditional correlations on returns data, to check for the robustness of our findings. Our basic result obtained from the time-varying cointegration approach still continued to hold in the sense that the correlation increased over time, especially since 2008. Details of these results are available upon request from the authors. It must, however, be pointed out, that since we are trying to analyse long-run diversification, the time-varying cointegration applied on the log-levels of data is the more appropriate approach rather than the DCC-GARCH approach of Guidi and Ugur (2014) used on the returns of the series, which in turn, tends to capture short-run comovements instead.