Global Journal of Management and Business Research, A: Administration and Management, Volume 21 Issue 12

vital for the design portfolio. The linear combination of stock market returns accounts for the variance in the data as a whole Alan Harper and Zhenhu Jin (2012). V. E mpirical R esults In this section, quantitative results obtained from the statistical analysis have been presented in the below tables. Various tests conducted are: correlations test, KMO test, component matrix test, communalities test, and rotated component matrix test. Table 1: Results of Correlations among 22 stock markets Source: Authors calculations Table 1 depicts stock market returns correlation with all the sample countries in the study. Sensex is correlated among the sample ranging from weak to highly correlated. Further, it can be inferred that Sensex has a weak correlation with few indices like Tadawul (Saudi Arabia, Amman SE General (Jordan), BLOM (Lebanon), and MSM (Oman). A geographical and economic association is one of the critical drivers for having such a relation. From the results depicted in Table 1, China, Jordan, Lebanon, Qatar, and Saudi Arabia are weakly correlated with other countries except with the countries geographically associated similarly France, Germany, Belgium, US, Canada, and Mexico are highly the rest having moderately correlated. Table 2: Results of KMO Measure and Bartlett’s Test KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .940 Bartlett's Test of Sphericity Approx. Chi-Square 15311.880 Df 231 Sig. .000 Source: Authors calculations For measuring the sample adequacy, the Kaiser-Meyer-Olkin (KMO) statistical method can be used, which measures the proportion of variance in the data variables that underlying factors might cause. 17 Global Journal of Management and Business Research Volume XXI Issue XII Version I Year 2021 ( ) A © 2021 Global Journals Design of Portfolio using Multivariate Analysis