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s and interest rate are related with all the independent variables. The correlation between money supply and interest rate shows they are related but still in a moderate level which is 0.445.

Both GDP and inflation also related with interest rate which is 0.003 and 0.296 respectively but still in a weak level. Its mean that if interest rate is highly correlated it’s actually having something in common and the research should not take it as independent variables.

From the table 3 the R value is 0.569 which is 56.9% of the regression model process has been explained by the independent variables that has involved in this study while the other 43.1% has been explained by other variables. R Square shows that 32.4% changes in property index can be explained by GDP, interest rate, inflation and money supply. The adjusted R Square follows the rules of regression which is lower than R Square indicates that how much variation in dependent variable is influence by independent variables.

Through the result 30.2% of the variations of property index can be explain by GDP, interest rate, inflation and money supply.

4.1.4 Anova

Table 4: Anova

Anova shows the value of F test to see if the whole method is significant. With P value of zero to three decimal places the model is statically significant. Therefore it’s indicated that all the independent variables which are the inflation, money supply, GDP, and interest rate has positive relationship to the property stock market performance in Malaysia. From the table above, since the P value is below 0.05 then this research should accept the entire null hypothesis which all the independent variables have significant relationship with property index. This means that if it’s greater than 0.05 the model is bust and should not go any further.

Y = 6579.368 + -0.185 GDP + -84.685 CPI + 0.003 M3 + 161.669 T-bills

(.914) (.000) (.000) (.000)

From the table above, 6579.368 is the alpha which intercept and it’s also shows the result of beta, β shows the relationship between dependent variable and independent variables. β values also will tell what is the degree for each independent variable that affects the outcome result when all others independent variables are held in constant. From the table, β GDP (IP) shows result of -0.185 which mean 1 point increase in GDP, property index will decrease by -0.185. But the P value is actually showing insignificant because more than 0.05 and can’t give so much impact on dependent variables compare to others variables. From the table, β inflation rate (CPI) show result of -84.685 and significant at 0.00, this negative relation exists between inflation rate and property stock market index. In this situation, when inflation rate changed by 1 point, the property stock market index will decrease by 84.865. While for money supply (M3), it shows positive relationship toward property stock market index in Malaysia. It shows β value of 0.003 and significant at 0.00. This means, when money supply changed by 1 unit, it will cause the property stock market index in Malaysia also increase by 0.003. For interest rate (T-bills), its shows positive relationship toward property stock market index in Malaysia and shows β value of 161.669 and significant at 0.00. This means, when interest rate (T-bill) changed by 1 point, it will cause the property stock market index