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3.5.3 Unit Analysis

In this research it involves interest rate (t-bills), GDP (IP), money supply (M3) and inflation (CPI) to measure macroeconomic variables and FTSE Bursa Malaysia KLCI: Property indices to indicate the performance of property stock.

3.5.4 Time Horizon

This study will use monthly basis data from the year of 2000 until 2010 for the all variables used in this research.

3.6 Theoretical Framework

There is a classical theory that explained the high correlation between the economic factors and stock market.

Dependent variable: property stock index

Independent variables: money supply (M3), inflation rate (CPI), interest rate and GDP growth.

Independent Dependent

Interest Rate

(T-bills)

Property stock

Index

GDP Growth

(IP)

Money Supply (M3)

Inflation (CPI)

According to the diagram above, it can be elaborated that the property stock market performance can be determined by the interest rate (t-bills), GDP (IP), money supply (M3) and inflation (CPI).

3.7 Data analysis and treatment

The statistical tools use in the research is Multiple Linear Regression Model. The general purpose of multiple regressions is to learn more about the relationship between several independent or predictor variables and a dependent or criterion variable. This model of analysis is done to examine the simultaneous effects of several independent variables on a dependent variable that is interval scaled.

Multiple Linear Regression Model:

Where:

Y = Dependent variable which represent property index

= The constant number of equation

= Coefficient Beta value

= Independent variable which represent GDP (IP)

= Independent variable which represent inflation rate (CPI)

= Independent variable which represent interest rate (t-bills)

= Independent variable which represent money supply (M3)

= Error

COEFFICIENT OF CORRELATION (R)

The correlation coefficient is used to measure of how well trends in the predicted values follow trends in past actual values. It measures the strength of association between 2 and more variables. In this study, the coefficient of correlation can be useful to test relationship between property index and four macroeconomics chosen.

COEFFICIENT OF DETERMINATION (R2)

The R-square value is an indicator of how well the model fits the data and the coefficient of the determination is better measure than (R) because the value of R-Squared can be interpreted precisely. In this research, movements of the variables that can be explained by movements in a benchmark index R-Squared when property index that explained by the four independent variables including GDP (IP), interest rate (t-bills), money supply (M3), inflation rate (CPI),

F-TEST

The analysis of F-Test allows deriving a test regression model earliest, either acceptable or meaningful to represent the relationship between variables. The significant in F-test shows the overall relationship within variables.

T-TEST

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