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Effects Towards Property Stock Market Return Finance Essay

In recent time the relationship between growth and stock market development has dominated both academician and practitioner’s literature. A significant research has been done to investigate the relationship between stock market returns and range of macroeconomic variables. Studied not only very useful to policy makers and investors but it will also test the efficiently of the stock market. In this research property stock is being chosen because of rapid development of Malaysia.

Currently there are 88 companies that have been listed on Bursa Malaysia which growth parallel with the economic growth in Malaysia. Most of these companies are active in property development in Malaysia which having a lot of project around Malaysia. Because of the rapid development by them, it’s become popular among the small investor to buy their shares.

Background Of The Study

Malaysia’s housing market was hit by the global economic slowdown in 2008 and 2009, with political instability and roiling business confidence. Average property prices fell -0.9% in 2009 when adjusted for inflation. Some developers deferred project launches, while others scaled back. Malaysia’s GDP contracted 3.6% in 2009, due to the global recession, after rising 5.75% annually from 2002 to 2008.

When all the variables in the economy take place it will reflect to the company affected and their stock as well. Stock performance has become an interest topic for investors as well individuals, beside it will be useful because it will influence countries development and growth. Stock prices is generally believed to be determined by some fundamental macroeconomic variables such as money supply, country reserve, interest rate, exchange rate, inflation rates, industrial production and many more.

The purpose of the present study is to investigate the relationship between Malaysian property stock prices and macroeconomic aggregates. Because of not many researchers tried to investigate based on the property sector. In order to analyze the interaction, four relevance economic indicators have been selected such as money supply (M3), inflation rate, interest rate and GDP.

Problem Statement

Thus this study will focuses its attention to four macroeconomic variables that may lead the stock price including money supply, inflation rate, GDP and interest rate with KLCI property indices. Those factors motivate to this study, to examine the issue for a Malaysian economy, for the period of study 1990-2010. In addition, it will make a finer point with respect to the relationship between economic growth and property stock market.

Research Question

In this study, there are several research questions that has been developed regarding the problem statement occurred. These research questions are:

Does the GDP growth has an effect towards property stock market return?

Does the inflation has an effect towards property stock market return?

Does the money supply has an effect towards property stock market return?

Doe the interest rate has an effect towards property stock market return?

Research Objective

The objectives of this study would be:

To investigate the effect between GDP growth and property stock market return.

To investigate the effect between inflation and property stock market return.

To investigate the effect between money supply and property stock market return.

To investigate the effect between interest rate and property stock market return.

Significant Of Study

Property stock

This study could provide some useful information and investor also will be able to understand the situation of their companies and how to deal with all the variables that had affected the return of property stock.

Researcher

This research also acts as a reference for other researchers and consultants to further their research. Furthermore, it can help these companies to understand the situation better and to overcome this situation.

Government

This study also can help the government to realize the effect of macroeconomic crisis to property stock in Malaysia.

Scope Of The Study

The purpose of this study is to determine whether the returns of the property stock market are related to the current economic activities in Malaysia. In order to explain, this study will using the property index as a stock market indicator and four relevant macroeconomic variables that may come from interest rate, GDP growth, money supply and inflation. To evaluate the effect between macroeconomic and property stock market multiple linear regression method will be use which comprise data from the year of 2000-2010 in monthly basis.

Limitation Of Study

In order to complete the study several limitation occurred which is brought some challenge to deal with along the process.

Time horizon

This study is conducted in a limited period where the data is only comprised from 2000-2010. It would give the different result if it done with the longer time horizon lets says data collected comprise of 30 years.

Availability of the data collects

Most of the previous study using different model and approach, also some information about property stock and macroeconomic are not easily available. Beside some journal available is not latest published.

Definition Of Terms

1.8.1 Property stock market index

In Malaysia overall performance of stock market can be measure from FTSE Bursa Malaysian KLCI. In this research property stock market index will be use which is comprised of performance of property stock in Malaysia.

1.8.2 Macroeconomic Variables

Macroeconomic are chosen instead of microeconomic because this research want to know the external impact towards property stock market. This study used four economic variables which is interest rate, GDP growth, money supply and inflation as well. The selection of these variables is chosen based from the past studies which is relevance in Malaysia.

1.8.3 Interest Rate

This economic indicator has been chosen because it would affect the future cash flow of property firms and discount rate. Usually higher interest rate would increase debt service on property companies and reduce future net income. It does affect the investor rather not to invest in stock market but they will save their money in the bank which is fixed deposit that will give higher interest rate.

1.8.4 GDP

Growth GDP is a measure of all currently produced final goods and services valued at market prices and the aggregated value of all the industries in an economy. Since real estate is a significant asset of a nation’s economy, the economic growth should reflect the property market conditions. Consequently, the GDP growth could have predicative power to property stock returns. Accordingly growth in GDP is expected to have a positive influence on the excess returns for property stocks.

1.8.5 Money Supply

When talking about the money supply (M3), its rationale to put this as a relevant macroeconomic factor. This is the broadest measure of money (comprise M1 and M2) as it is used by economists to estimate the entire supply of money within an economy. Changes in money supply will affect the equilibrium position of money and automatically altering the composition and price of asset in an investor portfolio. Second changes in money supply may impact on real economic variables and having a lagged influence on stock and property stock returns. However, increases in money supply may also give rise to greater inflation uncertainty thus can have an adverse impact on real estate market in Malaysia.

1.8.6 Inflation

When money supplies increase it can give rise in inflation and the economy. It’s generally measured by changes in Consumer Price Index (CPI) which measure the retail prices of several thousand goods and services purchased by household. An increase in inflation it will make an investor refused to put their money to invest in stock.

Summary

This study employs some important macroeconomic factors such as interest rate, GDP growth, money supply and inflation. Analysis is applied to find the significant although positive or negative relationship between them. This paper also represents an important step toward addressing the issue to identification between the macroeconomic environment and the property stock market and the implication to the country.

CHAPTER 2

LITERATURE REVIEW

2.0 Introduction

Stock market gives an important role to economic growth of a country. It is the lifeblood of the economy of a nation that concerns individuals, firms as well as government. However, stock market is a volatile financial market, in which various factors can affect the return that investors can gain from investing in stocks. Any change in such economic variables as real output, money supply, interest rate, inflation and others may affect stock prices through their influences on firms’ cash flows and discount factors. History has shown that, the relationship between macroeconomic variables and of stock market are always being a subject to academics and researchers around the globe. It’s always being done to investigate the relationship between stock market returns and a range of macroeconomic variables.

Many studies have been published about the relationships between stock returns and macroeconomic, Prantik and Vina (2003) study examines what moves Indian stock market which is a study on the linkage with real economy in the post-reform era which used the economic indicator including interest rate, inflation, money supply (M3) in Indian markets between 1994 and 2003. The finding shows that certain variables like the interest rate, output, money supply and inflation rate has considerable influence in the stock market movement in the considered period, while the other variables have very negligible impact on the stock market.

In Turkey, Kandir (2008) had done the investigation with Turkish stock returns. The research was done which is using the data from July 1997 to June 2005 with multiple linear regressions. The variables used in this study including inflation, money supply and interest rate. The result are interest rate seem to affect all of the portfolio returns, while inflation rate is significant for only three of the twelve portfolios. On the other hand, money supply does not appear to have any significant affect on stock returns.

On the other hand, Mehrara (2006) observed that the stock price index is not a leading indicator for economic variables. Iran stock market does not have informational efficiency with money supply. Tursoy, Gunsel, and Rjoub (2008) published his findings that there is no relationship between the macroeconomic variables and stock market return. The researchers tested 13 macroeconomic variables including the variables that will be use in this study against 11 industry portfolios of Istanbul Stock Exchange.

Agrawalla (2005) also found rising prices in the stock market cannot be taken to be a leading indicator of the revival of the economy in India.

On the other hand, (H. Ibrahim and Wan Yusoff, 2001) analyzes dynamic interactions among real output and money supply and equity prices for the Malaysian case using time series techniques of cointegration and vector auto regression. The researcher found that macroeconomic variables improve the predictability of the Malaysian equity prices.

Puah and Jayaraman (2007) study on causal linkages between the Fiji stock price index and the fundamental economic forces. The research found that except for interest rate, all the explanatory variables emerged with expected signs potential macroeconomic variables could provide impact to the emerging stock market in Fiji.

By the evidence from Ghana, Adam and Tweneboah (2008) examines the role of macroeconomic variables on stock prices movement in Ghana. The researcher use the Databank stock index to represent Ghana stock market and inward foreign direct investments, the treasury bill rate (as a measure of interest rates) and the consumer price index (as a measure of inflation) as macroeconomic variables using Johansen's multivariate cointegration test and innovation accounting techniques. They researchers found that inflation explain small proportion of the variation of the share prices compared to interest rate. The researcher suggest that based on the result, potential investors should pay more attention to interest rate rather than inflation.

In Malaysia, Abdul Rahman, Mohd Sidek and Hanim Tafri (2009) shown that the Malaysian stock market is sensitive to changes in the macroeconomic variables. The researcher used vector error correction model with the data range from January 1986 to March 2008. Its show the changes in Malaysian stock market index with changes in money supply and interest rate contribute significantly to the co-integrating relationship.

Morck, Yeung and Yu (1999) has argued that stock prices move together more in poor economies than in rich economies. The researchers found that stock prices in economies with high per capita gross domestic product (GDP) move in a relatively unsynchronized manner. In contrast, stock prices in low per capita GDP economies tend to move up or down together. A time series of stock price for the U.S. market as a develop economy while China, Malaysia and Poland are the emerging market.

Habibullah and Baharumshah (1996) urged that that Malaysia’s stock market is have a relationship to money supply as well as output (GDP). They used monthly data on stock price indices, with money supply and output were employed in this study. The stock price indexes used in this study are Composite, Industrial, Finance, Property, Plantation and Tin. For money supply the researchers used both M1 and M2, and output is measured by real Gross Domestic Product (GDP). The results suggest that Malaysia’s stock market is significantly efficient with respect to money supply as well as output.

2.1 GDP Growth

The study on GDP growth influence property stock market performance importance for the researcher to know the relationship between the total production of Malaysia and the property stock market. There are several researcher has done this kind of research and found the significant finding.

According to Morck et al (1999) stock prices move together more in poor economies than in rich economies. The researchers found that stock prices in economies with high per capita gross domestic product (GDP) have a different move with low per capita GDP. A time series of stock price for the U.S. market as a develop economy while China, Malaysia and Poland are the emerging market. Puah and Jayaraman (2007) analyzed Fiji stock prices index which is elastic with respect to real output. The researcher used Granger causality test indicates that changes in past values in real output could be used to predict the future movement of the stock prices.

H. Ibrahim and Wan Yusoff (2001) analyzes dynamic interactions among real output using Industrial Production as a proxy and money supply and equity prices for the Malaysian case using time series techniques of cointegration and vector auto regression. The researcher found that macroeconomic variables improve the predictability of the Malaysian equity prices.

Despite of giving significant result, Tursoy et al (2008) with their paper has examined the effect 13 macroeconomic variables including the variables that will be use in this study on the portfolios return results. The researchers indicate that macroeconomic factors have not significant effect on stock returns in Istanbul Stock Exchange (ISE). The researchers believe it may affect different industry in different manner by macroeconomic variables.

2.2 Interest Rate

When talking about the interest rate, there are many researcher has done this before. According to Tursoy et al (2008), the regression that has been done resulting that there is no significant pricing relation between the stock return and the interest rate.

Maysami, Hamzah and Howe (2004) found that Singapore stock market and the SES All-S Equities Property Index formed significant relationships with all macroeconomic variables identified including interest rate. The researchers took out the monthly time-series of property indices in Singapore. Humpe and Macmillan (2007) also found American’s data which is consistent with a single cointegrating vector, where stock prices are negatively related to a interest rate.

According to Prantik and Vani (2003), which is the researcher strongly agree that there has been a consistent relationship between certain variables like interest rate with stock price. The researcher believed that the real economic variables continue to affect the stock market in the post-reform era in India but highlight the insignificance of certain variables with respect to stock market.

Adam and Tweneboah (2008) studied the role of macroeconomic variables in stock market movement during period of January 1991 to December 2006. The researchers indicate that interest rate is the key determinant of the share price movements in Ghana. The researcher suggest that based on the result, potential investors should pay more attention to interest rate.

2.3 Money Supply

Many previous result suggest that stock market is informational efficient with respect to money supply. Habibullah and Baharumshah (1996) found that money supply is important in predicting stock prices in Malaysia using both M1 and M2 to represent the money supply. The trivariate cointegration analysis suggests that stock price index and macroeconomic variables in particular money supply are not cointegrated. The researcher believes that stock price index has already incorporated all past information on money supply (M1 and M2).

Rahman et al (2009) found that the government should be cautious with how money supplies are managed since they have influenced the stock price. This study examines the factors that affect the Malaysian stock market from the macroeconomic perspective, the researcher found out the monetary policies variables (proxy by money supply) have significant long run effects on Malaysia’s stock market.

Maysami et al (2004) urged that money supply has nothing to do with the performance of Singapore’s stock market specifically, for the SES All-S Equities Finance Index. The researchers examine the long-term equilibrium relationships between selected macroeconomic variables including money supply and the Singapore stock market index (STI), as well as with various Singapore Exchange Sector indices—the finance index, the property index, and the hotel index.

Agrawalla (2005) found that money supply (M3) is significant at 1% level of confidence in manufacturing of textile, wear and paper industry, manufacturing of food beverage and tobacco respectively. Using January 2001 to September 2005 monthly data the researcher believe that macroeconomic factors have not significant effect on stock returns in Istanbul Stock.

Using a data from equity prices for the period 1998 to 2008 Pakistani capital market reveal that money supply have significant long run effect on equity prices (Hasan and Nasir, 2008). This study facilitates the investors in taking effective investment decisions as by estimating the expected trends in money supply (M3) and, they can estimate the future direction of equity prices and can allocate their resources more efficiently.

2.4 Inflation

The relationship between equity market returns and inflation has been used to investigate in developed markets. Hasan and Nasir (2008) shows that unanticipated inflation was found to explained expected returns during periods of high volatility. Results of ARDL long run coefficients reveal that inflation is statistically insignificant in determining equity prices in long run.

However Ali, Rehman, Yilmaz, Khan and Afzal (2009) found no causal relationship was found between macro-economic indicators and stock exchange prices in Pakistan. Data from June 1990 to December 2008 have been used to analyze the relationship between various macro-economic variables and stock exchange prices. The set of macro-economic indicators including inflation cannot be used to predict stock prices moreover stock prices in Pakistan do not reflect the macro-economic condition of the country.

Prantik and Vani (2003) found that inflation rate has a positive relationship with the interest rate and hence should affect the stock market adversely. Same goes to Schwert (1989), the researcher found that macroeconomic volatility as measured by movements in inflation. For example the volatility of inflation rate during war periods is very high hence stock volatility increase during this period.

Cheng and Tan (2002) found beside the external factor which include the private consumption government expenditure, interest rate and money supply external factor also have a significant influence on Malaysian inflation. Saryal (2007) are using monthly data on the stock price indices of the Turkish stock market (ISE100 index), and the Consumer Price Index (CPI) are obtained from the Istanbul Stock Exchange database available from January 1986 to September 2005. The researcher found that the higher the rate of inflation, the greater the stock market volatility that is higher rates of inflation are coincident with greater stock market risk.

2.5 Summary

Studying the Malaysian context is important in order to provide a deeper understanding of this subject in enhancing a better decision making for the investor and academician. Previous study will help to establish a clear and better understanding on the topic.

CHAPTER 3

METHODOLOGY AND DATA

3.0 Introduction

This chapter will explain the method and data as well as the procedure that will be use in this study. The data collection and method analyzing data are discussed in order to understand the relationship between variables used. The particular chapter focuses on the research methodology that had been used for this research including data collection, sampling frame, theoretical framework and so on .The objective of this study was to gather information on the stock market behaviors specifically in Malaysia. In order to determine the significant of variables the hypothesis will be test to prove the relation. To achieve the above objectives, these studies use the monthly data from property Index from 2000-2010.

3.1 Data Collection

This research basically based on secondary data which mean that data that are previously collected through out other researcher. This is because of secondary data can almost gathered faster than primary data. It’s also just slightly different in term of period of time that has been chosen. Data are collected from published data sources but mostly are from:

Textbook and reference book

Textbook and reference book used in order to understand more deeply about the study. The textbook and reference book provide further deep explanation regarding the topic chosen such as the macroeconomic as well as the methodology of some formula for analysis.

Journals

The journals are the main sources of the research because it’s actually providing a lot of previous study that has been complete by other researcher. It also will help to do the literature reviews which provide the argument from the previous study. Most of the journals are being taken from finance and economic journal.

Website

Data also will be collected throughout the website. This is the technology that must be use 100% and easier to excess through relevant website to find out all supporting information regarding the topic.

3.2 Sampling Frame

This study used FTSE Bursa Malaysia KLCI: Property indices for acceptable result that comprise 88 property companies that represent the property sectors in the Malaysian economy.

3.3 Sources of Data

Data concerning on secondary data will be collected from property indices to proxy for Malaysian property stock market. For the independent variables we limit this study to selected macroeconomic variables which is interest rate (t-bills), GDP (IP), money supply (M3) as well as inflation (CPI). Our monthly data ranged is from 2000 until 2010.

3.4 Variable and Measurement

The variables used in this study can be categorized into two main types which are the dependent and the independent variables.

3.4.1 Dependent Variable

The dependent variable in this research would be the stock performance of property stock in Malaysia which is will be monitor throughout Property index in Malaysia.

3.4.2 Independent Variables

For the independent variable four variable will be choose and be measure. There are interest rate (t-bills), GDP (IP), money supply (M3), interest rate and inflation (CPI). All of this will be collected in monthly basis.

3.5 Research Design

This research is designed to explore the relationship between dependent and independent variables. In this study, it engages in hypotheses testing that will explain the certain significant correlations between property stock market performance and macroeconomic variables

3.5.1 Purpose of the study

In order to understand more about Malaysian stock market behavior this research want to determine the relationship between Malaysian property stock market and macroeconomic variables such as interest rate (t-bills), GDP (IP), money supply (M3) as well as inflation (CPI).

3.5.2 Types of investigation

This research involved the correlation types of investigation in order to understand the relationship between the dependent and independent variables. In this study, all the economic variables will be investigated to determine the existing relationship with property stock index.

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)

Figure I(Cheng & Tan, 2002): Theoretical Framework

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

The analysis of statistical test (T-test) has been used to compares the actual difference between two means in relation to the variation in the data. Correlation analysis is concern with the study of the relation between two variables.

3.8 Hypothesis Statement

In order to fulfill the answer of the research objective, hypothesis were conducted as below:

Hypothesis 1

H0: There is no significant effect between GDP growth and property stock price.

H1: There is significant effect between GDP growth and property stock price.

Hypothesis 2

H0: There is no effect relationship between interest rate and property stock price.

H1: There is significant effect between interest rate and property stock price.

Hypothesis 3

H0: There is no significant effect between money supply (M3) and property stock price.

H1: There is significant effect between money supply (M3) and property stock price.

Hypothesis 4

H0: There is no significant effect between inflation (CPI) and property stock price.

H1: There is significant effect between inflation (CPI) and property stock price.

3.9 Summary

This research will be complete according to the objective where to know whether there is any significant effect between the property stock market performance and macroeconomic variables. The multiple linear regression method was used to examine the relationship between the property market price and relevant macroeconomic variables. The result can indicate the movement and the volatility of the price. This information will perhaps can be used by the investors especially small investors, government, economist or other financial institutions for them to make understand more on Malaysia property stock market and economic. Since study focuses on the data from 2000 until 2010, if would give reliable result on this study.

CHAPTER 4

FINDING

4.0 Introductions

This chapter will discuss the finding of relationship between the macroeconomic variable and Malaysia property stock market performance. Its explains the data analysis, using data from year 2000-2010 with multiple regression as a tool of analysis between dependent and independent variables.

4.1 Multiple Linear Regressions

4.1.1 Descriptive Statistic

Table I: Descriptive Statistic

Descriptive analysis fall into two categories: measures of central tendency (mean) or measures of dispersion (standard deviation). From the table above N represent as a sample in this research while mean is the arithmetic average across the distribution of the data set. The measures of standard deviation are used to determine the consistency of a variable.

The larger the standard deviation, the more spread out the observations are, which explains how widely the values in a data set are spread around the mean. If the variance or standard deviation are large, the data are more dispersed.

4.1.2 Correlation

Table II: Correlation

This research used to explain more on the overall correlation of the relationship among the variables. From the table II its shows the relationship among others 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. Only money supply (M3) and interest rate (t-bills) seems significant relationship with property index.

4.1.3 Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the estimate

1

.569ᵅ

.324

.302

150.07226

Table III: Model Summary

From the table III 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

ANOVA

b

1359396

4

339849.034

15.090

.000

a

2837732

126

22521.684

4197128

130

Regression

Residual

Total

Model

1

Sum of

Squares

df

Mean Square

F

Sig.

Table IV: 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 alternate hypothesis which all the independent variables have significant effect with property index. This means that if it’s greater than 0.05 the model is bust and should not go any further.

4.1.5 Coefficients

Model

Unstandardized coefficients

Standardized coefficients (Beta)

t

Sig.

B

Std. Error

1 (Constant)

IP

CPI

M3

t-bills

6579.368

-.185

-84.685

.003

161.669

893.284

1.705

12.258

.000

33.182

-.012

-3.685

3.832

.409

7.365

-.109

-6.909

7.188

4.872

.000

.914

.000

.000

.000

Table V: Coefficients

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 RM 1, 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 percent, it will cause the property stock market index in Malaysia also increase by 161.699

4.1.6 Hypothesis Selection

By looking at the result from the multiple regressions above, it can conclude that the result from statistical analysis can be accepted:

Hypothesis 1

H0: There is no significant relationship between GDP growth and property stock price.

Hypothesis 2

H1: There is significant relationship between interest rate and property stock price.

Hypothesis 3

H1: There is significant relationship between money supply (M3) and property stock price.

Hypothesis 4

H1: There is significant relationship between inflation (CPI) and property stock price.

Summary

As a conclusion, its shows that three out of four of the macroeconomic variables have an influence on the property stock market index in Malaysia.

CHAPTER 5

CONCLUSION AND RECOMMENDATION

5.0 Conclusion

This research is conducted to discover the factor that can affect the Malaysia Property Index, which includes the relationship between the property stock market performance and the macroeconomic variables. GDP, interest rate, money supply and inflation rate are four independent variables which had been tested by using the multiple linear regression analysis.

In completing this research the limitation comes from the data collected since some of the data are not completed or available for this research. Other than that the limitation faced during this study was difficulty in finding the journal and articles to support the study as well as the time horizon covered is only from 2000 until 2010.

From the analysis, the result shows that there is a significant relationship between macroeconomic variables and property stock market performance in Malaysia but it is not strong enough. It can be seen through the value Anova and the R square is only 32.4%, it’s statically significant but in a weak level. While the adjusted R-squared indicates that about 30.2% of the variability of property index is accounted for by the model even after taking into account the number of independent variables in the model.

Furthermore from the observation of the four different macroeconomic variables coefficient of variation, It’s clearly indicates that there is a significant result because of the reject of the null hypothesis at 5% at significant level except for GDP. This result consistent with the previous study done by Prantik and Vina (2003), Kandir (2008), Tursay et al (2008), Adam and Tweneboah (2008), Mansor and Wan Sulaiman (2001) and Rahman et al (2009).

In this research, GDP seems to give insignificant result based on coefficient table. It maybe because of this research is using Industrial Production as a proxy of GDP monthly. But this research is actually followed the study H. Ibrahim and Wan Yusoff (2001) that using IP as a proxy of GDP because of Malaysia is likely not releasing monthly GDP. Based on the previous study, many researchers found that GDP give a significant result towards stock market. In can be found at study of Morck et al (1999), Puah and Jayaraman (2007), Habibullah and Baharumshah (1996), as well as H. Ibrahim and Wan Yusoff (2001). On the other hand this research is actually follow the result found in study of Mehrara (2006), Tursoy et al (2008), and Agrawalla (2005) which is GDP are not give a significant relationship towards stock market.

On the other hand, money supply seems to give less impact to property index compared to others variables. It’s follow the study of Kandir (2008) found that money supply does not appear to have any significant affect on stock market.

This research come with conclusions, stock market have a significant relationships with the macroeconomic variables identified. Overall from the result reveled, it can be concluded that three out of four main independent variables have influence the Malaysia property stock market performance.

5.1 Recommendation

This study had been conducted covering for the period of 10 years, 2000 to 2010. This research, from the finding and result of the analysis, some recommendation is needed to improve this research in the future.

In order to make this study to be more accurate and reliable, a longer duration of sample is needed such as period of 20 or 30 years. It had been prove that the longer of period of study, the result will be more accurate and reliable. Normally the effect of period of time may shows the accuracy of the result can be simply gained to clarify for the overall performance of this study.

These researches choose to used Multiple Linear Regression instead of using others method. Beside other methods of study such as vector auto regression (VAR), granger causality, error correlation model (ECM) also can be used to investigate the relationship between variables.

For the investor this research perhaps will help them to see how strong the influence of the macroeconomics variables toward property stock market index in Malaysia. For the future researcher, they are advisable to do more research on the other macroeconomic variables. There are several numbers of macroeconomic variables that need to be study in way to see the relationship with property stock market index in Malaysia. By doing more research on other macroeconomic variables, it can help investor to predict the market condition based on variety of macroeconomic variables.

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