Knowing the real relationship between money market and stock return is very important. The major time lagged effects of money supply on stock return signify informational inadequacy of the stock market. This study proposes to seek the relationship between money market and stock return. The introductory section provides the background for the proposed study reflecting on what the variables are and how they are related. The section also clarifies the research problem, the objectives of the study and hypotheses. Besides, significance of the study and definitions of terms also included.
1.2 Background of study
Many people depend on the stock market as their main source of income while others have their retirement funds tied to the stock market. This shows that performance of the stock market will decide the human being's future. If the stock market is outperformed, this can be a nightmare among the investors. Besides, an increase in performance of stock market will affect the economic activities such as consumption, investment and so on.
Monetary policy is one of the most successful tools that a central bank has at its discarding. In fact, many economists believe monetary policy as the most vital macroeconomic policy. The central bank uses monetary policy often to guide a desired level on the activities. Therefore, it is essential for identify the true relationship between monetary policy, and one vital determinant of the economy, the stock market.
The purpose of this study is to investigate the relationship between monetary policy and the stock market, particularly focusing at the relationship between the money supply and stock market prices.
1.3 Problem Statement
Many research conducted have indicated that there are certain relationship between money supply and stock return. Changes in money supply may influence stock price through changes in inflationary outlook or through portfolio exchange. Besides that, changes in money supply as well may sway stock price through its impact on interest rates. However, these studies were mainly from the developed countries and not many have conducted on emerging market (Christopher M. Bilson et al., 2001).
According to Moyer et al., (2003), stock returns are defined as the price index of the stock during jth minus j-1th period traded at stock exchange. This is supported by the research conducted by Fama and French (1992) Kenneth L. Fisher et al. (2002). Since the economy has the impact on the stock market transaction, the price of the stock will be affected by the demand and supply of the stock if there were any changes that happen in the economy of the world, region or country. For example, during the Asia Financial Crisis that had happened in 1997 whereby stock market in Asian market was in turmoil and demand for stock were affected; the price of stocks fall as the demand decrease.
Singh and Tawlar (1982) found that the causality between monetary and fiscal policies and stock prices has been tested using Granger's procedure (Granger 1989). The results showed that the stock market affected by the money supply changes. It shows that the stock market predict changes in economic activity, both monetary and fiscal policy. Thus, the study stated that fiscal and monetary policies affected by the changes in stock prices.
It seems realistic that many investors require higher expected returns on assets whose returns have higher sensitivities to aggregate liquidity. Liquidation is costlier when liquidity is lower, and those greater costs are especially undesirable to an investor whose wealth has already dropped and who thus has higher marginal utility of wealth.
Sellin (2001) found that the stock price will be affected by money supply if the future monetary policies can be predicted. He stated that a He argues that increase in money supply will lead people to think tight monetary policies in future. This lead to increase in interest rates, increase in discount rates, and the present value of future return declines. As a result, stock prices decline. Furthermore, Sellin (2001) found that decreasing in stock price cause by the outperformed of economic activities such interest rates.
Changes in money supply give valuable information for future output prediction. If the money supply increased, the economic activities will flow smoothly which mean that cash movement in the market is active. Thus, will results stock price to hike (Sellin, 2001). Ben Bernanke and Kenneth Kuttner (2005) suggest that stock price is influenced by the monetary value and the risks that involved during holding the stock.
A stock is valuable if the monetary value is high. An increase in the interest rate would lead increase the discount rate and cause decrease in the value of the stock. This is true if money supply and national output have strong effects on the stock market. In other words, national stock market are found to be informational inefficient with money supply.
The question here is, whether stock price affects money supply or otherwise is an important issue and the answer can only be determined through empirical research.
In summary, the purpose of this study is to clarify the true relationship between money supply and stock return. Besides that, this study also clarifying the position of money supply in investor's decision making. Other than that, this study also explains the relationship between the anticipated and unanticipated changes in money supply with the stock market.
1.4 Research Objectives
Cooper and Schindler (2009) stated that research objectives should express the intention for the study. There are two objectives of the study.
To determine the long run relationship between money supply and stock return.
To determine the causal effect between money supply and stock return.
1.6 Significance of the Study
Significance of this study consists of as followed:
Academician and Researcher
This study can be used as guidance, information and direction for other researchers when doing further investigation in a relevant topic. Academicians to answer all the questions of the particular topic that might exist during their academic teaching also can use this finding. The study will provide a greater overview and practical knowledge for the researcher concerning the movement of the money market instrument in relation of stock return.
Public
This study can be used as general knowledge about the return the will get when purchasing money market instrument.
Investor
This study will provide some benefits for the investors in general towards current stock price, economic condition, liquidity of money market instrument and specific information in details especially in and overcoming their problems and curiosity.
CHAPTER 2
LITERATURE REVIEW
2.1 Introduction
Many research and studies on the relationship between money supply and stock return had been carried out in Malaysia as well as in other countries. Findings and discussions of relationships among related topics in this field of study are summarized in this section.
2.2 Relationship between Money Supply and Stock Return
Many studies had been done regarding to the efficiency of stock markets in the Asian-Pacific region. Among some of these studies consist of those by Cheung and Mak (1992), Cha and Cheung (1993) and Cheung and Ho (1989). Cheung and Mak (1992) and Cha and Cheung (1993) found that some markets in Asia much likely to move closely together with U.S. and Japan. All these studies appear to indicate that the financial markets are included.
Studies on the relationship between money supply and stock return have been given bigger emphasis in the literature. Sprinkel (1964) found that the relationship between money supply and stock return are significant in the United States. Changes in money supply have a positive effect both directly and indirectly on the economic activities, which in turn will determine the stock price position.
A study by Malliaris and Urrutia (1991) on United States; Mookerjee (1987) on stock markets of France, United States, Japan, Italy, Canada, Germany, United Kingdom, the Netherlands, Belgium and Switzerland; and the study by Jeng, et al. (1990) that investigated the stock markets of Belgium, Britain, Canada, Czechoslovakia, France, Hungary, Japan, Poland, Sweden and United States, found that there was a relationship between money supply and stock returns.
Empirical work has provided evidence for the effect of money supply on stock returns. Mukherjee and Nake (1995) argue that money supply have effect on stock prices. Rate of inflation is positively related to money growth rate. As money supply increased, discount rate also increasing. Therefore, the negative effect on stock prices may be offset by the economic stimulus provided by money growth such as corporate earning effect which likely result in increased future cash flows and stock prices.
Increase in monetary growth shows that the cash availability is high. This will lead investors to buy more stocks. This will results higher stock price due to high demand of stock. However, improvement in monetary policy might lead to higher inflation and hence, higher nominal interest. Increase in interest rates will causes increase required rate of return and result low stock price.
The price of a stock is determined discounting back the cash flow with certain discounting rate by using present value method. Money supply has a major relationship with the discount rate and consequently with the present value of cash flows. Sellin (2001) suggested that the money supply affects the stock market prices. Previously these studies are done by Keynesian economists and real activity theorist. Keynesian states that there is a negative relationship between stock prices and money supply.
However, real activity theorists argue that there is a direct relationship between stock price and money supply. The Keynesian economists state that stock price will be influenced by money supply if only change in money supply modify the expectations about future monetary policy. Based on their theories, a positive money supply will encourage people to predict rigid monetary policy in the future. Anticipation of tense monetary policy will steer up the current interest rate.
Interest rate will incline along with discount rate. However, the present value of future earnings fall which lead decreasing in stock price. According to Sellin (2001), economic activities decline due to increase in interest rates, which further depress stock prices. Based on Bernanke and Kuttner (2005), money supply influences the present value of future returns through the movement of interest rate. Tightening the money supply raises the real interest rate. Therefore, an increase in the interest rate leads discount rate to incline.
Decreasing in present value of future return will reduce the stock price. Studies by Sellin (2001) state that change in money supply provide information regarding demand on money. Real economists believe that an increase in money supply relates with increasing in money demand regarding anticipation of increase in economic activity. Higher economic performance implies higher expected profitability, which lead stock prices to increase. Hence, the real activity theorists suggest that there is a positive relationship between money supply and stock price.
Bernanke and Kuttner (2005) found that change in money supply changes and variation in risk premium is inversely related. Tightening the money supply would lead increasing in risk premium. This is because to compensate the investor for holding the risky assets due to economic downfall, which reduces the ability for firms to earn profits. Investors would bear more risks during economic difficulties and hence demand for higher risk premium for holding stocks. They also found that the increasing in risk premium leads declining of stock's price.
A study conducted by Abdullah and Hayworth (1993) and Cheung and Lai (1999), they found that the money supply and stock prices could be related through portfolio swap or inflationary anticipation. In the case, increasing money supply might adjust the other assets in the portfolio. However, increasing in money supply might lead discount rate to hike through inflationary prediction. Thus, this will reduce stock prices.
On the other hand, an increase in money supply could increase the stock prices via the liquidity effect where by higher liquidity in the economy reduces the interest rate and, as a result, stock prices increase. The studies on the Malaysian economy on this topic have also been extensively investigated (e.g., Habibullah, and Baharumshah, 1996; Habibullah et al., 1999; Ibrahim, 1999; and Ibrahim and Aziz, 2003).
By employing the Granger non-causality test of Toda Yamamoto (1995), Habibullah et al. (1999) provide empirical evidence that KLSE stock prices has causal relationships with macroeconomic variables such as division money supply, national in- come, price level, interest rate and real effective exchange rate.
2.3 Argument from other countries
Studied regarding the relationship between money supply and stock return also been done outside Asia. For example, Malliaris and Unutia (1991) found the relationship on United States stock market; Mookerjee (1987) on stock markets of France, United States, Japan, Italy, Canada, Germany, United Kingdom, the Netherlands, Belgium and Switzerland and also the study by Jeng, et al. (1990) that examine the stock markets of Belgium, Britain, Canada, Czechoslovakia, France, Hungary, Japan, Poland, Sweden and United States.
A study by Patra and Poshakwale (2006) in Athen stock exchange, found that there was a relationship between money supply and stock price for both short-run and long-run equilibrium. Azeez and Yonezawa (2006) found that macroeconomic factors as a basic determinant of expected returns. They observed the Japanese stock market through the price of macroeconomic during bubble economic. It enables them to discover which factors are the systematic risks for pre and post stock price. They found that money supply is one of factors that affect the expected returns.
Study done by Sprinkel (1964) concluded that there is strong relationship between the stock market and money supply in the United States. In addition, Flannery and Protopapadakis (2001) studying NYSE-AMEX-NASD suggested that money supply is a strong risk factor where by monetary aggregate (M1) influences both returns and conditional volatility. However, Fama (1981), Geske and Roll (1983) found that stock returns are not related with money supply.
Errunza and Hogan (1998) found that unpredictable of money supply leads volatility in expected return for German and France but not for Italy, Netherlands, UK, Switzerland and Belgium. In addition, Humpe and Macmillan (2007) reported that Japan stock prices are negatively related with money supply however there is positive relationship between US stock prices and the money supply. The results of studies for emerging markets are contradictory.
For Amman Stock Exchange, Maghayereh (2002) suggested that the coefficient of money supply (M1) is unrelated but not statistically significant at the 10 % level, where by Al-Sharkas (2004) argue that money supply (M2) has a positive outcome on stock returns. Maysami et al. (2004) revealed the positive correlation between changes in money supply (M2) and Singapore's stock returns. Abugri (2008) reported that returns to money supply are negatively related and significant in Brazil and Argentina, while contradicted responses of returns to money supply in Mexico and Chile.
Study done by Muradoglu and Metin (1996) indicated that money supply is significantly related to stock returns in short run. In addition, the results of Muradoglu et al. (2001) show no co-integrate relationship between stock prices and any of monetary variables for whole research period (1988- 1995). Karamustafa and Kucukkale (2003), Kandir (2008), and Tursoy et al. (2008) found that the there is no relationship between stock return and money supply.
Besides, Karamustafa and Kucukkale (2003) point out the stock price is neither the result variable nor the cause variable of money supply. Ozturk (2008) suggeted that money supply does not Granger causes the stock returns but the stock returns do Granger causes Central Bank Money. Since the results are contradictory, the real relationship between money supply and stock prices is a pragmatic issue and the consequence varies over countries and time.
A study by Thornton (1993) found that the stock prices likely to correlate with money supply. A study on forecasting share price in Singapore, Mookerje and Yu (1997) found that estimating the share price affected by money supply and exchange rate. On Korean stock market, Hatemi (2002) suggested that it is proficient with respect to incorporating information regarding monetary policy changes.
Mukherjee and Naka (1995) found significant relationship between Japanese stock prices and the short-term interest rates (call money rates). Higher changes in money supply will results higher output productivity. Therefore, the money supply and the stock prices have a positive relationship. In addition, Abdullah and Hayworth (1993) and Mukherjee and Naka (1995) also found a positive relationship between money supply and stock returns for the US and for Japan, respectively.
Dhakal et al. (1993) suggested that changes in the money supply have significant direct and indirect impacts on changes in US stock prices. Previously, money supply guides the stock market, but recently, it is on the other way around. Ho (1983) and Hsiao's (1981) found that money supply the information on money supply is helpful in forecasting stock prices in Hong Kong, Japan, the Philippines, Australia and Thailand.
Sellin, Cornell, Pearce and Roley, Hafer and Hardouvelis (2001) found that stock prices might react differently based on the anticipated and unanticipated component of the money supply. Some economists disagree on the extent to which the market is efficient whereby in an efficient market, all the data available is fixed in the stock price. . Therefore, they disagree that only the unanticipated components that change the money supply would influence the stock market prices.
Previous studies by Husain and Mahmood (1999) found that stock prices are affected towards the changes in money supply in both short and long run. Finding that efficient market hypothesis does not persist, they conclude that stock market is inefficient with the money supply changes, finding that the efficient market hypothesis does not persist.
The question whether stock price leads money supply or otherwise is an important issue and the answer can only be determined through empirical research. In sum, following from the theory and review of literature, this paper seeks to study the following:
Is there a relationship between money supply and stock return? If there is, what is the direction of the relationship? Do the stock returns behave as the Keynesian economists argue or as the real activity theorists argue?
Do stock market returns react differently to the money supply
CHAPTER 3
DATA AND METHODOLOGY
3.1 Introduction
Based on the documented evidence illustrated in the previous chapter, money supply influences stock returns in developed market. To test whether such also recur in a less institutionally advance economy like Malaysia, this study adopted Arbitrage Pricing Theory (APT) and Error Correction Model (ECM) to determine the significant of money supply that influence stock market return and to examine relationship or linkage between stock return and money supply.
There are several appropriate approaches of operating the Arbitrage Pricing Theory (APT) for testing asset pricing in general. They include the Factor Analytic method that is the original procedure, the multiple regression and Full Information Maximum Likelihood (FIML). The multiple regression and FIML may be considered appropriate for pre-specified announcement of money supply. However, due to the time constraint and the simplicity of the approach, the study adopted only the multiple regression method to determine the money supply that significantly influences stock market return.
This study focuses on the empirical research on stock return of Malaysia, Singapore, Thailand, Indonesia and Filipina from year 1988 to 2011 except for Singapore (1982 to 2011). This is done by studying the impact of money supply towards the stock return to the selected country. In this study, money supply data will undergo factor analysis to test the relationship between stock market return and money supply. Annual data will be used instead of monthly data because of the availability of information.
The econometric model used in this research is the multiple linear regressions model to form a linear relationship between stock return and money supply. Stock return will be the dependent variable and money supply will be the independent variable. Stock return will be denominate by percentage of changes in Bursa Malaysia Composite Index (for Malaysia) and various stock indexes over the year. The stock return will be regresses with the independent variable.
3.2 Use of Index
Bursa Malaysia Composite Index (for Malaysia) was used as the dependent variable to represent stock return in Malaysia. Same goes with Singapore, Indonesia, Filipina and Thailand. This is because the composite index is a widely used value for stock return. The Composite Index is computed based on the stock price of one hundred companies. It indicates the movement in the general level of prices of stock listed on Composite Index. Other stock indexes are also used for the purpose of evaluating the impact of money supply on stock return in different sectors.
3.3 Data Descriptions
This empirical research will require some data extraction from internet and government agency resource centre for period of 23 years from 1988 until 2011 among five Asian countries namely Singapore, Malaysia, Thailand, Philippines and Indonesia except Singapore, data required for 29 year (1982 - 2011). The required data are secondary time series from various sources consists of yearly value of the stock market index of the major exchange in each country. Specifically, the index samples include the Singapore Straits Times (Singapore), Kuala Lumpuer Stock Exchange (Malaysia), Bangkok S.E.T (Thailand), Jakarta S.E.T (Indonesia) and Philippines S.E.T (Philippines). The data are obtained from such Bloomberg Database, Economy Report for each countries, the MetaStock database by Equis International and Central Bank for each countries Database. All the collected data will be analyzed using the Bound Test - ARDL Approach: Eview software. Besides the mentioned indexes, money supply being used as independent variables and required time series data for this variable. If necessary, some other factors might be used during the study.
This study used M2 as the money supply variable. M2 refers to the aggregate of currency, demand deposits, other checkable deposits, and travellers' check outstanding, saving deposits and money market deposit account, small time deposits and retail purchase of money market mutual fund (Fisher, 2001). The use of M2 in the model is reliable with the variable used by Sorensen, and Husain and Mahmood in their studies.
3.4 Model Specification
Model specification compromises of the formation of function and model base on the multiple linear regression. To conduct this research, a model is constructed to explain the relationship between money supply and stock return. This was meant to analyze the impact of money supply towards the stock return in selected countries.
Money Supply and Stock Return
3.5.1 Stock Return
The changes in stock indexes in this study will represent the stock return, which were the dependent variable. All this data are in the form of index. Stock indexes that are used in this study are the yearly stock price within the period of study. All the indices will be computed using the formula below as the representative of stock return in selected countries respectively.
Ru = SI1 - SIt-1 x 100
SIt-1
Where Ru is the stock return, SIt is the current stock price index and SIt-1 is the stock price index on the previous year.
Money Supply
Money supply refers to the total supply of money flows in the economy at specific period of time. Money supply in this research is measured by M2. M2 refer to the total of currency in circulation and checkable demand deposits . Most of the research conducted by researches normally used M1 as proxy for money supply [Bilson et al. (2001), Chen et al. (2005) and Bulmash and Trivoli (1991)].
Fama (1981) found that money supply related with stock returns. This is because an increase in movement of money supply will affect the stock returns activity. Stock price might be affected by the movement of money supply through the changes in inflation fluctuation as well as interest rate changes. Some economic experts believe that monetary supply could only explain the reason of increasing in stock prices. Therefore, this shows relationship between money supply and stock returns.
Monetarist states that the increase in money supply initially drives down interest rates, which in turn will stimulate output. However, the gains in lower interest rates and higher output will disappear as prices adjusted. Persistent increase in monetary aggregates will push prices of goods (inflation) and price of credits (interest rates) up. Thus, the study included M2 as a representative of monetary aggregates.
3.6 Method of Analysis
A few tests will be conducted to examine the regression model and its coefficients. This is necessary to ascertain whether the independent variable is significant and whether the model can be accepted. For these reasons, the following tests will be conducted:
3.6.1 Johansen Multivariate Cointegration Test
This test is performed to estimate and provides tests of hypotheses about the number of cointegration relationships. The number of such hypotheses tested match up directly to the number of variables. This analysis purposefully to seek whether one estimated cointegrating relationship is several of another or is a linear mixture of some others. This technique tests three hypotheses about the cointegrating relationship. Johansen and Juselius offer two tests statistically for each hypothesis. The first called trace statistic; secondly the maximum eigen-value statistic. Both are typically conducted by the econometrics software (Eview 7.0). There is not much explanation to choose one over the other. They often lead to the equal conclusion. If none of the three hypotheses are discarded, perhaps the regression is bogus. If the first hypothesis rejected, there is only one cointegrating correlation. If all the hypotheses are rejected, it shows that none of the variables have stochastic movement after all, because that is the only way there could be as cointegrating relationship as variables. Below is the equation that shows the first cointegration relationship.
This reveals the fact that error correction variable estimated earlier. Next is the corresponding cointegrating relationship.
The dependant variable in the equation is Y. The choice of which variable in a cointegrating relationship gets a coefficient of one is arbitrary. Variables are cointegrated if they are incorporated of the same order and a linear combination of then are stationary. Such linear mixture would then point to the existence of a long-term relationship between the variables (Jihansen & Julselius, 1990). The long run relationship between these variables are observed based on the cointegration procedure propose by Johansen-Juselius (1990).
3.6.2 Granger Causality Test
This test used to identify whether the causality relationship is exits between money supply and stock returns. The approach is expressed in two pairs of regression equation by simply twisting independent and dependent variables as follows.
(1)
(2)
Where,
Y = Stock market for selected countries
MS = Money Supply (M2)
T = time
According to Granger's definition of causality MS does not cause stock prices, if the past value of MS fails to explain the change in stock prices. To judge as whether these conditions hold the F-statistic were applied to equation 1 relative to equation 2.
F = [(R2UR - R2R) / m] / [(1 - R2) UR) / (n -2m-1)]
Where,
R2UR = Sum square of the unrestricted equation
R2R = Sum square of the restricted equation
N = number of observation
M = number of regressors
Four possible direction of causality may occur; MS causes stock prices, stock prices causes MS, bidirectional/feedback causality or MS and stock prices are independent.
CHAPTER 4
FINDINGS
4.1 Introduction
This chapter presents the empirical results of the relationship between money supply and stock return for the five selected countries in Asia namely Indonesia, Singapore, Philippines, Thailand and Malaysia. If the meaningful relationship were observed in this study, it implies that the changes in money supply will be reflected in stock prices. Thus, these results will give some policy implication in the efforts to improve the present stock markets in the long run. To observe the relationship between money supply and stock return, yearly data is used in the analysis.
In this study, we employed the Multi Index in terms of the R Square and Durbin Watson Test to examine the relationship between money supply and stock return. Besides, Cointegration tests also being applied to identify the relationship between variables in the long run. The results and discussion will follow the sequence of the above-mentioned methodology in Chapter 3 except for Augmented Dickey Fuller test and Phillips Perron test.
Firstly, the result obtained from the MIM (R Square and Durbin Watson test) being discussed and then cointegration model was used to analyse the relationship between money supply and sock return.
4.2 Multi Index Model (R Square and Durbin Watson)
Table 1: Summary Results on R Square and Durbin Watson test
COUNTRIES
R SQUARE
DURBIN WATSON
SINGAPORE
0.3825
1.7871
MALAYSIA
0.6208
1.8976
THAILAND
0.2764
1.8925
PHILIPPINES
0.3363
1.9054
INDONESIA
0.7544
2.0313
Table 1 shows that even it is significantly statistic, the explanatory power of the MIM in five Asian countries in this study was not so high. Cheng (1995) stated that the APT able to clarify 11% of variability of stock return of the U.K stocks. Cheng (1995) found that a low explanatory of APT is caused by three factors. First, risk and expected returns may not be stationary over the period. Second, APT-pricing relationship could grasp only in some months of the year and lastly, the opportunity of non-linear pricing correlation.
In this study the result shows considerable variation, ranging from a high of 75.44% for Indonesia to a low of 27.64% for Thailand, with intermediate ranking being in order from highest to lowest, Malaysia (62.08%), Singapore (38.25%) and Philippines (33.63%). The study also shown that, the explanatory power (R2) indicated that much efficient country tend to be very much influenced by money supply movement. The study utilised the auto-correlation test by using Durbin Watson test to examine for the existence of auto-correlation in the data. If the results are below than 2.0 and close to zero, it shows that the residuals have a positive correlation with the previous data. On the other hand, if the results are more than 2.0 and close to 4.0, the residuals are found to have negative correlation with the previous data. The Durbin Watson test shows that the results of the variables are below 2.0 in which indicates that the residuals are having an auto-correlation except for Indonesia where the result was 2.0313. The result clearly showed that auto-correlation existed present during period of study.
4.3 Co-integration Tests
The cointegration test is conducted to examine the long run co-movements for money supply and stock market returns. In this study, Johansen (1988), and Johansen and Juselius (1990) multivariate cointegration method used to analysis for the existence or absence of cointegration relationships between money supply and stock price. To carry out the test, it requires variables not to be 1(2) but can admit both 1(0) only and a mixture of 1(1) and 1(0). The results for cointegration tests based on maximum eigenvalues of stochastic matrix for each of the five Asian markets are presented in Table 2.
Table 2: Summary of Johansen Multivariate Co - Integration Test
Singapore
Variables: Straits Times Index, Money Supply (M2)
H0
Eigenvalues
Trace Statistic
5% Critical Value
1% Critical Value
P=0
P≤1
0.3137
0.0129
10.9049
0.3638
15.41
3.76
20.04
6.65
Notes: P indicates the number of cointegrating vectors.
Malaysia
Variables: KLSE, Money Supply (M2)
H0
Eigenvalues
Trace Statistic
5% Critical Value
1% Critical Value
P=0
P≤1
0.6613
0.0926
25.9537
2.1385
15.41
3.76
20.04
6.65
Notes: P indicates the number of cointegrating vectors.
Thailand
Variables: Bangkok Stock Exchange, Money Supply (M2)
H0
Eigenvalues
Trace Statistic
5% Critical Value
1% Critical Value
P=0
P≤1
0.2734
0.1044
9.4518
2.4253
15.41
3.76
20.04
6.65
Notes: P indicates the number of cointegrating vectors.
Philippines
Variables: Philippines Stock Exchange, Money Supply (M2)
H0
Eigenvalues
Trace Statistic
5% Critical Value
1% Critical Value
P=0
P≤1
0.4945
0.2275
20.6852
5.6775
15.41
3.76
20.04
6.65
Notes: P indicates the number of cointegrating vectors.
Indonesia
Variables: Jakarta Stock Exchange, Money Supply (M2)
H0
Eigenvalues
Trace Statistic
5% Critical Value
1% Critical Value
P=0
P≤1
0.3305
0.0006
8.8407
0.0121
15.41
3.76
20.04
6.65
Notes: P indicates the number of cointegrating vectors.
Singapore: The maximum eigenvalues (λ max) result is different from zero. Thus, the null hypothesis of no cointegrating relationship is rejected. The empirical results suggest that Singapore's money supply and stock return were co-integrated in the long-run.
Malaysia: For Malaysia, max λ are significant at 5% level for at least single cointegration vector hypothesis (r ≤ 1). Therefore, the null hypothesis is rejected. Therefore, Malaysia stock markets are cointegrated with money supply.
Thailand: The Maximum eignevalue test confirms the non-zero vector among the variables. The null hypothesis that there is no cointegration relationship among Thailand's money supply is rejected, at most one cointegrating vectors during the period 1988 to 2011.
Philippines: The Johansen Juselius test was reliable on rejecting the null hypothesis of non-cointegration in Philippines. This empirical result suggests that the Indonesia money supply and stock returns were co-integrated in the long run.
Indonesia: Table 2 shows that λ max statistic are significant at 5% level for at least single cointegarting vector analysis (r ≤ 1). The test shows that we can reject the null hypothesis at least a single cointegrating vector and accept the alternative hypothesis. The results suggest that money supply is strongly integrated with Indonesia's stock markets.
4.4 Granger Causality Test
The Granger-causality test is applicableif stationarity existed between variables. However, if variables are non-stationarity, first differenced used to identify the causal relationship. Using first differencing, valuable information concerning the long-run equilibrium properties of the data could be lost. Cointegration tests are meant to solve this problem and indeed provide valid estimation of long run relationship between different variables. Below is the summary result of the tests.
Table 3: F-STATISTICS FOR GRANGER CAUSALITY ANALYSIS
SINGAPORE
Null Hypothesis:
F-Statistic
Prob.
MS does not Granger Cause Stock Return
6.30122
0.0186
Stock Return does not Granger Cause MS
6.48779
0.0171
MALAYSIA
Null Hypothesis:
F-Statistic
Prob.
MS does not Granger Cause Stock Return
0.78398
0.5588
Stock Return does not Granger Cause MS
0.93950
0.4768
THAILAND
Null Hypothesis:
F-Statistic
Prob.
MS does not Granger Cause Stock Return
0.80962
0.3789
Stock Return does not Granger Cause MS
0.79480
0.3833
PHILIPPINES
Null Hypothesis:
F-Statistic
Prob.
MS does not Granger Cause Stock Return
0.02101
0.8862
Stock Return does not Granger Cause MS
3.22067
0.0878
INDONESIA
Null Hypothesis:
F-Statistic
Prob.
MS does not Granger Cause Stock Return
4.61570
0.0441
Stock Return does not Granger Cause MS
5.02861
0.0364
The summary results of the Granger causality are presented in Table 7. The null hypothesis states that there is no causation between the two variables. It can be concluded that in all cases the null hypothesis of money supply does not Granger causes stock markets could be rejecting meaning to say that money supply significantly explains the changes that occurs in stock prices. To test the reverse causality from stock price to money supply, the money had been made as the dependent variable.
The F statistics for testing the reverse causation indicates that we could strongly reject the null hypothesis that stock markets do not cause money supply. As a conclusion the Granger causality analysis indicates the strong existence of bi-directional causation running from money supply to stock returns and stock returns to money supply. Indeed this result is consistent with the other research which noted the expansionary effect of monetary policy on stock returns.
In summary, the result of the Johansen Juselius cointegration tests fails to reject the null hypothesis of zero cointegrating vectors in all countries in this study. From the empirical results, it suggests the presence of correlation between stock price and money supply in the long run. This result is similar with the study done by Fauzias, Norazlan and Zaidi (1999) who agreed that there is a long run relationship among the Malaysian stock market with money supply. Study done by Nasseh and Strauss (2000) also found that there is a long-run relationship exists between stock price and money supply in Europe.
As a conclusion, the result of the Granger casuality shows that there is bidirectional relationship between stock return activity and the changes in money supply in Asia. Therefore, stock returns which precisely affected by the changes of stock prices are grounded in economic basics, influenced by money supply.
CHAPTER 5
CONCLUSION AND RECOMMENDATION
5.1 Introduction
Many studies in the past have indicated that a relationship does exist between money supply and equity market return. But not all have significant explanatory power towards stock return for different countries. This is because different countries have different rhythm of performance and development which cannot be explained by the variability of the money supply. This paper extended to find out the relationship that exists between money supply and stock return from different countries namely Malaysia, Thailand, Singapore, Philippines, and Indonesia.
This is done by using Principal Component Analysis and Regression using E-View Software. Correlation matrix for independent variable (money supply) is computed to determine the level of correlation and the significance level to identify the level of multi-collinerity. Variable will be regress against the stock return from different countries from 1988 to 2011, except for Singapore from 1982 to 2011. The result of this research indicates that money supply do play an important role in stock return for all the countries being selected.
In summary, it is worthwhile to note that the efficient countries (Malaysia and Singapore) and less efficient countries (Thailand, Philippines and Indonesia) stock market are reflected on money supply on its stock prices, but the stock price movements are different from each other. These relationships between money supply and stock returns are important findings to understand the behaviour of stock price and thus, it will help the policy makers to implement stock stabilization.
5.2 Implication and Suggestion
The study highlighted that the money supply could be crucial factors of determinants of stock returns in efficient countries. The policy that could maintain the crucial level of those variables is needed in obtaining a sustainable stock market in these countries. Clearly, money supply is among the most important determinants of financial decision. The financial theory of interest emphasized savings and investments demand as interest rate determinants, while the liquidity preference theory points to demand and supply of cash advance.
5.3 Limitation of Study
There are several improvement needed in this research as this research have weakness from the data collection method, methodology or the analysis tools. First of all, most of the researches in the past have used monthly stock return instead of annual stock return and the research should incorporate a longer period of time. This may result a better result compare to the annually return for 23 years in this research. However, due to the time constraint and the availability of data, this research could only use annual data instead of monthly data. Besides, the time that was used in this research included outlier is the Financial Crisis in 1977 which may affect the consistency of the result of this research.
Secondly, the result would be more accurate if more variables are included such as GDP, tax rate, political risk, exchange rate and dividend yield where we can evaluate the impact of money supply towards stock return accurately among the selected countries. Besides, certain test to determine the accountability of the research was unable to be conducted due to lack of size (observation) and time.
Furthermore, the method of analysis may not be appropriate as there are many other ways to conduct this research such as GARCH model, event studies, Vector Auto-Regression Moving Average (VARMA) model, autoregressive conditional heteroscedasity (ARCH) model and others. This is more complicated by ways of understand and applying the models planned by the finance literature, which happen to be out of my expertise. However, most of the problems occurred are solved by referring to the research done by C.M. Bilson et al. (2001) with a little modification. This is much useful for research of this paper with the environment in ASEAN region since there are limitation of data and time to carry out this research.
Lastly, variation of the availability of the data at Bursa Malaysia (for Malaysia) and stock index for certain years. Different figures come up in different report by the government agency and government bodies. This will delay the search from achieving precision and consistency for researchers. This problem also happens for other countries (Indonesia, Philippines, Singapore, and Thailand).
5.4 Recommendation for Future Research
The study only examines the existence of relationship between money supply and stock market for different countries. It does not cover certain areas in finance research such as the announcement effect of the money supply towards stock return and the difference effect of other independent variables towards stock return. Such researches are needed in order to understand the behaviour of the stock return which will benefit investors, researchers, and regulators in the future.
In addition, investigation on the variability of the stock price towards money supply is strongly recommended as the stock prices have a direct effect on the stock return in the selected countries. Thus, several areas for future research were also identified. These are outlined as follows:
This study is basically focused only on five Asian countries. Future research may extend the analysis to include international data such as for developed countries, developing countries and less developed countries.
This study found that the money supply found to have significant effect on stock prices; a more detailed study on this variable may be useful for investors and policy makers in cross border investment, and in structuring a sound policy.
A comprehensive study of the relationship between money supply and stock prices can be carried over a longer time period, for instance from 1960 to 2011. This will give a better idea on the impact of this variable and different methods should be used as measurement in determine the relationship between money supply and stock market.
