DISCUSSION, CONCLUSION AND IMPLICATIONS
5.2 Discussion of Major Findings
Table 55: Summary of Ordinary Least Square
Independen t Variables
Ordinary Least Square
Log(KLSE) Log(SET) Log(IDX) Log(PSE)
Log(CPI)
Significant at 1%
(negative)
Significant at 5%
(negative)
Not Significant
(positive)
Significant at 1%
(negative) Log(ER)
Significant at 1%
(negative)
Not Significant
(negative)
Significant at 1%
(negative)
Significant at 1%
(negative) Log(GDP)
Significant at 1%
(negative)
Not Significant
(positive)
Not Significant
(positive)
Significant at 1%
(positive) Log(IR)
Significant at 1%
(positive)
Not Significant
(positive)
Significant at 1%
(negative)
Not Significant
(positive) Log(M1)
Significant at 1%
(positive)
Significant at 1%
(positive)
Not Significant
(positive)
Not Significant
(negative)
Table 55 presents the major findings and results that derived from the testing done in previous chapter. It clearly explain and show that the corresponding macroeconomic
According to the results, it indicates that there is a negative relationship between Consumer Price Index (CPI) and stock returns which is supported by numerous previous researches such as Hu et al (2000), Cauchie et al (2003), Ahmed et al(2012), Al-Zoubi et al (2011) and Hasan (2008), which have been mentioned in Chapter 2.
From the study above, exchange rate (ER) also shows that there is negative relationship with stock market returns and this applies to all four emerging nations that being analyzed in this paper. This result is supported by Liu et al (2008) and Wong et al (2002). Since these countries involve in the international trades, any fluctuations in exchange rates will lead to certain impacts to both exports and imports.
Gross Domestic Product (GDP) shows that there is a positive relationship with stock market returns and this is proved by Taulbee (2001) who argued that GDP is the proxy of the purchasing power ability of investors and, therefore, higher purchasing power ability will lead to greater stock market performance. However, result shows that there is a negative relationship between Gross Domestic Product (GDP) and FTSE Bursa Malaysia (KLSE). This result can be supported by the studies done by Dimson et al (2002).
According to the result, there is always a negative relationship between interest rate (IR) and stock return and this apply to Indonesia Stock Exchange (Bursa Efek Indonesia, IDX) as result shows a negative relationship between interest rate (IR) and Indonesia Stock Exchange (Bursa Efek Indonesia, IDX). This is supported by the result done by Alam et al. (2009) and he explained that when deposit interest rate increases, userswill tend totransfer their funds or investments from stock market to banks. Interestingly, result for FTSE Bursa Malaysia (KLSE) shows that it has a positive relationship with interest rate (IR) and this can be backed by the research done by Maysami et al (2004).
Shiblee (2009) claims that themovement in the stock prices are mainly set by status of money supply naturallyseems right to agree that increases in the rate of money supply
will lead to an increase in stock prices and this is align with the result of positive relationship with FTSE Bursa Malaysia (KLSE) and The Stock Exchange of Thailand (SET). Money supply increases will lead to a greater liquidity and will eventually bring down the interest rates and hence lead to an increase in aggregate demand and ultimately increase the stock market returns. However, the result of The Philippine Stock Exchange (PSE) shows a negative relationship with money supply and again this is supported by the study completed by Wongbangpo and Sharma (2002) and Theophano and Sunil (2006).
Table 56: Summary of Granger Causality Test
Independent Variables
Granger Causality Test
Log(KLSE) Log(SET) Log(IDX) Log(PSE)
Log(CPI)
Significant at 1%
Significant at
5% Not
Significant Not Significant
Log(ER) Not
Significant Not
Significant Not
Significant Not Significant
Log(GDP) Not
Significant Significant at 1%
Significant at 5%
Not Significant
Log(IR) Not
Significant Significant at
5% Not
Significant Not Significant Log(M1)
Significant at 5%
Significant at 10%
Not Significant
Not Significant
Short run relationship was also studied in this paper using Granger Causality test.
Result shows that the different macroeconomic variables have different short term relationship with different stock markets. It is believed that the short term relationship between these variables are vary for different stock markets and this is due to different countries will be having different situation from time to time.
As per the results, Consumer Price Index (CPI) has significant relationship with FTSE Bursa Malaysia (KLSE) and The Stock Exchange of Thailand (SET) in short run.
As for exchange rate (ER), result shows that there is no relationship between exchange rate (ER) and stock market returns in short run.
Gross Domestic Product (GDP) has significant short run relationship with The Stock Exchange of Thailand (SET) and Indonesia Stock Exchange (Bursa Efek Indonesia, IDX).
In terms of interest rate (IR), it has a short run relationship with The Stock Exchange of Thailand (SET) only.
Lastly, result shows that money supply (M1) is having short run relationship with FTSE Bursa Malaysia (KLSE) and The Stock Exchange of Thailand (SET).
Table 57: Summary of Johansen Cointegration Test
Tests Long-run Relationship Test: Johansen Cointegration Test
Log(KLSE) Log(SET) Log(IDX) Log(PSE)
Trace test Cointegrated at r=0
Cointegrated at
r=0 Cointegrated at r=0 No cointegration Max
Eigenvalu e Test
No cointegration Cointegrated at
r=0 Cointegrated at r=0 No cointegration
The table above shows the long-run relationship between the respective emerging countries’ stock markets and the macroeconomic variables.
Result shows that long-run relationships exist between the independent variables and FTSE Bursa Malaysia. This is in line with the findings from Ibrahim (2003), who
utilized the stock market data from Bursa Malaysia with a set of similar macroeconomic variables.
Result shows that long-run relationships exist between the independent variables and The Stock Exchange of Thailand (SET). This is aligned with the research done by Chowdhury (2004), who observed the long-run relationship between macroeconomic variables and The Stock Exchange of Thailand (SET) from year 1990 until 2003.
Result shows that long-run relationships exist between the independent variables and Indonesia Stock Exchange (Bursa Efek Indonesia, IDX). This result is similar with the analysis done by Abduh and Surur (2013), who investigated the long-run relationship between economic activities and Indonesia Stock Exchange (Bursa Efek Indonesia, IDX).
However, no long-run relationship exists between the independent variables and The Philippines Stock Exchange (PSE) and this is supported by the studies done by Chowdhury (2004), who observed the long-run relationship between macroeconomic variables and The Philippines Stock Exchange (PSE) from year 1990 until 2003.