FINDINGS AND ANALYSIS
P- Value Result Independent Variable
4.7 Variance Decomposition
Hypothesis 4
H0: There is no relationship between stock market returns of The Philippine Stock Exchange (PSE) and interest rate (IR).
H1: There is a relationship between stock market returns of The Philippine Stock Exchange (PSE) and interest rate (IR).
Table 41 shows that PSE is not affected by IR. This is due to P-value of IR (0.9270) is not significant at 10% significance level and this also means that IR does not has Granger cause impact on PSE. Thus, this study will not reject H0 and there is no relationship between stock return of PSE and interest rate in short run.
Hypothesis 5
H0: There is no relationship between stock market returns of The Philippine Stock Exchange (PSE) and money supply (M1).
H1: There is a relationship between stock market returns of The Philippine Stock Exchange (PSE) and money supply (M1).
Result in Table 41 shows that P-value of M1 (0.3758) is not significant at 10% significant level. Thus, this study will not reject H0 and there is no short term relationship between stock return of PSE and money supply.
Variance decomposition determines the amount of information that contributed by each variables to one another in an auto-regression. It verifies how much of the forecast error variance of each variable can be explained by exogenous shocks to other variables (Brooks, 2008).
4.7.1 FTSE Bursa Malaysia (KLSE)
Table 42: Variance Decomposition of Log(KLSE) towards Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1)
Perio
d S.E. CPI ER GDP IR M1 KLCI
1 0.624899 0.000000 0.000000 0.000000 0.000000 0.000000 100.0000 2 0.897602 4.442400 0.236227 0.249426 0.840920 4.539218 89.69181 3 1.053333 7.762350 1.251321 0.700411 1.268518 5.661452 83.35595 4 1.206485 7.756893 1.754412 0.802556 1.886315 6.342476 81.45735 5 1.375096 7.306911 1.777736 0.802721 2.268323 6.894088 80.95022 6 1.545235 7.659336 1.747459 0.834958 2.312430 7.168248 80.27757 7 1.700269 8.770503 1.745665 0.910983 2.289942 7.146299 79.13661 8 1.830135 10.27163 1.759649 0.984122 2.374731 7.010168 77.59971 9 1.936809 11.59214 1.776312 1.035196 2.559191 6.869891 76.16727 10 2.029342 12.33614 1.767028 1.078617 2.763331 6.733055 75.32183
Hypothesis:
H0: Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1) do not have an impact on stock return of FTSE Bursa Malaysia (KLSE).
H1: Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1) have impact on stock
return of FTSE Bursa Malaysia (KLSE).
From the result above, it shows that shock in exchange rate has a smaller impact of 0.236227 percent in KLSEin period 2 (short run). However, Consumer Price Index (CPI) has a larger impact of 12.33614 percent on KLSEin period 10 (long run).
On the other hand, from the data, it indicates that the shock on independent variable to dependent variable gets greater as it risesgradually from Period 1 to Period 10.
Generally, it is believed that the impacts of independent variable in short run is minimal and can see larger impact in the long run on dependent variable.
Therefore, this paper rejectsH0and concludes that the selected macroeconomic variables have impacts on stock market returns of FTSE Bursa Malaysia (KLSE).
4.7.2 The Stock Exchange of Thailand (SET)
Table 43: Variance Decomposition of Log(SET) towards Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1)
Perio
d S.E. CPI ER GDP IR M1 SET
1 0.785125 0.000000 0.000000 0.000000 0.000000 0.000000 100.0000 2 1.225581 2.272917 0.324451 5.844149 0.665269 2.193643 88.69957 3 1.534560 9.951370 0.808555 7.682945 0.980105 8.711119 71.86591 4 1.761004 17.17116 0.662929 6.724602 1.136182 13.21128 61.09385 5 1.946082 19.96773 1.715851 6.196467 1.484035 15.06870 55.56721 6 2.109496 20.15923 3.368694 6.683399 1.934361 16.35446 51.49985 7 2.251283 19.82437 4.295741 7.597037 2.209048 18.21586 47.85794 8 2.371633 19.58966 4.607700 8.630860 2.284690 20.34314 44.54396 9 2.479313 19.40275 4.697836 9.661923 2.303651 22.08638 41.84746 10 2.583648 19.14887 4.677638 10.51870 2.345160 23.48500 39.82463
Hypothesis:
H0: Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1) do not have an impact on stock return of The Stock Exchange of Thailand (SET).
H1: Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1) has an impact on stock return of The Stock Exchange of Thailand (SET).
From result, t shows that shock in exchange rate has a smaller impact of 0.324451 percent in SET in period 2 (short run). However, money supply (M1) has a larger impact of 23.48500 percent on SET in period 10 (long run).
On the other hand, from the data, it indicates that the impacts on independent
variable to dependent variable getlarger as it rises gradually from Period 1 to Period 10.
Generally, it is believed that the impacts of independent variable in short run is minimal and can see larger impact in the long run on dependent variable.
Therefore, this paper rejects H0 and concludes that the selected macroeconomic variables have impacts on stock market returns of The Stock Exchange of Thailand (SET).
4.7.3 Indonesia Stock Exchange (Bursa Efek Indonesia, IDX)
Table 44: Variance Decomposition of Log(IDX) towards Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1)
Perio
d S.E. CPI ER GDP IR M1 IDX
1 0.943006 0.000000 0.000000 0.000000 0.000000 0.000000 100.0000 2 1.234363 1.383350 0.652153 1.977485 0.870425 0.068381 95.04821 3 1.409893 1.979865 1.388787 11.47368 1.724159 0.869101 82.56440 4 1.566303 1.752370 1.592533 18.15365 2.259125 0.748195 75.49413 5 1.727891 1.675532 1.811095 19.91139 2.303263 1.002248 73.29647 6 1.887340 1.865358 2.074036 20.30410 2.254157 1.596519 71.90583 7 2.032440 2.272380 2.389638 20.41939 2.393773 2.179172 70.34565 8 2.158012 2.700790 2.809554 20.36613 2.610999 2.697928 68.81460 9 2.264434 2.956879 3.414328 20.23455 2.721945 3.091607 67.58069 10 2.356305 3.021906 4.180969 20.12561 2.691737 3.335199 66.64458
Hypothesis:
H0: Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1) do not have an impact on stock return of Indonesia Stock Exchange (Bursa Efek Indonesia, IDX).
H1: Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1) has an impact on stock return of Indonesia Stock Exchange (Bursa Efek Indonesia, IDX).
From the data above, the result shows that shock in money supply (M1) has a smaller impact of 0.0683481 percent in IDX in period 2 (short run). However, Gross Domestic Product (GDP) has a larger impact of 20.12561 percent on IDX in period 10 (long run).
On the other hand, from the data, it indicates that the impact on independent variable to dependent variable is getting greater as it increases gradually.
Generally, it is believed that the impact of independent variable in short run is minimal and can see larger impact in the long run on dependent variable.
Therefore, this paper rejects H0 and concludes that the selected macroeconomic variables have impacts on stock market returns of Indonesia Stock Exchange (Bursa Efek Indonesia, IDX).
4.7.4 The Philippine Stock Exchange (PSE)
Table 45: Variance Decomposition of Log(PSE) towards Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1)
Perio
d S.E. CPI ER GDP IR M1 PSE
1 0.683857 0.000000 0.000000 0.000000 0.000000 0.000000 100.0000 2 1.097985 1.967344 0.043433 0.003171 0.352930 0.893164 96.73996 3 1.410066 3.333321 0.465321 0.003487 0.469256 1.365036 94.36358 4 1.683030 4.059460 1.333894 0.062267 0.409415 1.199178 92.93579
5 1.939998 4.689291 2.510198 0.264780 0.364747 1.100617 91.07037 6 2.188009 5.386441 3.808583 0.544328 0.391699 1.401786 88.46716 7 2.429404 6.131203 5.080606 0.788029 0.479326 2.139467 85.38137 8 2.664078 6.870522 6.228821 0.944825 0.605214 3.213480 82.13714 9 2.890470 7.571759 7.206604 1.018071 0.750842 4.464039 78.98868 10 3.106860 8.221094 8.009596 1.032715 0.904375 5.736653 76.09557
Hypothesis:
H0: Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1) do not have an impact on stock return of The Philippine Stock Exchange (PSE).
H1: Log(CPI), Log(ER), Log(GDP), Log(IR), Log(M1) has an impact on stock return of The Philippine Stock Exchange (PSE).
From the data above, the result shows that shock in money supply (M1) has a smaller impact of 0.003171 percent in PSE in period 2 (short run). However, Consumer Price Index (CPI) has a larger impact of 8.221094 percent on PSE in period 10 (long run).
On the contrary, from the data, it indicates that the impact on independent variable to dependent variable gets greater as it rises gradually from Period 1 to Period 10.
Generally, it is believed that the shocks of independent variable in short run is minimal and can see larger impact in the long run on dependent variable.
Therefore, this paper rejects H0 and concludes that the selected macroeconomic variables have impacts on stock market returns of The Philippine Stock Exchange (PSE).