Figure 1: Exchange Rate (LNER) and Share Price (LNSP) from Q2 2009 to Q4 2015
Figure 1 illustrate the performance of exchange rate and share price (both are in the natural logarithm form) from the second quarter of 2009 to the fourth quarter of 2015. Based on the figure alone, no decisive conclusion regarding the correlation of the two variables could be formed as there is no consistent trend throughout the period. Table 1 shows that the correlation between share price and exchange rate is 0.3009 when the ordinary covariance analysis is applied to the data series. This suggests the variables are positive correlated over the period but the relationship is relatively weak. However, a positive correlation between the variables indicates a negative comovement between them as the exchange rate is recorded in terms of the number of Australian dollars per US dollar.
Table 1: Result of Correlation Test between LNER and LNSP
4.1 Ordinary Least Square (OLS) Regression
4.1.1 Level Series
When the OLS regression is applied to the equation 1, the result is reported in Table 2. From the table, the t-statistic of intercept and share price are -12.5814 (p = 0.0000) and 12.9807 (p = 0.0000) respectively. These indicate that both explanatory variables are statistically significant and the probability of the coefficients equal zero are very small. Similarly, the F-statistic of 168.4987 (p = 0.0000) suggests that all slope coefficients (excluding the constant) are not equal to zero. Notably, the coefficient of the share price is positive (β1 = 0.3307). As discussed earlier, the exchange rate is written in terms of the number of Australian dollars per US dollar. As a result, an increase in the exchange rate in the model i...
... middle of paper ...
...0.0000) respectively while the Durbin-Watson statistic becomes 2.0425. The higher adjusted R-squared value indicates that more dependent variable is explained by the explanatory variables in the first differences regression compared to the level series regression. In addition, as the Durbin-Watson statistic closes to two, this suggests that there is no autocorrelation in the model. Moreover, the value is higher than the adjusted R-squared value so the regression on the first difference series is probably not spurious.
Therefore, the significant coefficients in the regression model may suggest there is positive relationship between the first difference series of the Australian exchange rate and the Australian share prices. Similar with the level series, this evidence is required to be handled with caution.
Table 3: Results of OLS Regression on First Difference Series
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