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Revista Tinerilor Economiºti (The Young Economists Journal)

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Business Statistics – Economic Informatics<br />

returns on investment of the S&P/ASX200 Index could affect weather conditions. Thus,<br />

the one way relationship between weather variables and return on investment of the<br />

S&P/ASX200 Index has been determined:<br />

ASX 200 t<br />

n<br />

= ∑<br />

n<br />

iTE<br />

t −1<br />

+ ∑ β j ASX t − j + u1<br />

t<br />

i=<br />

1<br />

j = 1<br />

α (6)<br />

ASX 200 tS<br />

n<br />

= ∑<br />

n<br />

iQTE<br />

t −1<br />

+ ∑ β j ASX t − j + u1<br />

t<br />

i=<br />

1<br />

j = 1<br />

α (7)<br />

ASX 200 t<br />

n<br />

= ∑ iWBTE<br />

n<br />

t −1<br />

+ ∑ β j ASX t − j + u1<br />

t<br />

i=<br />

1<br />

j = 1<br />

α (8)<br />

ASX 200 t<br />

n<br />

= ∑<br />

n<br />

iQWBTE<br />

t −1<br />

+ ∑ β j ASX t − j + u1t<br />

i=<br />

1<br />

j = 1<br />

α (9)<br />

ASX 200 t<br />

n<br />

= ∑ i HU<br />

n<br />

t −1<br />

+ ∑ β j ASX t − j + u 1 t<br />

i = 1<br />

j = 1<br />

α (10)<br />

ASX 200 t<br />

n<br />

= ∑ i PRE<br />

n<br />

t −1<br />

+ ∑ β j ASX t − j + u 1t<br />

i = 1<br />

j = 1<br />

α (11)<br />

ASX 200 t<br />

n<br />

= ∑ iVPRE<br />

n<br />

t −1<br />

+ ∑ β j ASX t − j + u 1t<br />

i = 1<br />

j = 1<br />

α (12)<br />

Where, n indicates lags and it is being assumed no relationship (white noise)<br />

and weather variables series error terms (which has not been given in the<br />

between t u1 equation) u2 t (Granger 1969). Granger Causality Test is based on F statistics which<br />

were proven by Wald (Işığıçok, 1994):<br />

( ESS r − ESSur<br />

) / n<br />

Fn;<br />

m−<br />

2n<br />

=<br />

(13)<br />

ESSur<br />

/( m − 2n)<br />

Where, ESS indicates the sum of error terms squares, ur indicates the model<br />

which is unrestricted, while r indicates the model which is restricted.<br />

If the computed F value exceeds the critical F value at the chosen level of<br />

significance (α) with (n;m-2n) degrees of freedom, the null hypothesis (H0) that there is<br />

no causality between the two series should be rejected. So, coefficients (or coefficient)<br />

in the model are statistically significant.<br />

4. EMPIRICAL ANALYSIS<br />

4.1 Descriptive Statistics and Pre-estimation Analysis<br />

<strong>The</strong> descriptive statistics of the weather variables and S&P/ASX200 Index<br />

returns are presented in Table 1. <strong>The</strong> descriptive statistics for weather-related variables<br />

indicates that the average temperature in Australia is around 21oC, maximum is around<br />

39oC and minimum is 8.5oC. <strong>The</strong> minimum of 2.2mb (millibars) and maximum of<br />

62.0mb indicate high changes in atmospheric pressure, but moderate fluctuation in<br />

humidity.<br />

<strong>The</strong> minimum of -6.78 per cent and maximum of 5.89 per cent show that daily<br />

167

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