Model adequacy was again verified using the methods applied in 5.4 and as the lagged GARCH terms are very significant we can confirm volatility clustering is again present in this time series. 5.62 is greater in the winter than in the summer, this is because the high marginal cost of ‘Volatility natural gas production and the inelastic winter mean that shocks of even a small magnitude can cause a large price swings’ Suenaga et al (2006). Four new variables were generated, each indicative of a weather season. (Equation 44), Winter (Equation 45), (Equation 46) and (Equation 47) dummy variables were Spring Summer Autumn constructed and are defined below. Equation Equation Equation Equation In initial testing the coefficient of was found not to be statistically significant, this variable ‘Autumn’ was dropped from the analysis and regression model re-run, this is shown below in Equation 48. Equation Equation Where denotes spot volatility (defined in Equation 22). Table 17 displays the estimated coefficients and their significant levels (95% Conf.). Summer and Spring were found to be very significant, and Winter and WSDummy were found to be significant. Spot Coefficients Std. Err. t Robust S.E Robust t VIF Volatility 0.0207614 0.0050475 8.03 0.0051286 4.05 Equation 48 -0.0063683 0.0031445 -2.03 0.0038773 -1.64 1.80 -0.0088985 0.0035025 -2.54 0.0029643 -3.00 1.71
Model adequacy was again verified using the methods applied in 5.4 and as the lagged GARCH terms are very significant we can confirm volatility clustering is again present in this time series. 5.62 ‘Volatility is greater in the winter than in the summer, this is because the high marginal cost of natural gas production and the inelastic winter mean that shocks of even a small magnitude can cause a large price swings’ Suenaga et al (2006). Four new variables were generated, each indicative of a weather season. Winter (Equation 44), Spring (Equation 45), Summer (Equation 46) and Autumn (Equation 47) dummy variables were constructed and are defined below. Equation Equation Equation Equation In initial testing the coefficient of ‘Autumn’ was found not to be statistically significant, this variable was dropped from the analysis and regression model re-run, this is shown below in Equation 48. Equation Equation Where denotes spot volatility (defined in Equation 22). Table 17 displays the estimated coefficients and their significant levels (95% Conf.). Summer and Spring were found to be very significant, and Winter and WSDummy were found to be significant. Spot Volatility Coefficients Std. Err. t Robust S.E Robust t VIF Equation 48 0.0207614 0.0050475 8.03 0.0051286 4.05 -0.0063683 0.0031445 -2.03 0.0038773 -1.64 1.80 -0.0088985 0.0035025 -2.54 0.0029643 -3.00 1.71
Alec_Horton_Dissertation.docx