Modelling price and volatility inter-relationships in the Australian wholesale spot electricity markets
AbstractThis paper examines the inter-relationships of wholesale spot electricity prices among the four regional electricity markets in the Australian National Electricity Market (NEM): namely, New South Wales, Queensland, South Australia and Victoria using the constant conditional correlation and Tse and Tsui's (Tse, Y.K., Tsui, A.K.C., 2002. A multivariate generalised autoregressive conditional heteroscedasticity model with time-varying correlations. Journal of Business and Economic Statistics 20 (3), 351-362.) and Engle's (Engle, R., 2002. Dynamic conditional correlation: a sample class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics 20 (3), 339-350.) dynamic conditional correlation multivariate GARCH models. Tse and Tsui's (Tse, Y.K., Tsui, A.K.C., 2002. A multivariate generalised autoregressive conditional heteroscedasticity model with time-varying correlations. Journal of Business and Economic Statistics 20 (3), 351-362.) dynamic conditional correlation multivariate GARCH model which takes account of the Student t specification produces the best results. At the univariate GARCH(1,1) level, the mean equations indicate the presence of positive own mean spillovers in all four markets and little evidence of mean spillovers from the other lagged markets. In the dynamic conditional correlation equation, the highest conditional correlations are evident between the well-connected markets indicating the presence of strong interdependence between these markets with weaker interdependence between the not so well-interconnected markets.
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Bibliographic InfoArticle provided by Elsevier in its journal Energy Economics.
Volume (Year): 31 (2009)
Issue (Month): 5 (September)
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Wholesale spot electricity price markets Constant and dynamic conditional correlation Multivariate GARCH;
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