Modelling price and volatility relationships in the Australian wholesale spot electricity markets using constant and dynamic conditional correlation multivariate GARCH models

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Author(s)
Higgs, Helen
Griffith University Author(s)
Year published
2008
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This 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 (2002) and Engle's (2002) dynamic conditional correlation multivariate GARCH models. Tse and Tsui's (2000) 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 ...
View more >This 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 (2002) and Engle's (2002) dynamic conditional correlation multivariate GARCH models. Tse and Tsui's (2000) 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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View more >This 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 (2002) and Engle's (2002) dynamic conditional correlation multivariate GARCH models. Tse and Tsui's (2000) 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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Conference Title
Proceedings of the 37th Australian Conference of Economists
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Copyright Statement
© 2008 Economic Society of Australia QLD Inc. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Published by Blackwell Publishing Ltd. Please refer to the publisher's website for access to the definitive, published version.
Subject
Time-Series Analysis