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Ignatieva, Katja

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  • Title: Modelling Spot Price Dependence in Australian Electricity Markets with Applications to Risk Management
  • Department Affiliation: Applied Finance and Actuarial Studies
  • Supervisor’s name: Associate Professor Stefan Trueck


Our study is aimed to give a better understanding of the price dynamics in regional electricity spot markets in Australia. We examine the dependence structure between electricity spot prices and apply the results in risk management.


We focus in particular on the dependence between regional prices and conduct a pioneer study on the use of copulas for capturing this dependence structure. Our study yields important insights with respect to joint price movements, extreme price outcomes and the impact of interconnection within the Australian electricity market.

Key Literature/Theoretical Perspective:

  1. Worthington, A., Kay-Spratley, A., Higgs, H., 2005. Transmission of prices and price volatility in Australian electricity spot markets: A multivariate GARCH analysis. Energy Economics 27(2), 337-350.
  2. Higgs, H., 2009. Modelling price and volatility inter-relationships in the Australian wholesale spot electricity markets. Energy Economics 31(5), 748-756.


Our analysis is based on a GARCH approach to model time-varying volatilities of the marginal price series in the considered regions in combination with copulas to capture the dependence structure between the different markets. The performance of copula models is tested in risk management application where we estimate the Value-at-Risk for a stylized portfolios of holding electricity spot contracts in different markets.


We find a positive dependence structure between prices from all of the considered markets with the strongest dependence is exhibited between markets that are well connected via interconnector transmission. The Student-t copula outperforms all other one-parametric copulas whereas the overall best results are obtained using mixture models due to their ability of also capturing asymmetric dependence in the tails of the distribution. Regarding Value-at-Risk applications, we find that due to the spiky and extreme volatile behaviour of electricity spot prices in the considered markets, none of the considered models could provide an appropriate specification of the risk. Still, overall the mixture copula model in combination with Student-t marginals performs best, while the Student-t copula yields results that are only slightly worse. Both models outperform the Gaussian copula model.

Key words:

Electricity markets, copula, dependence modelling, volatility.