During periods of market stress, electricity prices can rise dramatically. Electricity retailers cannot pass these extreme prices on to customers because of retail price regulation. Improved prediction of these price spikes, therefore, is important for risk management. This paper builds a time-varying-probability Markov-switching model of Queensland electricity prices, aimed particularly at forecasting price spikes. Variables capturing demand and weather patterns are used to drive the transition probabilities. Unlike traditional Markov-switching models, that assume normality of the prices in each state, the model presented here uses a generalized beta distribution to allow for the skewness in the distribution of electricity prices during high-price episodes.
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Paper provided by National Centre for Econometric Research in its series NCER Working Paper Series with number
10.
Find related papers by JEL classification: C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other
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