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Recently regime-switching models have become the standard tool for modeling electricity prices. These models capture the main properties of electricity spot prices well but estimation of the model parameters requires computer intensive methods. Moreover, the distribution of the price spikes must be assumed given although the high volatility of the spikes makes it difficult to check this assumption. Consequently, there are a number of competing proposals. Alternatively we propose the use of a semiparametric Markov regime-switching model that does not specify the distribution under the spike regime. To estimate the model we use robust estimation techniques as an alternative to commonly applied estimation approaches. The model in combination with the estimation framework is easier to estimate, needs less computation time and distributional assumptions. To show its advantages we compare the proposed model with a well established Markov-switching model in a simulation-study. Further we apply the model to Australian logprices. The results are in accordance with the results from the simulation-study, indicating that the proposed model might be advantageous whenever the distribution of the spike process is not sufficiently known. The results are thus encouraging and suggest the use of our approach when modeling electricity prices and pricing derivatives.

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