Abstract
Predicting the occurrence of extreme prices, so-called spikes, is one of the greatest challenges when modeling electricity spot prices. Despite the fact that recently new insights have been achieved, the contemporaneous literature seems to be still at its beginning of understanding the dierent mechanisms that drive spike probabilities. We therefore reconsider the problem of forecasting the occurrence of spikes, in the Australian electricity market. For this purpose, we rst discuss properties of the price data with a focus on the occurrence of spikes. We then propose simple models for the probability of spikes which take these properties into account. The models compare favorably for in- and out-of-sample forecasts to a competing approach based on the autoregressive conditional hazard model.
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