In this paper, we present an empirical analysis of deregulated electricity prices.  We begin by examining the distributional and temporal properties of the price process in a non-parametric framework. This analysis is followed by comparing the
forecasting ability of several different statistical models. The findings reveal several characteristics unique to electricity prices including deterministic components of the series at different frequencies and a high degree of persistence in the price level.  An “inverse leverage effect” is also found, where positive shocks to the price series result in larger increases in volatility than negative shocks. Results consistent with other asset prices, such as time-varying volatility are also uncovered. With regards to the forecasting ability of the models, we find that existing financial models of asset prices fail to capture the extremely erratic nature of electricity prices. Non-Markovian specifications in conjunction with exogenous information (e.g. weather) are a necessary starting point for practical applications, such as security pricing.
 

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