A PIT - Based approach to Validation of Electricity Spot Price Models

Abstract: The modeling of electricity spot prices is still in its early stages, with various different competing models being proposed by different researchers. This makes model evaluation and comparison research an important area, for practitioners and researchers alike. However, there is a distinct lack in the literature of consensus regarding model evaluation tools to assess model validity, with different researchers using different methods of varying suitability as validation methods. In this thesis the current landscape of electricity spot price models and how they are currently evaluated is mapped out. Then, as the main contribution this research aims to make, a general and flexible framework for model validation is proposed, based on the Probability Integral Transform (PIT). The probability integral transform, which can be seen as a generalization of analyzing residuals in simple time series and regression models, transforms the realizations of a time series into independent and identically distributed U(0,1) variables using the conditional distributions of the time series. Testing model validity is with this method reduced to testing if the PIT values are independent and identically distributed U(0,1) variables. The thesis is concluded by testing spot price models of varying validity according to previous research using this framework against actual spot price data. These empirical tests suggest that PIT-based model testing does indeed point us toward the more suitable models, with especially unsuitable models being rejected by a large margin.