Modeling and forecasting multivariate electricity price spikes

Hans Manner, Dennis Türk and Michael Eichler

Energy Economics, 2016, vol. 60, issue C, 255-265

Abstract: We consider the problem of forecasting the occurrence of extreme prices in the Australian electricity markets from high frequency spot prices. In particular, we are interested in the simultaneous occurrence of such so-called spikes in two or more markets. Our approach is based on a novel dynamic model for multivariate binary outcomes, which allows the latent variables driving these observed outcomes to follow a vector autoregressive process. Furthermore the model is constructed using a copula representation for the joint distribution of the resulting innovations. This has several advantages over the standard multivariate probit model. First, it allows for nonlinear dependence between the error terms. Second, the distribution of the latent errors can be chosen freely. Third, the computational burden can be greatly reduced making estimation feasible in higher dimensions and for large samples. The model is applied to spikes in half-hourly electricity prices in four interconnected Australian markets. The multivariate model provides a superior fit compared to single-equation models and generates better forecasts for spike probabilities. Furthermore, evidence of spillover dynamics between the markets is revealed.

Keywords: Electricity price spikes; Multivariate binary choice models; Copulas; Vector autoregression (search for similar items in EconPapers)
JEL-codes: C32 C35 C53 Q41 Q47 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:60:y:2016:i:c:p:255-265

DOI: 10.1016/j.eneco.2016.10.006

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