Bayesian estimation of stable CARMA spot models for electricity prices

Gernot Müller and Armin Seibert

Energy Economics, 2019, vol. 78, issue C, 267-277

Abstract: We develop a Bayesian estimation procedure for the electricity spot price model in Benth et al. (2014). This model incorporates a trend and seasonality component, a stable CARMA process for the price spikes, and an additional Lévy process for mid-range price level changes. Our MCMC algorithm has two advantages over the existing stepwise estimation procedure presented in Benth et al. (2014): First, since our algorithm produces samples from the full posterior distribution over all parameters, we can estimate the parameters much more accurately, which is shown in simulation studies. Second, we can provide accuracy measures as credibility intervals in addition to the point estimates. The approach is quite general, so that it can be adapted also to other similar pricing models. For illustration, we analyse spot and future prices from the EEX using the new Bayesian method and provide estimates for the risk premium together with credibility regions.

Keywords: α -Stable process; CARMA model; Electricity prices; Futures prices; Markov chain Monte Carlo; Seasonality; Stable density approximation (search for similar items in EconPapers)
JEL-codes: C11 C13 C32 C58 G13 Q41 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:78:y:2019:i:c:p:267-277

DOI: 10.1016/j.eneco.2018.10.016

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