Gonzalez, J, Moriarty, J and Palczewski, J orcid.org/0000-0003-0235-8746 (2017) Bayesian calibration and number of jump components in electricity spot price models. Energy Economics, 65. pp. 375-388. ISSN 0140-9883
Abstract
We find empirical evidence that mean-reverting jump processes are not statistically adequate to model electricity spot price spikes but independent, signed sums of such processes are statistically adequate. Further we demonstrate a change in the composition of these sums after a major economic event. This is achieved by developing a Markov Chain Monte Carlo (MCMC) procedure for Bayesian model calibration and a Bayesian assessment of model adequacy (posterior predictive checking). In particular we determine the number of signed mean-reverting jump components required in the APXUK and EEX markets, in time periods both before and after the recent global financial crises. Statistically, consistent structural changes occur across both markets, with a reduction of the intensity and size, or the disappearance, of positive price spikes in the later period. All code and data are provided to enable replication of results.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 Elsevier B.V. This is an author produced version of a paper published in Energy Economics. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Multi-factor models; Bayesian calibration; Markov Chain Monte Carlo; Ornstein-Uhlenbeck process; Electricity spot price; Negative jumps |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 May 2017 14:36 |
Last Modified: | 03 Nov 2018 01:38 |
Published Version: | https://doi.org/10.1016/j.eneco.2017.04.022 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.eneco.2017.04.022 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:94785 |