Bayesian calibration and number of jump components in electricity spot price models
View/ Open
Volume
65
Pagination
375 - 388 (14)
Publisher
Publisher URL
DOI
10.1016/j.eneco.2017.04.022
Journal
Energy Economics
ISSN
0140-9883
Metadata
Show full item recordAbstract
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.
Authors
Gonzalez, J; MORIARTY, JM; Palczewski, JCollections
- Mathematics [1446]