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dc.contributor.author
Gudkov, Nikolay
dc.contributor.author
Ignatieva, Katja
dc.date.accessioned
2021-05-07T05:39:36Z
dc.date.available
2021-05-05T04:06:21Z
dc.date.available
2021-05-07T05:39:36Z
dc.date.issued
2021-06
dc.identifier.issn
0140-9883
dc.identifier.issn
1873-6181
dc.identifier.other
10.1016/j.eneco.2021.105260
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/482491
dc.description.abstract
Over the past few years, the electricity derivatives market has experienced a substantial growth in the volume of trade and the diversity of available products. This has led to a rich data environment that requires more sophisticated and accurate modelling approaches for electricity spot prices. This paper deals with an analysis of continuous-time stochastic volatility jump-diffusion processes in the context of pricing of futures contracts written on electricity spots. We formulate a variety of models which aim to capture the most prominent characteristics and stylised facts of the electricity spot market including mean reversion, seasonality, extreme volatility, and spikes. The proposed modelling framework extends the existing models by incorporating mean reversion, stochastic volatility, and jumps in both the underlying spot price process and its volatility. The modelling parameters are estimated using the Markov Chain Monte Carlo (MCMC) technique for the Australian electricity market. We find that incorporating stochastic volatility and jumps in both the underlying electricity spot price and its volatility is absolutely essential to accurately fit the observed electricity spot prices. We derive futures prices in a semi-closed form and confirm flexibility of the proposed models by their ability to fit the observed spot and futures prices in the Australian electricity market.
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.subject
power markets
en_US
dc.subject
electricity spot markets
en_US
dc.subject
electricity modelling
en_US
dc.subject
energy derivatives
en_US
dc.subject
stochastic volatility
en_US
dc.subject
jump diffusion models
en_US
dc.subject
futures pricing
en_US
dc.title
Electricity price modelling with stochastic volatility and jumps: An empirical investigation
en_US
dc.type
Journal Article
dc.date.published
2021-04-05
ethz.journal.title
Energy Economics
ethz.journal.volume
98
en_US
ethz.journal.abbreviated
Energy econ.
ethz.pages.start
105260
en_US
ethz.size
26 p.
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Amsterdam
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02204 - RiskLab / RiskLab
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02003 - Mathematik Selbständige Professuren::09557 - Cheridito, Patrick / Cheridito, Patrick
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02204 - RiskLab / RiskLab
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02003 - Mathematik Selbständige Professuren::09557 - Cheridito, Patrick / Cheridito, Patrick
ethz.date.deposited
2021-05-05T04:06:30Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2021-05-07T05:39:47Z
ethz.rosetta.lastUpdated
2021-05-07T05:39:47Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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