Modeling the electricity spot price with switching regime semi-nonparametric distributions

Spot prices of electricity in liberalized markets feature seasonality, mean reversion, random short-term jumps, skewness and highly kurtosis, as a result from the interaction between the supply and demand and the physical restrictions for transportation and storage. To account for such stylized fact...

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Autores:
Trespalacios, Alfredo
Cortés, Lina M.
Perote, Javier
Tipo de recurso:
Fecha de publicación:
2019
Institución:
Universidad EAFIT
Repositorio:
Repositorio EAFIT
Idioma:
eng
OAI Identifier:
oai:repository.eafit.edu.co:10784/14587
Acceso en línea:
http://hdl.handle.net/10784/14587
Palabra clave:
Electricity markets
Gram-Charlier series
switching regime models
Ornstein–Uhlembeck process
Rights
License
Acceso abierto
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spelling Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees2019-11-25T15:54:50Z2019-11-222019-11-25T15:54:50Zhttp://hdl.handle.net/10784/14587C14C22C53L94L98Q2Spot prices of electricity in liberalized markets feature seasonality, mean reversion, random short-term jumps, skewness and highly kurtosis, as a result from the interaction between the supply and demand and the physical restrictions for transportation and storage. To account for such stylized facts, we propose a stochastic process with a component of mean reversion and switching regime to represent the dynamics of the spot price of electricity and its logarithm. The short-term movements are represented by semi-nonparametric (SNP) distributions, in contrast to previous studies that traditionally assume Gaussian processes. The application is done for the Colombian electricity market, where El Niño phenomenon represents an additional source of risk that should be considered to guarantee long-term supply, sustainability of investments and efficiency of prices. We show that the switching regime model with SNP distributions for the random components outperforms traditional models leading to accurate estimates and simulations, and thus being a useful tool for risk management and policy making.engUniversidad EAFITEscuela de Economía y FinanzasModeling the electricity spot price with switching regime semi-nonparametric distributionsworkingPaperinfo:eu-repo/semantics/workingPaperDocumento de trabajo de investigacióndrafthttp://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_8042Acceso abiertohttp://purl.org/coar/access_right/c_abf2Electricity marketsGram-Charlier seriesswitching regime modelsOrnstein–Uhlembeck processalfredotrespalacios@itm.edu.coTrespalacios, Alfredo1bb5aa38-54d2-410e-953d-42e8de035219-1Cortés, Lina M.d512530b-e532-45b9-baa6-ab16fae407ac-1Perote, Javier87d7d691-7fbd-4383-b605-58196730b574-1LICENSElicense.txtlicense.txttext/plain; charset=utf-82556https://repository.eafit.edu.co/bitstreams/96ce7f34-8c18-4f60-b898-512f46123060/download76025f86b095439b7ac65b367055d40cMD51ORIGINALWP-2019-14-Lina M. Cortés.pdfWP-2019-14-Lina M. Cortés.pdfapplication/pdf2397973https://repository.eafit.edu.co/bitstreams/4266b06b-a977-4e2b-acb3-015294b61aaf/download19d0b3e3285bb2a26c99aa5bf27646deMD5210784/14587oai:repository.eafit.edu.co:10784/145872024-12-04 11:47:35.333open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.co
dc.title.eng.fl_str_mv Modeling the electricity spot price with switching regime semi-nonparametric distributions
title Modeling the electricity spot price with switching regime semi-nonparametric distributions
spellingShingle Modeling the electricity spot price with switching regime semi-nonparametric distributions
Electricity markets
Gram-Charlier series
switching regime models
Ornstein–Uhlembeck process
title_short Modeling the electricity spot price with switching regime semi-nonparametric distributions
title_full Modeling the electricity spot price with switching regime semi-nonparametric distributions
title_fullStr Modeling the electricity spot price with switching regime semi-nonparametric distributions
title_full_unstemmed Modeling the electricity spot price with switching regime semi-nonparametric distributions
title_sort Modeling the electricity spot price with switching regime semi-nonparametric distributions
dc.creator.fl_str_mv Trespalacios, Alfredo
Cortés, Lina M.
Perote, Javier
dc.contributor.eafitauthor.none.fl_str_mv alfredotrespalacios@itm.edu.co
dc.contributor.author.none.fl_str_mv Trespalacios, Alfredo
Cortés, Lina M.
Perote, Javier
dc.subject.keyword.spa.fl_str_mv Electricity markets
Gram-Charlier series
switching regime models
Ornstein–Uhlembeck process
topic Electricity markets
Gram-Charlier series
switching regime models
Ornstein–Uhlembeck process
description Spot prices of electricity in liberalized markets feature seasonality, mean reversion, random short-term jumps, skewness and highly kurtosis, as a result from the interaction between the supply and demand and the physical restrictions for transportation and storage. To account for such stylized facts, we propose a stochastic process with a component of mean reversion and switching regime to represent the dynamics of the spot price of electricity and its logarithm. The short-term movements are represented by semi-nonparametric (SNP) distributions, in contrast to previous studies that traditionally assume Gaussian processes. The application is done for the Colombian electricity market, where El Niño phenomenon represents an additional source of risk that should be considered to guarantee long-term supply, sustainability of investments and efficiency of prices. We show that the switching regime model with SNP distributions for the random components outperforms traditional models leading to accurate estimates and simulations, and thus being a useful tool for risk management and policy making.
publishDate 2019
dc.date.available.none.fl_str_mv 2019-11-25T15:54:50Z
dc.date.issued.none.fl_str_mv 2019-11-22
dc.date.accessioned.none.fl_str_mv 2019-11-25T15:54:50Z
dc.type.eng.fl_str_mv workingPaper
info:eu-repo/semantics/workingPaper
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_b1a7d7d4d402bcce
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_8042
dc.type.local.spa.fl_str_mv Documento de trabajo de investigación
dc.type.hasVersion.eng.fl_str_mv draft
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10784/14587
dc.identifier.jel.none.fl_str_mv C14
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url http://hdl.handle.net/10784/14587
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dc.language.iso.eng.fl_str_mv eng
language eng
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http://purl.org/coar/access_right/c_abf2
dc.coverage.spatial.eng.fl_str_mv Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees
dc.publisher.spa.fl_str_mv Universidad EAFIT
dc.publisher.department.spa.fl_str_mv Escuela de Economía y Finanzas
institution Universidad EAFIT
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