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...
- 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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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 C22 C53 L94 L98 Q2 |
url |
http://hdl.handle.net/10784/14587 |
identifier_str_mv |
C14 C22 C53 L94 L98 Q2 |
dc.language.iso.eng.fl_str_mv |
eng |
language |
eng |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.local.spa.fl_str_mv |
Acceso abierto |
rights_invalid_str_mv |
Acceso abierto 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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repository.name.fl_str_mv |
Repositorio Institucional Universidad EAFIT |
repository.mail.fl_str_mv |
repositorio@eafit.edu.co |
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1818102388500725760 |