GARCH-based put option valuation to maximize benefit of wind investors
A method based on Empirical Martingale Simulation (EMS) is presented to evaluate investments in wind energy. Risk-neutral prices are calculated, where electricity market prices are modeled using an ARIMA–GARCH method which shows conditional heteroskedasticity. The values of the put options are calcu...
- Autores:
-
Rodríguez, Jenny Esperanza
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2014
- Institución:
- Universidad ICESI
- Repositorio:
- Repositorio ICESI
- Idioma:
- eng
- OAI Identifier:
- oai:repository.icesi.edu.co:10906/79820
- Acceso en línea:
- http://www.sciencedirect.com/science/article/pii/S0306261914008988
http://hdl.handle.net/10906/79820
http://dx.doi.org/10.1016/j.apenergy.2014.08.085
- Palabra clave:
- Inversiones
Mercado
Simulación
Economía
Negocios y management
Economics
Business
- Rights
- openAccess
- License
- https://creativecommons.org/licenses/by-nc-nd/4.0/
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Rodríguez, Jenny Esperanzayerodriguez@icesi.edu.co2016-08-22T19:32:34Z2016-08-22T19:32:34Z2014-12-01http://www.sciencedirect.com/science/article/pii/S0306261914008988http://hdl.handle.net/10906/79820http://dx.doi.org/10.1016/j.apenergy.2014.08.085instname: Universidad Icesireponame: Biblioteca Digitalrepourl: https://repository.icesi.edu.co/A method based on Empirical Martingale Simulation (EMS) is presented to evaluate investments in wind energy. Risk-neutral prices are calculated, where electricity market prices are modeled using an ARIMA–GARCH method which shows conditional heteroskedasticity. The values of the put options are calculated a week ahead and it is observed that wind producers that invest in the options market can hedge against price risk and can also maximize their benefits. The use of Monte Carlo simulation with the EMS method in periods of high volatility is especially useful for investors facing price volatilities in order to improve their returns. The model is applied to the Colombian electricity market.9 páginasDigitalapplication/pdfengElsevierFacultad de Ciencias Administrativas y EconómicasContaduría Pública y Finanzas InternacionalesDepartamento Contable y FinancieroApplied Energy, Vol. 136 - 2014EL AUTOR, expresa que la obra objeto de la presente autorización es original y la elaboró sin quebrantar ni suplantar los derechos de autor de terceros, y de tal forma, la obra es de su exclusiva autoría y tiene la titularidad sobre éste. PARÁGRAFO: en caso de queja o acción por parte de un tercero referente a los derechos de autor sobre el artículo, folleto o libro en cuestión, EL AUTOR, asumirá la responsabilidad total, y saldrá en defensa de los derechos aquí autorizados; para todos los efectos, la Universidad Icesi actúa como un tercero de buena fe. Esta autorización, permite a la Universidad Icesi, de forma indefinida, para que en los términos establecidos en la Ley 23 de 1982, la Ley 44 de 1993, leyes y jurisprudencia vigente al respecto, haga publicación de este con fines educativos. Toda persona que consulte ya sea la biblioteca o en medio electrónico podrá copiar apartes del texto citando siempre la fuentes, es decir el título del trabajo y el autor.https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)http://purl.org/coar/access_right/c_abf2InversionesMercadoSimulaciónEconomíaNegocios y managementEconomicsBusinessGARCH-based put option valuation to maximize benefit of wind investorsinfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_2df8fbb1Artículoinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85136259268ORIGINALDocumento.htmlDocumento.htmltext/html289http://repository.icesi.edu.co/biblioteca_digital/bitstream/10906/79820/1/Documento.htmlf8e1f0a82f7ea749d820e8172fdaff07MD5110906/79820oai:repository.icesi.edu.co:10906/798202018-10-02 11:56:31.833Biblioteca Digital - Universidad icesicdcriollo@icesi.edu.co |
| dc.title.eng.fl_str_mv |
GARCH-based put option valuation to maximize benefit of wind investors |
| title |
GARCH-based put option valuation to maximize benefit of wind investors |
| spellingShingle |
GARCH-based put option valuation to maximize benefit of wind investors Inversiones Mercado Simulación Economía Negocios y management Economics Business |
| title_short |
GARCH-based put option valuation to maximize benefit of wind investors |
| title_full |
GARCH-based put option valuation to maximize benefit of wind investors |
| title_fullStr |
GARCH-based put option valuation to maximize benefit of wind investors |
| title_full_unstemmed |
GARCH-based put option valuation to maximize benefit of wind investors |
| title_sort |
GARCH-based put option valuation to maximize benefit of wind investors |
| dc.creator.fl_str_mv |
Rodríguez, Jenny Esperanza |
| dc.contributor.author.spa.fl_str_mv |
Rodríguez, Jenny Esperanza |
| dc.subject.spa.fl_str_mv |
Inversiones Mercado Simulación Economía |
| topic |
Inversiones Mercado Simulación Economía Negocios y management Economics Business |
| dc.subject.none.fl_str_mv |
Negocios y management |
| dc.subject.eng.fl_str_mv |
Economics Business |
| description |
A method based on Empirical Martingale Simulation (EMS) is presented to evaluate investments in wind energy. Risk-neutral prices are calculated, where electricity market prices are modeled using an ARIMA–GARCH method which shows conditional heteroskedasticity. The values of the put options are calculated a week ahead and it is observed that wind producers that invest in the options market can hedge against price risk and can also maximize their benefits. The use of Monte Carlo simulation with the EMS method in periods of high volatility is especially useful for investors facing price volatilities in order to improve their returns. The model is applied to the Colombian electricity market. |
| publishDate |
2014 |
| dc.date.issued.none.fl_str_mv |
2014-12-01 |
| dc.date.accessioned.none.fl_str_mv |
2016-08-22T19:32:34Z |
| dc.date.available.none.fl_str_mv |
2016-08-22T19:32:34Z |
| dc.type.eng.fl_str_mv |
info:eu-repo/semantics/article |
| dc.type.coar.none.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.type.local.s.fl_str_mv |
Artículo |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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publishedVersion |
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http://www.sciencedirect.com/science/article/pii/S0306261914008988 |
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http://hdl.handle.net/10906/79820 |
| dc.identifier.doi.none.fl_str_mv |
http://dx.doi.org/10.1016/j.apenergy.2014.08.085 |
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instname: Universidad Icesi |
| dc.identifier.reponame.none.fl_str_mv |
reponame: Biblioteca Digital |
| dc.identifier.repourl.none.fl_str_mv |
repourl: https://repository.icesi.edu.co/ |
| url |
http://www.sciencedirect.com/science/article/pii/S0306261914008988 http://hdl.handle.net/10906/79820 http://dx.doi.org/10.1016/j.apenergy.2014.08.085 |
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instname: Universidad Icesi reponame: Biblioteca Digital repourl: https://repository.icesi.edu.co/ |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.ispartof.eng.fl_str_mv |
Applied Energy, Vol. 136 - 2014 |
| dc.rights.uri.none.fl_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
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info:eu-repo/semantics/openAccess |
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Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) |
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http://purl.org/coar/access_right/c_abf2 |
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https://creativecommons.org/licenses/by-nc-nd/4.0/ Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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9 páginas |
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Digital |
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application/pdf |
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Elsevier |
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Facultad de Ciencias Administrativas y Económicas |
| dc.publisher.program.spa.fl_str_mv |
Contaduría Pública y Finanzas Internacionales |
| dc.publisher.department.spa.fl_str_mv |
Departamento Contable y Financiero |
| institution |
Universidad ICESI |
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