Daily Temperature Modelling for Weather Derivative Pricing - A Comparative Index Forecast Analysis of Adapted Popular Temperature Models

dc.contributor.author	Strömmer-Van Keymeulen, Kim Eva
dc.contributor.department	University of Gothenburg/Department of Economics	eng
dc.contributor.department	Göteborgs universitet/Institutionen för nationalekonomi med statistik	swe
dc.date.accessioned	2013-07-05T07:58:44Z
dc.date.available	2013-07-05T07:58:44Z
dc.date.issued	2013-07-05
dc.description.abstract	This study aims to construct improved daily air temperature models to obtain more precise index values for New York LaGuardia and, thus, more accurate weather derivative prices for contracts written on that location. The study shows that dynamic temperature submodels using a quadratic trend on a 50-year dataset generally produce more accurate forecast results than the studied models that do not. Moreover, the market model outperforms all other models up to 19 months ahead in the future.	sv
dc.identifier.uri	http://hdl.handle.net/2077/33400
dc.language.iso	eng	sv
dc.relation.ispartofseries	201307:52	sv
dc.relation.ispartofseries	Uppsats	sv
dc.setspec.uppsok	SocialBehaviourLaw
dc.title	Daily Temperature Modelling for Weather Derivative Pricing - A Comparative Index Forecast Analysis of Adapted Popular Temperature Models	sv
dc.title.alternative	Daily Temperature Modelling for Weather Derivative Pricing - A Comparative Index Forecast Analysis of Adapted Popular Temperature Models	sv
dc.type	text
dc.type.degree	Student essay
dc.type.uppsok	H1

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