Show simple item record

dc.contributor.authorStrömmer-Van Keymeulen, Kim Eva
dc.date.accessioned2013-07-05T07:58:44Z
dc.date.available2013-07-05T07:58:44Z
dc.date.issued2013-07-05
dc.identifier.urihttp://hdl.handle.net/2077/33400
dc.description.abstractThis 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.language.isoengsv
dc.relation.ispartofseries201307:52sv
dc.relation.ispartofseriesUppsatssv
dc.titleDaily Temperature Modelling for Weather Derivative Pricing - A Comparative Index Forecast Analysis of Adapted Popular Temperature Modelssv
dc.title.alternativeDaily Temperature Modelling for Weather Derivative Pricing - A Comparative Index Forecast Analysis of Adapted Popular Temperature Modelssv
dc.typetext
dc.setspec.uppsokSocialBehaviourLaw
dc.type.uppsokH1
dc.contributor.departmentUniversity of Gothenburg/Department of Economicseng
dc.contributor.departmentGöteborgs universitet/Institutionen för nationalekonomi med statistikswe
dc.type.degreeStudent essay


Files in this item

Thumbnail
Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record