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A multivariate analysis approach to forecasts combination. Application to Foreign Exchange (FX) markets
dc.contributor.author | Maté Jiménez, Carlos | es-ES |
dc.date.accessioned | 2016-01-15T11:17:35Z | |
dc.date.available | 2016-01-15T11:17:35Z | |
dc.date.issued | 2011-06-01 | es_ES |
dc.identifier.issn | 0120-1751 | es_ES |
dc.identifier.uri | http://hdl.handle.net/11531/5104 | |
dc.description | Artículos en revistas | es_ES |
dc.description.abstract | es-ES | |
dc.description.abstract | Forecasting is characterized by the availability of a lot of methods and the fact that technological and economic forecast horizons are increasingly more different from each other. Combining forecasts is an adequate methodology for handling the above scenario, which is conceptually suitable for the application of several methods of multivariate analysis. This paper reviews some main problems in combining forecasts efficiently from the multivariate analysis view. In particular, a methodology to produce combined forecasts with a large number of forecasts is proposed. The usefulness of such a methodology is assessed in exchange rates forecasting. Further research is suggested for finance as well as for other practical contexts such as energy markets. | en-GB |
dc.format.mimetype | application/pdf | es_ES |
dc.language.iso | en-GB | es_ES |
dc.rights | es_ES | |
dc.rights.uri | es_ES | |
dc.source | Revista: Revista Colombiana de Estadística, Periodo: 1, Volumen: online, Número: 2, Página inicial: 347, Página final: 275 | es_ES |
dc.subject.other | Instituto de Investigación Tecnológica (IIT) | es_ES |
dc.title | A multivariate analysis approach to forecasts combination. Application to Foreign Exchange (FX) markets | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.description.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.rights.holder | es_ES | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es_ES |
dc.keywords | es-ES | |
dc.keywords | Combining forecasting, Factor analysis, Forecasting methodology, Principal components analysis, Time series. | en-GB |
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