Using high-frequency data and time series models to improve yield management

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dc.contributor.author Cancelo, José Ramón
dc.contributor.author Espasa, Antoni
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2009-06-30T07:18:23Z
dc.date.available 2009-06-30T07:18:23Z
dc.date.issued 1996-04
dc.identifier.uri http://hdl.handle.net/10016/4543
dc.description.abstract We show the potential contribution of time series models (TSM) to the analysis of high frequency (less than monthly) time series of economic activity. The evolution of the series is induced by stable patterns of behavior of economic agents; but these patterns are so complex that simple smoothing techniques or subjective forecasting can not consider all underlying factors and TSM are needed if a full efficient analysis is to be carried out. The main ideas are illustrated with an apllication to Spanish daily electricity consumption.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries 1996-31-10
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Calendar effects
dc.subject.other Daily data
dc.subject.other Electricity consumption
dc.subject.other Forecasting
dc.subject.other Weekly seasonality
dc.title Using high-frequency data and time series models to improve yield management
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
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