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Forecasting with quantitative methods the impact of special events in time series


Nikolopoulos, Konstantinos


Bitte beziehen Sie sich beim Zitieren dieses Dokumentes immer auf folgenden Persistent Identifier (PID):http://nbn-resolving.de/urn:nbn:de:0168-ssoar-241672

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Abstract Quantitative methods are very successful for producing baseline forecasts of time series; however these models fail to forecast neither the timing nor the impact of special events such as promotions or strikes. In most of the cases the timing of such events is not known so they are usually referred as shocks (economics) or special events (forecasting). Sometimes the timing of such events is known a priori (i.e. a future promotion); but even then the impact of the forthcoming event is hard to estimate. Forecasters prefer to use their own judgment for adjusting for forthcoming special events, but humans’ efficiency in such tasks has been found to be deficient. This study after examining the relative performance of Artificial Neural Networks, Multiple Linear Regression and Nearest Neighbor approaches proposes an expert method which combines the strengths of regression and artificial intelligence.
Sprache Dokument Englisch
Publikationsjahr 2010
Seitenangabe S. 947-955
Zeitschriftentitel Applied Economics, 42 (2010) 8
DOI http://dx.doi.org/10.1080/00036840701721042
Status Postprint; begutachtet (peer reviewed)
Lizenz PEER Licence Agreement (applicable only to documents from PEER project)