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

Authors: Jose Ramon Cancelo, Antoni Espasa

Addresses: Dpto. Economia Aplicada II, Facultad de Ciencias Economicas y Empresariales, Universidad de La Coruna, Campus de La Zapateira, 15071, La Coruna, Spain. Dpto. Estadistica y Econometria, Facultad de Ciencias Juridicas y Sociales, Universidad Carlos III de Madrid, c/ Madrid 126, 28903 Madrid, Spain

Abstract: High-frequency (less than monthly) time series data provide valuable information for designing the adequate yield policy of the organisation. However, it is not easy to extract this information from raw data; although the evolution of the series is usually induced by stable patterns of behaviour of the economic agents, these patterns are so complex that simple smoothing techniques or subjective forecasting cannot consider all underlying factors. In this paper, we discuss time series models as a tool for carrying out a full and efficient analysis. The main ideas are illustrated with an application to Spanish daily electricity consumption.

Keywords: organisational learning; forecasting; simulation; signal extraction; electricity consumption.

DOI: 10.1504/IJSTM.2001.001591

International Journal of Services Technology and Management, 2001 Vol.2 No.1/2, pp.59-70

Published online: 14 Dec 2003 *

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