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

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  • Cancelo, José Ramón
  • Espasa, Antoni

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.

Suggested Citation

  • Cancelo, José Ramón & Espasa, Antoni, 1996. "Using high-frequency data and time series models to improve yield management," DES - Working Papers. Statistics and Econometrics. WS 4543, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:4543
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    Cited by:

    1. Cancelo, José Ramón & Espasa, Antoni & Grafe, Rosmarie, 2007. "Forecasting from one day to one week ahead for the Spanish system operator," DES - Working Papers. Statistics and Econometrics. WS ws078418, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Espasa, Antoni & Cancelo, José Ramón & Revuelta, J. Manuel, 1996. "Automatic modelling of daily series of economic activity," DES - Working Papers. Statistics and Econometrics. WS 3356, Universidad Carlos III de Madrid. Departamento de Estadística.

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    Keywords

    Calendar effects;

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