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Performance of combined double seasonal univariate time series models for forecasting water demand

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Author Info

  • Jorge Caiado

    (CEMAPRE, School of Economics and Management (ISEG), Technical University of Lisbon)

Abstract

In this article, we examine the daily water demand forecasting performance of double seasonal univariate time series models (Holt-Winters, ARIMA and GARCH) based on multi-step ahead forecast mean squared errors. A within-week seasonal cycle and a within-year seasonal cycle are accommodated in the various model specifications to capture both seasonalities. We investigate whether combining forecasts from different methods for different origins and horizons could improve forecast accuracy. The analysis is made with daily data for water consumption in Granada, Spain.

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File URL: http://cemapre.iseg.utl.pt/archive/preprints/286.pdf
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Bibliographic Info

Paper provided by Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon in its series CEMAPRE Working Papers with number 0903.

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Length: 12 pages
Date of creation: May 2009
Date of revision:
Handle: RePEc:cma:wpaper:0903

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Keywords: ARIMA; Combined forecasts; Double seasonality; Exponential Smoothing; Forecasting; GARCH; Water demand;

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  1. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  2. Sean D. Campbell & Francis X. Diebold, 2003. "Weather Forecasting for Weather Derivatives," NBER Working Papers 10141, National Bureau of Economic Research, Inc.
  3. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
  4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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