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Modelling the Currency in Circulation for the State of Qatar

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  • Balli, Faruk
  • Elsamadisy, Elsayed

Abstract

The main concern of this report is to model the daily and weekly forecasting of the currency in circulation (CIC) for the State of Qatar. The time series of daily observations of the CIC is expected to display marked seasonal and cyclical patterns daily, weekly or even monthly basis. We have compared the forecasting performance of typical linear forecasting models, namely the regression model and the seasonal ARIMA model using daily data. We found that seasonal ARIMA model performs better in forecasting CIC, particularly for short-term horizons.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 20159.

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Date of creation: 15 Jan 2010
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Handle: RePEc:pra:mprapa:20159

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Keywords: Currency in Circulation; Forecasting; Seasonal ARIMA;

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  1. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(1), pages 134-44, January.
  2. Bindseil, Ulrich & Seitz, Franz, 2001. "The supply and demand for Eurosystem deposits - The first 18 months," Working Paper Series, European Central Bank 0044, European Central Bank.
  3. Marek Hlavacek & Michael Konak & Josef Cada, 2005. "The Application of Structured Feedforward Neural Networks to the Modelling of Daily Series of Currency in Circulation," Working Papers, Czech National Bank, Research Department 2005/11, Czech National Bank, Research Department.
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