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Modelling the Currency in Circulation for the State of Qatar

Author

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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.

Suggested Citation

  • Balli, Faruk & Elsamadisy, Elsayed, 2010. "Modelling the Currency in Circulation for the State of Qatar," MPRA Paper 20159, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:20159
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    References listed on IDEAS

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    1. 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 2005/11, Czech National Bank, Research and Statistics Department.
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    5. Naoto Kunitomo & Makoto Takaoka, 2002. "On RegARIMA Model, RegSSARMA Model and Seasonality," CIRJE F-Series CIRJE-F-146, CIRJE, Faculty of Economics, University of Tokyo.
    6. William A Allen, 2004. "Implementing Monetary Policy," Lectures, Centre for Central Banking Studies, Bank of England, number 4, April.
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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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