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Modelling the Currency in Circulation for the State of Qatar

Author

Listed:
  • 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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    File URL: https://mpra.ub.uni-muenchen.de/20159/1/MPRA_paper_20159.pdf
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    References listed on IDEAS

    as
    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 Department.
    2. Riaz Riazuddin & Mahmood ul Hasan Khan, 2005. "Detection and Forecasting of Islamic Calendar Effects in Time series Data," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 1, pages 25-34.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. Bindseil, Ulrich & Seitz, Franz, 2001. "The supply and demand for Eurosystem deposits - The first 18 months," Working Paper Series 0044, European Central Bank.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Currency in Circulation; Forecasting; Seasonal ARIMA;

    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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