Modelling the currency in circulation for the State of Qatar
AbstractPurpose – This paper seeks to model the daily and weekly forecasting of the currency in circulation (CIC) for the State of Qatar. Design/methodology/approach – The paper employs linear forecasting models, the regression model and the seasonal ARIMA model to forecast the CIC for Qatar. Findings – Comparing the linear methods, the seasonal ARIMA model provides better estimates for short-term forecasts. The range of forecast errors for the seasonal ARIMA model forecasts are less than 100 million QR for the short-term CIC forecasts. Practical implications – The findings of this paper suggest that the CIC in Qatar is in a pattern and it would be easier to forecast the currency in circulation in Qatar economy. Accurate estimates of money market liquidity would help Qatar Central bank, to maintain the price stability in the Qatar economy. Originality/value – This paper forecasts the currency in circulation for the State of Qatar. Additionally, the empirical part of the paper compares the different methodologies find the appropriate model for the CIC for the state of Qatar.
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Bibliographic InfoArticle provided by Emerald Group Publishing in its journal International Journal of Islamic and Middle Eastern Finance and Management.
Volume (Year): 5 (2012)
Issue (Month): 4 (December)
Contact details of provider:
Web page: http://www.emeraldinsight.com
Postal: Emerald Group Publishing, Howard House, Wagon Lane, Bingley, BD16 1WA, UK
Other versions of this item:
- Balli, Faruk & Elsamadisy, Elsayed, 2010. "Modelling the Currency in Circulation for the State of Qatar," MPRA Paper 20159, University Library of Munich, Germany.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
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- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
- Bindseil, Ulrich & Seitz, Franz, 2001. "The supply and demand for Eurosystem deposits - The first 18 months," Working Paper Series 0044, European Central Bank.
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