IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/20159.html
   My bibliography  Save this paper

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
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/20159/1/MPRA_paper_20159.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    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.
    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. Alberto Cabrero & Gonzalo Camba-Mendez & Astrid Hirsch & Fernando Nieto, 2009. "Modelling the daily banknotes in circulation in the context of the liquidity management of the European Central Bank," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(3), pages 194-217.
    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. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
    7. William A Allen, 2004. "Implementing Monetary Policy," Lectures, Centre for Central Banking Studies, Bank of England, number 4, April.
    8. Maroje Lang & Davor Kunovac & Silvio Basač & Željka Štaudinger, 2008. "Modelling of Currency outside Banks in Croatia," Working Papers 17, The Croatian National Bank, Croatia.
    9. Bindseil, Ulrich & Seitz, Franz, 2001. "The supply and demand for Eurosystem deposits - The first 18 months," Working Paper Series 44, European Central Bank.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Abdul Hadi Abdul Rahim & Muhammad Hafizuddin Hussin & Mohammad Amnan Awang Ali & Muhammad Hanis Roslan & Haslina Hassan & Radhwa Abu Bakar, 2024. "Developing Arabiyatuna Board Game for Engaging Students’ Knowledge Towards the Arabic Language & Culture," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(3s), pages 1325-1330, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mariam El Hamiani Khatat, 2018. "Monetary Policy and Models of Currency Demand," IMF Working Papers 2018/028, International Monetary Fund.
    2. Maroje Lang & Davor Kunovac & Silvio Basač & Željka Štaudinger, 2008. "Modelling of Currency outside Banks in Croatia," Working Papers 17, The Croatian National Bank, Croatia.
    3. Bandholz, Harm & Clostermann, Joerg & Seitz, Franz, 2007. "Explaining the US Bond Yield Conundrum," MPRA Paper 2386, University Library of Munich, Germany.
    4. Antonio Diez De Los Rios, 2009. "Can Affine Term Structure Models Help Us Predict Exchange Rates?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(4), pages 755-766, June.
    5. Alberto Cabrero & Gonzalo Camba-Mendez & Astrid Hirsch & Fernando Nieto, 2009. "Modelling the daily banknotes in circulation in the context of the liquidity management of the European Central Bank," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(3), pages 194-217.
    6. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2024. "Predicting Bond Return Predictability," Management Science, INFORMS, vol. 70(2), pages 931-951, February.
    7. Argyropoulos Efthymios & Tzavalis Elias, 2015. "Term spread regressions of the rational expectations hypothesis of the term structure allowing for risk premium effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 49-70, February.
    8. Benjamin K. Johannsen & Elmar Mertens, 2021. "A Time‐Series Model of Interest Rates with the Effective Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(5), pages 1005-1046, August.
    9. Meredith Beechey & P�r Österholm, 2014. "Policy interest-rate expectations in Sweden: a forecast evaluation," Applied Economics Letters, Taylor & Francis Journals, vol. 21(14), pages 984-991, September.
    10. Zsolt Darvas & Zoltán Schepp, 2007. "Forecasting Exchange Rates of Major Currencies with Long Maturity Forward Rates," Working Papers 0705, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest.
    11. Michael D. Bauer & Glenn D. Rudebusch, 2020. "Interest Rates under Falling Stars," American Economic Review, American Economic Association, vol. 110(5), pages 1316-1354, May.
    12. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    13. Byrne, Joseph & Cao, Shuo & Korobilis, Dimitris, 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," MPRA Paper 63844, University Library of Munich, Germany.
    14. Manolis G. Kavussanos & Ilias D. Visvikis, 2011. "The Predictability of Non-Overlapping Forecasts: Evidence from a New Market," Multinational Finance Journal, Multinational Finance Journal, vol. 15(1-2), pages 125-156, March - J.
    15. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2016. "The Term Premium as a Leading Macroeconomic Indicator," Working Papers 201613, University of Pretoria, Department of Economics.
    16. Onorante, Luca & Pedregal, Diego J. & Pérez, Javier J. & Signorini, Sara, 2010. "The usefulness of infra-annual government cash budgetary data for fiscal forecasting in the euro area," Journal of Policy Modeling, Elsevier, vol. 32(1), pages 98-119, January.
    17. Darvas, Zsolt & Schepp, Zoltán, 2007. "Kelet-közép-európai devizaárfolyamok előrejelzése határidős árfolyamok segítségével [Forecasting the exchange rates of three Central-Eastern European currencies with forward exchange rates]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 501-528.
    18. Michael Wagner, 2010. "Forecasting Daily Demand in Cash Supply Chains," American Journal of Economics and Business Administration, Science Publications, vol. 2(4), pages 377-383, November.
    19. P. Byrne, Joseph & Cao, Shuo & Korobilis, Dimitris, 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-71, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    20. Berardi, Andrea & Plazzi, Alberto, 2022. "Dissecting the yield curve: The international evidence," Journal of Banking & Finance, Elsevier, vol. 134(C).

    More about this item

    Keywords

    Currency in Circulation; Forecasting; Seasonal ARIMA;
    All these keywords.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:20159. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.