IDEAS home Printed from https://ideas.repec.org/a/bla/scotjp/v58y2011i1p127-152.html
   My bibliography  Save this article

Forecasting The Uk/Us Exchange Rate With Divisia Monetary Models And Neural Networks

Author

Listed:
  • Rakesh K. Bissoondeeal
  • Michail Karoglou
  • Alicia M. Gazely

Abstract

This paper compares the UK/US exchange rate forecasting performance of linear and nonlinear models based on monetary fundamentals, to a random walk (RW) model. Structural breaks are identified and taken into account. The exchange rate forecasting framework is also used for assessing the relative merits of the official Simple Sum and the weighted Divisia measures of money. Overall, there are four main findings. First, the majority of the models with fundamentals are able to beat the RW model in forecasting the UK/US exchange rate. Second, the most accurate forecasts of the UK/US exchange rate are obtained with a nonlinear model. Third, taking into account structural breaks reveals that the Divisia aggregate performs better than its Simple Sum counterpart. Finally, Divisia-based models provide more accurate forecasts than Simple Sum‐based models provided they are constructed within a nonlinear framework.

Suggested Citation

  • Rakesh K. Bissoondeeal & Michail Karoglou & Alicia M. Gazely, 2011. "Forecasting The Uk/Us Exchange Rate With Divisia Monetary Models And Neural Networks," Scottish Journal of Political Economy, Scottish Economic Society, vol. 58(1), pages 127-152, February.
    • Handle: RePEc:bla:scotjp:v:58:y:2011:i:1:p:127-152
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1467-9485.2010.00538.x
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    2. Michael Frenkel & Isabell Koske, 2004. "How well can monetary factors explain the exchange rate of the euro?," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 32(3), pages 233-244, September.
    3. Frenkel, Jacob A, 1976. " A Monetary Approach to the Exchange Rate: Doctrinal Aspects and Empirical Evidence," Scandinavian Journal of Economics, Wiley Blackwell, vol. 78(2), pages 200-224.
    4. Church, Keith B. & Curram, Stephen P., 1996. "Forecasting consumers' expenditure: A comparison between econometric and neural network models," International Journal of Forecasting, Elsevier, vol. 12(2), pages 255-267, June.
    5. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
    6. Elger, Thomas & Jones, Barry E. & Nilsson, Birger, 2006. "Forecasting with Monetary Aggregates: Recent Evidence for the United States," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 428-446.
    7. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    8. Barnett, William A., 1980. "Economic monetary aggregates--reply," Journal of Econometrics, Elsevier, vol. 14(1), pages 57-59, September.
    9. Philip Hans Franses & Paul van Homelen, 1998. "On forecasting exchange rates using neural networks," Applied Financial Economics, Taylor & Francis Journals, vol. 8(6), pages 589-596.
    10. Michail Karoglou, 2010. "Breaking down the non-normality of stock returns," The European Journal of Finance, Taylor & Francis Journals, vol. 16(1), pages 79-95.
    11. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    12. Dornbusch, Rudiger, 1976. "Expectations and Exchange Rate Dynamics," Journal of Political Economy, University of Chicago Press, vol. 84(6), pages 1161-1176, December.
    13. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    14. Rakesh Bissoondeeal & Jane Binner & Thomas Elger, 2009. "Monetary models of exchange rates and sweep programs," Applied Financial Economics, Taylor & Francis Journals, vol. 19(14), pages 1117-1129.
    15. 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.
    16. Jane Binner & Rakesh Bissoondeeal & Thomas Elger & Alicia Gazely & Andrew Mullineux, 2005. "A comparison of linear forecasting models and neural networks: an application to Euro inflation and Euro Divisia," Applied Economics, Taylor & Francis Journals, vol. 37(6), pages 665-680.
    17. Smith, P N & Wickens, M R, 1986. "An Empirical Investigation into the Causes of Failure of the Monetary Model of the Exchange Rate," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(2), pages 143-162, April.
    18. Belongia, Michael T & Chrystal, K Alec, 1991. "An Admissible Monetary Aggregate for the United Kingdom," The Review of Economics and Statistics, MIT Press, vol. 73(3), pages 497-503, August.
    19. McCrae, Michael, et al, 2002. "Can Cointegration-Based Forecasting Outperform Univariate Models? An Application to Asian Exchange Rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(5), pages 355-380, August.
    20. Frankel, Jeffrey A, 1979. "On the Mark: A Theory of Floating Exchange Rates Based on Real Interest Differentials," American Economic Review, American Economic Association, vol. 69(4), pages 610-622, September.
    21. Chrystal, K. Alec & MacDonald, Ronald, 1995. "Exchange rates, financial innovation and divisia money: the sterling/dollar rate 1972-1990," Journal of International Money and Finance, Elsevier, vol. 14(4), pages 493-513, August.
    22. Franses Philip Hans & van Griensven Kasper, 1998. "Forecasting Exchange Rates Using Neural Networks for Technical Trading Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(4), pages 1-8, January.
    23. Joseph Plasmans & William Verkooijen & Hennie Daniels, 1998. "Estimating structural exchange rate models by artificial neural networks," Applied Financial Economics, Taylor & Francis Journals, vol. 8(5), pages 541-551.
    24. Drake, Leigh & Chrystal, K Alec, 1994. "Company-Sector Money Demand: New Evidence on the Existence of a Stable Long-Run Relationship for the United Kingdom," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 26(3), pages 479-494, August.
    25. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    26. Engel, Charles & Hamilton, James D, 1990. "Long Swings in the Dollar: Are They in the Data and Do Markets Know It?," American Economic Review, American Economic Association, vol. 80(4), pages 689-713, September.
    27. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    28. William A. Barnett, 2000. "The User Cost of Money," Contributions to Economic Analysis, in: The Theory of Monetary Aggregation, pages 6-10, Emerald Group Publishing Limited.
    29. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    30. Rakesh K. Bissoondeeal & Jane M. Binner & Muddun Bhuruth & Alicia Gazely & Veemadevi P. Mootanah, 2008. "Forecasting exchange rates with linear and nonlinear models," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 10(4), pages 414-429.
    31. Drake, Leigh & Chrystal, K Alec, 1997. "Personal Sector Money Demand in the UK," Oxford Economic Papers, Oxford University Press, vol. 49(2), pages 188-206, April.
    32. Taylor, Mark P. & Peel, David A., 2000. "Nonlinear adjustment, long-run equilibrium and exchange rate fundamentals," Journal of International Money and Finance, Elsevier, vol. 19(1), pages 33-53, February.
    33. Qi, Min & Wu, Yangru, 2003. "Nonlinear prediction of exchange rates with monetary fundamentals," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 623-640, December.
    34. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-218, March.
    35. Nag, Ashok K & Mitra, Amit, 2002. "Forecasting Daily Foreign Exchange Rates Using Genetically Optimized Neural Networks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(7), pages 501-511, November.
    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. Huseyin Ince & Ali Fehim Cebeci & Salih Zeki Imamoglu, 2019. "An Artificial Neural Network-Based Approach to the Monetary Model of Exchange Rate," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 817-831, February.
    2. Somayeh Kokabisaghi & Mohammadesmaeil Ezazi & Reza Tehrani & Nourmohammad Yaghoubi, 2019. "Sanction or Financial Crisis? An Artificial Neural Network-Based Approach to model the impact of oil price volatility on Stock and industry indices," Papers 1912.04015, arXiv.org, revised Sep 2020.
    3. Rakesh Bissoondeeal & Michail Karoglou & Andy Mullineux, 2014. "Breaks in the UK Household Sector Money Demand Function," Manchester School, University of Manchester, vol. 82, pages 47-68, December.
    4. Supanee Harnphattananusorn, 2020. "Relationship between Thai Baht and Oil Price: A Neural Network Model," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 371-376.
    5. Mustafa Ozer & Veysel Inal & Mustafa Kirca, 0. "The Relationship Between the Health Services Price Index and The Real Effective Exchange Rate Index in Turkey: A Frequency Domain Causality Analysis," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(36), pages 21-41, June.

    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. Yuan, Chunming, 2011. "The exchange rate and macroeconomic determinants: Time-varying transitional dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 22(2), pages 197-220, August.
    2. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    3. Mylonidis, Nikolaos & Stamopoulou, Ioanna, 2011. "The role of monetary policy in managing the euro - dollar exchange rate," MPRA Paper 29291, University Library of Munich, Germany.
    4. Joscha Beckmann & Ansgar Belke & Michael Kühl, 2009. "How Stable Are Monetary Models of the Dollar-Euro Exchange Rate? - A Time-varying Coefficient Approach," Ruhr Economic Papers 0134, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    5. Joscha Beckmann & Ansgar Belke & Michael Kühl, 2009. "How Stable Are Monetary Models of the Dollar-Euro Exchange Rate?: A Time-Varying Coefficient Approach," Discussion Papers of DIW Berlin 944, DIW Berlin, German Institute for Economic Research.
    6. Ahmad Zubaidi Baharumshah & Liew Khim Sen & Lim Kian Ping, 2003. "Exchange Rates Forecasting Model: An Alternative Estimation Procedure," International Finance 0307005, University Library of Munich, Germany.
    7. repec:zbw:rwirep:0134 is not listed on IDEAS
    8. Rakesh Bissoondeeal & Michail Karoglou & Andy Mullineux, 2014. "Breaks in the UK Household Sector Money Demand Function," Manchester School, University of Manchester, vol. 82, pages 47-68, December.
    9. Levent KORAP, 2008. "Exchange Rate Determination Of Tl/Us$:A Co-Integration Approach," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 7(1), pages 24-50, May.
    10. Engel, Charles, 2014. "Exchange Rates and Interest Parity," Handbook of International Economics, in: Gopinath, G. & Helpman, . & Rogoff, K. (ed.), Handbook of International Economics, edition 1, volume 4, chapter 0, pages 453-522, Elsevier.
    11. Cheung, Yin-Wong & Chinn, Menzie D. & Pascual, Antonio Garcia & Zhang, Yi, 2019. "Exchange rate prediction redux: New models, new data, new currencies," Journal of International Money and Finance, Elsevier, vol. 95(C), pages 332-362.
    12. Kenneth Rogoff, 2009. "Exchange rates in the modern floating era: what do we really know?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 145(1), pages 1-12, April.
    13. Joscha Beckmann & Ansgar Belke & Michael Kühl, 2011. "Cointegration, structural breaks and monetary fundamentals of the Dollar/Yen Exchange," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 17(4), pages 397-412, November.
    14. Joscha Beckmann & Ansgar Belke & Michael Kühl, 2011. "The dollar-euro exchange rate and macroeconomic fundamentals: a time-varying coefficient approach," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 147(1), pages 11-40, April.
    15. Habimana, Olivier, 2017. "The multiscale relationship between exchange rates and fundamentals differentials: Empirical evidence from Scandinavia," MPRA Paper 75956, University Library of Munich, Germany.
    16. Wang, Jian-Xin & Wong, Hoi-In, 1997. "The predictability of Asian exchange rates: evidence from Kalman filter and ARCH estimations," Journal of Multinational Financial Management, Elsevier, vol. 7(3), pages 231-252, October.
    17. Dimitris A. Georgoutsos & Georgios P. Kouretas, 2017. "The Relevance of the Monetary Model for the Euro / USD Exchange Rate Determination: a Long Run Perspective," Open Economies Review, Springer, vol. 28(5), pages 989-1010, November.
    18. Jane Binner & Rakesh Bissoondeeal & Thomas Elger & Alicia Gazely & Andrew Mullineux, 2005. "A comparison of linear forecasting models and neural networks: an application to Euro inflation and Euro Divisia," Applied Economics, Taylor & Francis Journals, vol. 37(6), pages 665-680.
    19. Samuel W. Malone & Robert B. Gramacy & Enrique Ter Horst, 2016. "Timing Foreign Exchange Markets," Econometrics, MDPI, vol. 4(1), pages 1-23, March.
    20. Xie, Zixiong & Chen, Shyh-Wei, 2019. "Exchange rates and fundamentals: A bootstrap panel data analysis," Economic Modelling, Elsevier, vol. 78(C), pages 209-224.
    21. Hina, Hafsa & Qayyum, Abdul, 2015. "Exchange Rate Determination and Out of Sample Forecasting: Cointegration Analysis," MPRA Paper 61997, University Library of Munich, Germany.

    More about this item

    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:bla:scotjp:v:58:y:2011:i:1:p:127-152. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/sesssea.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.