IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-10-00808.html
   My bibliography  Save this article

Nonlinear prediction of Malaysian exchange rate with monetary fundamentals

Author

Listed:
  • Chun-Teck Lye

    (Multimedia University)

  • Tze-Haw Chan

    (Universiti Sains Malaysia)

  • Chee-Wooi Hooy

    (Universiti Sains Malaysia)

Abstract

This paper compares one-step-ahead out-of-sample predictions on Malaysian Ringgit-US Dollar exchange rate using the generalized regression neural network for a range of forecasting horizons from 1991M3 to 2008M8. We find that the monetary fundamentals are significant in explaining the dynamics of Malaysian exchange rate in a longer forecast horizon as the performance of monetary exchange rate models outperformed the random walk benchmark model. The results also revealed that Malaysian exchange rate market provides profitable short-term arbitrage opportunities with lagged observations, and the integration of autoregressive terms into the monetary exchange rate models enhanced the out-of-sample forecasting performance.

Suggested Citation

  • Chun-Teck Lye & Tze-Haw Chan & Chee-Wooi Hooy, 2011. "Nonlinear prediction of Malaysian exchange rate with monetary fundamentals," Economics Bulletin, AccessEcon, vol. 31(3), pages 1960-1967.
    • Handle: RePEc:ebl:ecbull:eb-10-00808
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2011/Volume31/EB-11-V31-I3-P177.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Baharumshah, Ahmad Zubaidi & Masih, A. Mansur M., 2005. "Current account, exchange rate dynamics and the predictability: the experience of Malaysia and Singapore," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(3), pages 255-270, July.
    2. 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.
    3. Cheung, Yin-Wong & Chinn, Menzie D. & Pascual, Antonio Garcia, 2005. "Empirical exchange rate models of the nineties: Are any fit to survive?," Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1150-1175, November.
    4. Soofi, Abdol S. & Cao, Liangyue, 1999. "Nonlinear deterministic forecasting of daily Peseta-Dollar exchange rate," Economics Letters, Elsevier, vol. 62(2), pages 175-180, February.
    5. Cerra, Valerie & Saxena, Sweta Chaman, 2010. "The monetary model strikes back: Evidence from the world," Journal of International Economics, Elsevier, vol. 81(2), pages 184-196, July.
    6. Azad, A.S.M. Sohel, 2009. "Random walk and efficiency tests in the Asia-Pacific foreign exchange markets: Evidence from the post-Asian currency crisis data," Research in International Business and Finance, Elsevier, vol. 23(3), pages 322-338, September.
    7. Panda, Chakradhara & Narasimhan, V., 2007. "Forecasting exchange rate better with artificial neural network," Journal of Policy Modeling, Elsevier, vol. 29(2), pages 227-236.
    8. Rapach, David E. & Wohar, Mark E., 2002. "Testing the monetary model of exchange rate determination: new evidence from a century of data," Journal of International Economics, Elsevier, vol. 58(2), pages 359-385, December.
    9. 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.
    10. Shiu‐Sheng Chen & Yu‐Hsi Chou, 2010. "Exchange Rates and Fundamentals: Evidence from Long‐Horizon Regression Tests," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(1), pages 63-88, February.
    11. 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.
    12. Hsieh, David A., 1988. "The statistical properties of daily foreign exchange rates: 1974-1983," Journal of International Economics, Elsevier, vol. 24(1-2), pages 129-145, February.
    13. 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.
    14. Cao, Liangyue & Soofi, Abdol S., 1999. "Nonlinear deterministic forecasting of daily dollar exchange rates," International Journal of Forecasting, Elsevier, vol. 15(4), pages 421-430, October.
    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. Shamaila Butt & Suresh Ramakrishnan & Nanthakumar Loganathan & Muhammad Ali Chohan, 2020. "Evaluating the exchange rate and commodity price nexus in Malaysia: evidence from the threshold cointegration approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-19, December.

    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. Chun-Teck Lye & Tze-Haw Chan & Chee-Wooi Hooy, 2012. "Nonlinear Analysis Of Chinese And Malaysian Exchange Rates Predictability With Monetary Fundamentals," Journal of Global Business and Economics, Global Research Agency, vol. 5(1), pages 38-49, July.
    2. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    3. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
    4. Noor Zainab.Tunggal & Shariff Umar Shariff Abd. Kadir & Venus-Khim Sen Liew, 2018. "Panel Analysis of Monetary Model of ASEAN-5 Exchange Rates," International Business Research, Canadian Center of Science and Education, vol. 11(11), pages 1-7, November.
    5. Amat, Christophe & Michalski, Tomasz & Stoltz, Gilles, 2018. "Fundamentals and exchange rate forecastability with simple machine learning methods," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 1-24.
    6. 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.
    7. Katusiime, Lorna & Shamsuddin, Abul & Agbola, Frank W., 2015. "Macroeconomic and market microstructure modelling of Ugandan exchange rate," Economic Modelling, Elsevier, vol. 45(C), pages 175-186.
    8. Cem Kadilar & Muammer Simsek & Cagdas Hakan Aladag, 2009. "Forecasting The Exchange Rate Series With Ann: The Case Of Turkey," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 9(1), pages 17-29, May.
    9. 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.
    10. Xie, Zixiong & Chen, Shyh-Wei, 2019. "Exchange rates and fundamentals: A bootstrap panel data analysis," Economic Modelling, Elsevier, vol. 78(C), pages 209-224.
    11. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    12. Balke, Nathan S. & Ma, Jun & Wohar, Mark E., 2013. "The contribution of economic fundamentals to movements in exchange rates," Journal of International Economics, Elsevier, vol. 90(1), pages 1-16.
    13. Lai, Lin & Guo, Kun, 2017. "The performance of one belt and one road exchange rate: Based on improved singular spectrum analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 299-308.
    14. Philippe Bacchetta & Eric van Wincoop & Toni Beutler, 2010. "Can Parameter Instability Explain the Meese-Rogoff Puzzle?," NBER International Seminar on Macroeconomics, University of Chicago Press, vol. 6(1), pages 125-173.
    15. Ryan Greenaway‐McGrevy & Nelson C. Mark & Donggyu Sul & Jyh‐Lin Wu, 2018. "Identifying Exchange Rate Common Factors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 2193-2218, November.
    16. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "The implications of monetary expansion in China for the US dollar," Journal of Asian Economics, Elsevier, vol. 46(C), pages 71-84.
    17. Ali Trabelsi Karoui & Aida Kammoun, 2021. "Exchange Rate Determination: Mixed Microstructural and Macroeconomic Approach," International Journal of Economics and Financial Issues, Econjournals, vol. 11(3), pages 89-106.
    18. Christopher J. Neely & Lucio Sarno, 2002. "How well do monetary fundamentals forecast exchange rates?," Review, Federal Reserve Bank of St. Louis, vol. 84(Sep), pages 51-74.
    19. Takashi Kano, 2021. "Exchange Rates and Fundamentals: A General Equilibrium Exploration," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(1), pages 95-117, February.
    20. 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.

    More about this item

    Keywords

    Autoregressive; monetary model; neural network; random walk;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • F3 - International Economics - - International Finance

    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:ebl:ecbull:eb-10-00808. 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: John P. Conley (email available below). General contact details of provider: .

    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.