IDEAS home Printed from https://ideas.repec.org/a/taf/apfiec/v14y2004i4p233-242.html
   My bibliography  Save this article

Modelling East Asian exchange rates: a Markov-switching approach

Author

Listed:
  • Guglielmo Maria Caporale
  • Nicola Spagnolo

Abstract

This paper compares the ability of nonlinear and standard linear models to capture the dynamics of foreign exchanges rates in the presence of structural breaks. The analysis is conducted for three East Asian countries, namely Indonesia, South Korea and Thailand. It is shown that a Markov regime-switching model with shifts in the mean and variance (rather than a STAR model) is well suited to capture the nonlinearities in exchange rates. Such a model is found to outperform a random walk specification in terms of both in-sample fitting and out-of-sample forecasting. In order to evaluate competing forecasts, accuracy measures based on both the forecast errors and the variance forecast are used.

Suggested Citation

  • Guglielmo Maria Caporale & Nicola Spagnolo, 2004. "Modelling East Asian exchange rates: a Markov-switching approach," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 233-242.
    • Handle: RePEc:taf:apfiec:v:14:y:2004:i:4:p:233-242
    DOI: 10.1080/0960310042000201192
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/0960310042000201192
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0960310042000201192?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 61-82, Suppl. De.
    2. Engel, Charles, 1994. "Can the Markov switching model forecast exchange rates?," Journal of International Economics, Elsevier, vol. 36(1-2), pages 151-165, February.
    3. Obstfeld, Maurice, 1996. "Models of currency crises with self-fulfilling features," European Economic Review, Elsevier, vol. 40(3-5), pages 1037-1047, April.
    4. De Gooijer, Jan G. & Kumar, Kuldeep, 1992. "Some recent developments in non-linear time series modelling, testing, and forecasting," International Journal of Forecasting, Elsevier, vol. 8(2), pages 135-156, October.
    5. 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.
    6. Jeanne, Olivier & Masson, Paul, 2000. "Currency crises, sunspots and Markov-switching regimes," Journal of International Economics, Elsevier, vol. 50(2), pages 327-350, April.
    7. Stock, James H., 1987. "Measuring Business Cycle Time," Scholarly Articles 3425950, Harvard University Department of Economics.
    8. Paul R. Krugman, 1991. "Target Zones and Exchange Rate Dynamics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(3), pages 669-682.
    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. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    11. Hsieh, David A, 1989. "Testing for Nonlinear Dependence in Daily Foreign Exchange Rates," The Journal of Business, University of Chicago Press, vol. 62(3), pages 339-368, July.
    12. 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.
    13. Sarantis, Nicholas, 1999. "Modeling non-linearities in real effective exchange rates," Journal of International Money and Finance, Elsevier, vol. 18(1), pages 27-45, January.
    14. Bekaert, Geert & Hodrick, Robert J., 1993. "On biases in the measurement of foreign exchange risk premiums," Journal of International Money and Finance, Elsevier, vol. 12(2), pages 115-138, April.
    15. Diebold, Francis X. & Nason, James A., 1990. "Nonparametric exchange rate prediction?," Journal of International Economics, Elsevier, vol. 28(3-4), pages 315-332, May.
    16. Stock, James H, 1987. "Measuring Business Cycle Time," Journal of Political Economy, University of Chicago Press, vol. 95(6), pages 1240-1261, December.
    17. Hansen, Bruce E, 1996. "Erratum: The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(2), pages 195-198, March-Apr.
    18. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    19. Garcia, Rene, 1998. "Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(3), pages 763-788, August.
    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. Chien-Hsiu Lin & Shih-Kuei Lin & An-Chi Wu, 2015. "Foreign exchange option pricing in the currency cycle with jump risks," Review of Quantitative Finance and Accounting, Springer, vol. 44(4), pages 755-789, May.
    2. Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022. "“An application of deep learning for exchange rate forecasting”," AQR Working Papers 202201, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2022.
    3. Alexandros Pasiouras & Theodoros Daglis, 2020. "The Dollar Exchange Rates in the Covid-19 Era: Evidence from 5 Currencies," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 352-361.
    4. Guglielmo Maria Caporale & Faek Menla Ali & Fabio Spagnolo & Nicola Spagnolo, 2015. "International Portfolio Flows and Exchange Rate Volatility for Emerging Markets," CESifo Working Paper Series 5615, CESifo.
    5. Christian Dunis & Jia Miao, 2007. "Trading foreign exchange portfolios with volatility filters: the carry model revisited," Applied Financial Economics, Taylor & Francis Journals, vol. 17(3), pages 249-255.
    6. Chih-Nan Chen & Chien-Hsiu Lin, 2022. "Optimal carry trade portfolio choice under regime shifts," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 483-506, August.
    7. Diteboho Xaba & Ntebogang Dinah Moroke & Ishmael Rapoo, 2019. "Modeling Stock Market Returns of BRICS with a Markov-Switching Dynamic Regression Model," Journal of Economics and Behavioral Studies, AMH International, vol. 11(3), pages 10-22.
    8. Chien-Chung Nieh & Jeng-Bau Lin & Yu-Shan Wang, 2008. "Regime-switching analysis for the impacts of exchange rate volatility on corporate values: a Taiwanese case," Applied Economics, Taylor & Francis Journals, vol. 40(4), pages 491-504.
    9. Claudio Bonilla & Rafael Romero-Meza & Melvin Hinich, 2006. "Episodic nonlinearity in Latin American stock market indices," Applied Economics Letters, Taylor & Francis Journals, vol. 13(3), pages 195-199.
    10. Suman Das & Saikat Sinha Roy, 2021. "Predicting regime switching in BRICS currency volatility: a Markov switching autoregressive approach," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 48(2), pages 165-180, June.
    11. S. Anoop Kumar & B. Kamaiah, 2014. "On Chaotic Nature of the Emerging European Forex Markets," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 17(53), pages 25-40, September.
    12. Firat Melih Yilmaz & Ozer Arabaci, 2021. "Should Deep Learning Models be in High Demand, or Should They Simply be a Very Hot Topic? A Comprehensive Study for Exchange Rate Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 217-245, January.
    13. Wali, Muammer & Chan, Felix & Manzur, Meher, 2017. "Nonlinear dependence in exchange rate returns: How do emerging Asian currencies compare with major currencies?," Journal of Asian Economics, Elsevier, vol. 50(C), pages 62-72.
    14. Konstantinos N. Konstantakis & Ioannis G. Melissaropoulos & Theodoros Daglis & Panayotis G. Michaelides, 2023. "The euro to dollar exchange rate in the Covid‐19 era: Evidence from spectral causality and Markov‐switching estimation," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2037-2055, April.
    15. Yucel, Eray, 2011. "A Review and Bibliography of Early Warning Models," MPRA Paper 32893, University Library of Munich, Germany.
    16. Bellalah, Mondher & Masood, Omar & Thapa, Priya Darshini Pun & Levyne, Olivier & Triki, Rabeb, 2012. "Economic forces and stock exchange prices: pre and post impacts of global financial recession of 2008," MPRA Paper 50942, University Library of Munich, Germany.

    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. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    2. Carlo Altavilla & Paul De Grauwe, 2010. "Non-linearities in the relation between the exchange rate and its fundamentals," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(1), pages 1-21.
    3. Clarida, Richard H. & Sarno, Lucio & Taylor, Mark P. & Valente, Giorgio, 2003. "The out-of-sample success of term structure models as exchange rate predictors: a step beyond," Journal of International Economics, Elsevier, vol. 60(1), pages 61-83, May.
    4. 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.
    5. Yuan, Chunming, 2011. "Forecasting exchange rates: The multi-state Markov-switching model with smoothing," International Review of Economics & Finance, Elsevier, vol. 20(2), pages 342-362, April.
    6. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, September.
    7. Wu, Jyh-Lin & Hu, Yu-Hau, 2009. "New evidence on nominal exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 28(6), pages 1045-1063, October.
    8. repec:ebl:ecbull:v:7:y:2008:i:8:p:1-12 is not listed on IDEAS
    9. Frommel, Michael & MacDonald, Ronald & Menkhoff, Lukas, 2005. "Markov switching regimes in a monetary exchange rate model," Economic Modelling, Elsevier, vol. 22(3), pages 485-502, May.
    10. Franc Klaassen, 2005. "Long Swings in Exchange Rates: Are They Really in the Data?," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 87-95, January.
    11. Lucio Sarno & Giorgio Valente & Mark E. Wohar, 2004. "Monetary Fundamentals and Exchange Rate Dynamics under Different Nominal Regimes," Economic Inquiry, Western Economic Association International, vol. 42(2), pages 179-193, April.
    12. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.
    13. Edoardo Otranto, 2005. "The multi-chain Markov switching model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(7), pages 523-537.
    14. Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.
    15. Wu, Jyh-Lin & Chen, Show-Lin, 2001. "Nominal exchange-rate prediction: evidence from a nonlinear approach," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 521-532, August.
    16. repec:wyi:journl:002068 is not listed on IDEAS
    17. Manera, Matteo & Cologni, Alessandro, 2006. "The Asymmetric Effects of Oil Shocks on Output Growth: A Markov-Switching Analysis," International Energy Markets Working Papers 12121, Fondazione Eni Enrico Mattei (FEEM).
    18. Jaehun Chung & Yongmiao Hong, 2013. "Model-Free Evaluation of Directional Predictability in Foreign Exchange," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    19. Suman Das & Saikat Sinha Roy, 2021. "Predicting regime switching in BRICS currency volatility: a Markov switching autoregressive approach," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 48(2), pages 165-180, June.
    20. Carlo Altavilla & Paul De Grauwe, 2010. "Forecasting and combining competing models of exchange rate determination," Applied Economics, Taylor & Francis Journals, vol. 42(27), pages 3455-3480.
    21. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    22. Peter Tillmann, 2003. "The Regime‐Dependent Determination of Credibility: A New Look at European Interest Rate Differentials," German Economic Review, Verein für Socialpolitik, vol. 4(4), pages 409-431, November.

    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:taf:apfiec:v:14:y:2004:i:4:p:233-242. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAFE20 .

    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.