IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v31y2015i2p473-487.html
   My bibliography  Save this article

Pretesting for multi-step-ahead exchange rate forecasts with STAR models

Author

Listed:
  • Enders, Walter
  • Pascalau, Razvan

Abstract

It is well known that a linear model may forecast better than a nonlinear one, even when the nonlinear model is consistent with the actual data-generating process. Moreover, forecasting with nonlinear models can be quite programming-intensive, as multi-step-ahead forecasts need to be simulated. We propose a simple pretest to help determine whether it is worthwhile to forecast a series using a STAR model. In particular, we extend Teräsvirta’s in-sample test for LSTAR and ESTAR behavior to multi-step-ahead out-of-sample forecasts. We apply our pretest to the real exchange rates of various OECD countries. When the test strongly rejects the null of linearity, a nonlinear model clearly outperforms a linear one in terms of multi-step-ahead forecasting accuracies (i.e., lower mean absolute percentage errors). However, when it fails to reject the null or does so only mildly, a direct approach based on an autoregressive model yields forecasts that are slightly superior to those generated from a logistic model. We also find that, when the proposed test strongly rejects the null of linearity, the “direct” method of forecasting and the bootstrap predictor yield similar performances, with the latter outperforming in terms of lower mean absolute percentage errors.

Suggested Citation

  • Enders, Walter & Pascalau, Razvan, 2015. "Pretesting for multi-step-ahead exchange rate forecasts with STAR models," International Journal of Forecasting, Elsevier, vol. 31(2), pages 473-487.
  • Handle: RePEc:eee:intfor:v:31:y:2015:i:2:p:473-487
    DOI: 10.1016/j.ijforecast.2014.12.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169207014001836
    Download Restriction: Full text for ScienceDirect subscribers only

    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. Levich, Richard M. & Potì, Valerio, 2015. "Predictability and ‘good deals’ in currency markets," International Journal of Forecasting, Elsevier, vol. 31(2), pages 454-472.
    2. 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.
    3. Frédérique Bec & Mélika Ben Salem & Marine Carrasco, 2010. "Detecting Mean Reversion in Real Exchange Rates from a Multiple Regime star Model," Annals of Economics and Statistics, GENES, issue 99-100, pages 395-427.
    4. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters,in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46 National Bureau of Economic Research, Inc.
    5. Michael, Panos & Nobay, A Robert & Peel, David A, 1997. "Transactions Costs and Nonlinear Adjustment in Real Exchange Rates: An Empirical Investigation," Journal of Political Economy, University of Chicago Press, vol. 105(4), pages 862-879, August.
    6. Andrew C. Harvey, 1990. "The Econometric Analysis of Time Series, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 026208189x.
    7. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, vol. 60(1), pages 85-107, May.
    8. Thomakos, Dimitrios D. & Guerard, John Jr., 2004. "Naive, ARIMA, nonparametric, transfer function and VAR models: A comparison of forecasting performance," International Journal of Forecasting, Elsevier, vol. 20(1), pages 53-67.
    9. Jean Imbs & Haroon Mumtaz & Morten O. Ravn & Hélène Rey, 2003. "Nonlinearities and Real Exchange Rate Dynamics," Journal of the European Economic Association, MIT Press, vol. 1(2-3), pages 639-649, 04/05.
    10. Kapetanios, George & Shin, Yongcheol & Snell, Andy, 2003. "Testing for a unit root in the nonlinear STAR framework," Journal of Econometrics, Elsevier, vol. 112(2), pages 359-379, February.
    11. Marcellino, Massimliano, 2004. "Forecasting EMU macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 20(2), pages 359-372.
    12. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    13. Lucio Sarno & Mark P. Taylor, 2002. "Purchasing Power Parity and the Real Exchange Rate," IMF Staff Papers, Palgrave Macmillan, vol. 49(1), pages 1-5.
    14. Massimiliano Marcellino, "undated". "Instability and non-linearity in the EMU," Working Papers 211, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    15. Enders, Walter & Falk, Barry, 1998. "Threshold-autoregressive, median-unbiased, and cointegration tests of purchasing power parity," International Journal of Forecasting, Elsevier, vol. 14(2), pages 171-186, June.
    16. Shintani, Mototsugu & Terada-Hagiwara, Akiko & Yabu, Tomoyoshi, 2013. "Exchange rate pass-through and inflation: A nonlinear time series analysis," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 512-527.
    17. Sollis, Robert & Leybourne, Stephen & Newbold, Paul, 2002. "Tests for Symmetric and Asymmetric Nonlinear Mean Reversion in Real Exchange Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(3), pages 686-700, August.
    18. Sercu, Piet & Uppal, Raman & Van Hulle, Cynthia, 1995. " The Exchange Rate in the Presence of Transaction Costs: Implications for Tests of Purchasing Power Parity," Journal of Finance, American Finance Association, vol. 50(4), pages 1309-1319, September.
    19. White, Halbert, 2006. "Approximate Nonlinear Forecasting Methods," Handbook of Economic Forecasting, Elsevier.
    20. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.
    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. repec:eee:intfor:v:35:y:2019:i:2:p:429-442 is not listed on IDEAS
    2. Si Mohammed, Kamel & Chérif touil, Noreddine & Maliki, Samir, 2015. "An Empirical Test of Purchasing Power Parity of the Algerian Exchange Rate: Evidence from Panel Dynamic," MPRA Paper 75285, University Library of Munich, Germany.

    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:eee:intfor:v:31:y:2015:i:2:p:473-487. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.