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Non-linear interest rate dynamics and forecasting: evidence for US and Australian interest rates

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  • David G. McMillan

    (School of Management, University of St Andrews, UK)

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    Abstract

    Recent empirical finance research has suggested the potential for interest rate series to exhibit non-linear adjustment to equilibrium. This paper examines a variety of models designed to capture these effects and compares both their in-sample and out-of-sample performance with a linear alternative. Using short- and long-term interest rates we report evidence that a logistic smooth-transition error-correction model is able to best characterize the data and provide superior out-of-sample forecasts, especially for the short rate, over both linear and non-linear alternatives. This model suggests that market dynamics differ depending on whether the deviations from long-run equilibrium are above or below the threshold value. Copyright © 2007 John Wiley & Sons, Ltd.

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    File URL: http://hdl.handle.net/10.1002/ijfe.358
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    Bibliographic Info

    Article provided by John Wiley & Sons, Ltd. in its journal International Journal of Finance & Economics.

    Volume (Year): 14 (2009)
    Issue (Month): 2 ()
    Pages: 139-155

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    Handle: RePEc:ijf:ijfiec:v:14:y:2009:i:2:p:139-155

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    1. Obstfeld, Maurice & Taylor, Alan M, 1997. "Nonlinear Aspects of Goods-Market Arbitrage and Adjustment: Heckscher's Commodity Points Revisited," CEPR Discussion Papers 1672, C.E.P.R. Discussion Papers.
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    7. Martin Martens & Paul Kofman & Ton C. F. Vorst, 1998. "A threshold error-correction model for intraday futures and index returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 245-263.
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    9. Enders, Walter & Granger, Clive W J, 1998. "Unit-Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 304-11, July.
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    13. Clements, Michael P & Smith, Jeremy, 1999. "A Monte Carlo Study of the Forecasting Performance of Empirical SETAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(2), pages 123-41, March-Apr.
    14. Dumas, Bernard, 1992. "Dynamic Equilibrium and the Real Exchange Rate in a Spatially Separated World," Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 153-80.
    15. Enders, Walter & Siklos, Pierre L, 2001. "Cointegration and Threshold Adjustment," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 166-76, April.
    16. Alvaro Escribano & Santiago Mira, 2001. "Nonlinear error correction models," Documentos de trabajo conjunto ULL-ULPGC 2001-03, Facultad de Ciencias Económicas de la ULPGC.
    17. Francis X. Diebold & James M. Nason, 1989. "Nonparametric exchange rate prediction?," Finance and Economics Discussion Series 81, Board of Governors of the Federal Reserve System (U.S.).
    18. David McMillan, 2001. "Non-Linear Predictability of Stock Market Returns: Evidence from Non-Parametric and Threshold Models," Discussion Paper Series, Department of Economics 200102, Department of Economics, University of St. Andrews.
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    20. Shively, Philip A., 2003. "The nonlinear dynamics of stock prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 43(3), pages 505-517.
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    Cited by:
    1. Stefano Puddu, 2013. "Real Sector and Banking System: Real and Feedback Effects. A Non-Linear VAR Approach," IRENE Working Papers 13-01, IRENE Institute of Economic Research.
    2. Daiki Maki, 2013. "Detecting cointegration relationships under nonlinear models: Monte Carlo analysis and some applications," Empirical Economics, Springer, vol. 45(1), pages 605-625, August.

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