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Is non-linearity a permanent feature? Evidence from recursive and rolling estimation


  • David G. McMillan


Using recursive and rolling estimation evidence is reported that STAR non-linearity is ever present within the DJIA. Further, the parameters of interest exhibit some temporal dependence. These results suggest that non-linearity is a regular feature of the data that should be modelled and used in forecasting, although variation in parameter values may need to be incorporated.

Suggested Citation

  • David G. McMillan, 2005. "Is non-linearity a permanent feature? Evidence from recursive and rolling estimation," Applied Financial Economics Letters, Taylor and Francis Journals, vol. 1(4), pages 229-232, July.
  • Handle: RePEc:taf:apfelt:v:1:y:2005:i:4:p:229-232

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    References listed on IDEAS

    1. Balke, Nathan S & Fomby, Thomas B, 1997. "Threshold Cointegration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 627-645, August.
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    3. Mark J. Powers, 2000. "Introduction," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 20(1), pages 3-4, January.
    4. 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.
    5. Leung, Mark T. & Daouk, Hazem & Chen, An-Sing, 2000. "Forecasting stock indices: a comparison of classification and level estimation models," International Journal of Forecasting, Elsevier, vol. 16(2), pages 173-190.
    6. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
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