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The variance ratio and trend stationary model as extensions of a constrained autoregressive model

Listed author(s):
  • Shlomo Zilca

    (Faculty of Management, Tel Aviv University, Tel Aviv, Israel)

Registered author(s):

    This paper shows that a constrained autoregressive model that assigns linearly decreasing weights to past observations of a stationary time series has important links to the variance ratio methodology and trend stationary model. It is demonstrated that the proposed autoregressive model is asymptotically related to the variance ratio through the weighting schedules that these two tools use. It is also demonstrated that under a trend stationary time series process the proposed autoregressive model approaches a trend stationary model when the memory of the autoregressive model is increased. These links create a theoretical foundation for tests that confront the random walk model simultaneously against a trend stationary and a variety of short- and long-memory autoregressive alternatives. Copyright © 2009 John Wiley & Sons, Ltd.

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    File URL: http://hdl.handle.net/10.1002/for.1137
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    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

    Volume (Year): 29 (2010)
    Issue (Month): 5 ()
    Pages: 467-475

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    Handle: RePEc:jof:jforec:v:29:y:2010:i:5:p:467-475
    DOI: 10.1002/for.1137
    Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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    1. Myung Jig Kim & Charles R. Nelson & Richard Startz, 1991. "Mean Reversion in Stock Prices? A Reappraisal of the Empirical Evidence," Review of Economic Studies, Oxford University Press, vol. 58(3), pages 515-528.
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