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Testing the Random Walk Hypothesis: Power Versus Frequency of Observation

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Author Info
Pierre Perron (Yale University)
Robert J. Shiller () (Cowles Foundation, Yale University)

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Abstract

Power functions of tests of the random walk hypothesis versus stationary first order autoregressive alternatives are tabulated for samples of fixed span but various frequencies of observation. For a t-test and normalized test, power is found to depend, for a substantial range of parameter values, more on the span of the data in time than on the number of observations. For a runs test, power rapidly declines as the number of observations is increased beyond a certain point.

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File URL: http://cowles.econ.yale.edu/P/cd/d07a/d0732.pdf
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Publisher Info
Paper provided by Cowles Foundation, Yale University in its series Cowles Foundation Discussion Papers with number 732.

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Length: 28 pages
Date of creation: Dec 1984
Date of revision:
Handle: RePEc:cwl:cwldpp:732

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Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA
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Web page: http://cowles.econ.yale.edu/
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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

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Related research
Keywords: Random walk; unit roots; power function; efficient markets hypothesis;

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This page was last updated on 2009-11-4.

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