Abstract

http://ssrn.com/abstract=396681
 
 

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The Size and Power of the Variance Ratio Test in Finite Samples: a Monte Carlo Investigation


Andrew W. Lo


Massachusetts Institute of Technology (MIT) - Sloan School of Management; Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL); National Bureau of Economic Research (NBER)

A. Craig Mackinlay


University of Pennsylvania - Finance Department; National Bureau of Economic Research (NBER)

June 1988

NBER Working Paper No. t0066

Abstract:     
We examine the finite sample properties of the variance ratio test of the random walk hypothesis via Monte Carlo simulations under two null and three alternative hypotheses. These results are compared to the performance of the Dickey-Fuller t and the Box-Pierce Q statistics. Under the null hypothesis of a random walk with independent and identically distributed Gaussian increments, the empirical size of all three tests are comparable. Under a heteroscedastic random walk null, the variance ratio test is more reliable than either the Dickey-Fuller or Box-Pierce tests. We compute the power of these three tests against three alternatives of recent empirical interest: a stationary AR(1), the sum of this AR(1) and a random walk, and an integrated AR( 1). By choosing the sampling frequency appropriately, the variance ratio test is shown to be as powerful as the Dickey-Fuller and Box-Pierce tests against the stationary alternative, and is more powerful than either of the two tests against the two unit-root alternatives.

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Date posted: July 16, 2004  

Suggested Citation

Lo, Andrew W. and Mackinlay, A. Craig, The Size and Power of the Variance Ratio Test in Finite Samples: a Monte Carlo Investigation (June 1988). NBER Working Paper No. t0066. Available at SSRN: http://ssrn.com/abstract=396681

Contact Information

Andrew W. Lo (Contact Author)
Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )
100 Main Street
E62-618
Cambridge, MA 02142
United States
617-253-0920 (Phone)
781 891-9783 (Fax)
HOME PAGE: http://web.mit.edu/alo/www
Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)
Stata Center
Cambridge, MA 02142
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Archie Craig MacKinlay
University of Pennsylvania - Finance Department ( email )
The Wharton School
3620 Locust Walk
Philadelphia, PA 19104
United States
215-898-5309 (Phone)

National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
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