The size and power of the variance ratio test in finite samples : A Monte Carlo investigation
AbstractWe 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(l), 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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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 40 (1989)
Issue (Month): 2 (February)
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Web page: http://www.elsevier.com/locate/jeconom
Other versions of this item:
- Andrew W. Lo & Craig A. MacKinlay, . "The Size and Power of the Variance Ratio Test in Finite Samples: A Monte Carlo Investigation," Rodney L. White Center for Financial Research Working Papers 28-87, Wharton School Rodney L. White Center for Financial Research.
- Andrew W. Lo & A. Craig MacKinlay, 1988. "The Size and Power of the Variance Ratio Test in Finite Samples: A Monte Carlo Investigation," NBER Technical Working Papers 0066, National Bureau of Economic Research, Inc.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Phillips, P.C.B., 1986.
"Testing for a Unit Root in Time Series Regression,"
Cahiers de recherche
8633, Universite de Montreal, Departement de sciences economiques.
- Campbell, John & Mankiw, Gregory, 1987.
"Are Output Fluctuations Transitory?,"
3122545, Harvard University Department of Economics.
- White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
- Schwert, G. William, 1987. "Effects of model specification on tests for unit roots in macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 20(1), pages 73-103, July.
- Poterba, James M & Summers, Lawrence H, 1986.
"The Persistence of Volatility and Stock Market Fluctuations,"
American Economic Review,
American Economic Association, vol. 76(5), pages 1142-51, December.
- James M. Poterba & Lawrence H. Summers, 1987. "The Persistence of Volatility and Stock Market Fluctuations," NBER Working Papers 1462, National Bureau of Economic Research, Inc.
- James M. Poterba & Lawrence H. Summers, 1984. "The Persistence of Volatility and Stock Market Fluctuations," Working papers 353, Massachusetts Institute of Technology (MIT), Department of Economics.
- White, Halbert & Domowitz, Ian, 1984. "Nonlinear Regression with Dependent Observations," Econometrica, Econometric Society, vol. 52(1), pages 143-61, January.
- Pierre Perron & Robert J. Shiller, 1984.
"Testing the Random Walk Hypothesis: Power Versus Frequency of Observation,"
Cowles Foundation Discussion Papers
732, Cowles Foundation for Research in Economics, Yale University.
- Shiller, Robert J. & Perron, Pierre, 1985. "Testing the random walk hypothesis : Power versus frequency of observation," Economics Letters, Elsevier, vol. 18(4), pages 381-386.
- Robert J. Shiller & Pierre Perron, 1985. "Testing the Random Walk Hypothesis: Power versus Frequency of Observation," NBER Technical Working Papers 0045, National Bureau of Economic Research, Inc.
- Shiller, Robert J, 1981.
"The Use of Volatility Measures in Assessing Market Efficiency,"
Journal of Finance,
American Finance Association, vol. 36(2), pages 291-304, May.
- Robert J. Shiller, 1981. "The Use of Volatility Measures in Assessing Market Efficiency," NBER Working Papers 0565, National Bureau of Economic Research, Inc.
- Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
- Dufour, J.M. & Roy, R., 1984.
"Some Robust Exact Results on Sample Autocorrelations and Tests of Randomness,"
Cahiers de recherche
8412, Universite de Montreal, Departement de sciences economiques.
- Dufour, Jean-Marie & Roy, Roch, 1985. "Some robust exact results on sample autocorrelations and tests of randomness," Journal of Econometrics, Elsevier, vol. 29(3), pages 257-273, September.
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