Local Power of Andrews and Ploberger Tests Against Nearly Integrated, Nearly White Noise Process
AbstractWe find that the Andrews and Ploberger’s (1996) tests have unit local power against the nearly integrated, nearly white noise process (ref. Nabeya and Perron (1994)). Therefore, compared with the stationary local alternatives, higher power is expected when testing against such process. Monte Carlo simulation confirms our results. We apply the tests to monthly SP500 stock returns and strongly reject the martingale difference hypothesis.
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Bibliographic InfoPaper provided by Boston University - Department of Economics in its series Boston University - Department of Economics - Working Papers Series with number WP2006-027.
Length: 08 pages
Date of creation: May 2006
Date of revision:
ARMA(1; 1); local power; Nearly integrated; nearly white noise process; stock returns;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
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- Donald W.K. Andrews & Werner Ploberger, 1994. "Testing for Serial Correlation Against an ARMA(1,1) Process," Cowles Foundation Discussion Papers 1077, Cowles Foundation for Research in Economics, Yale University.
- Perron, P. & Ng, S., 1994.
"Useful Modifications to Some Unit Root Tests with Dependent Errors and Their Local Asymptotic Properties,"
Cahiers de recherche
9427, Universite de Montreal, Departement de sciences economiques.
- Perron, Pierre & Ng, Serena, 1996. "Useful Modifications to Some Unit Root Tests with Dependent Errors and Their Local Asymptotic Properties," Review of Economic Studies, Wiley Blackwell, vol. 63(3), pages 435-63, July.
- Perron, P. & Ng, S., 1994. "Useful Modifications to Some Unit Root Tests with Dependent Errors and Their Local Asymptotic Properties," Cahiers de recherche 9427, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Nabeya, S. & Perron, P., 1991.
"Local Asymtotic Distributions Related to the AR(1) MOdel with Dependent Errors,"
362, Princeton, Department of Economics - Econometric Research Program.
- Nabeya, Seiji & Perron, Pierre, 1994. "Local asymptotic distribution related to the AR(1) model with dependent errors," Journal of Econometrics, Elsevier, vol. 62(2), pages 229-264, June.
- King, Maxwell L & McAleer, Michael, 1987. "Further Results on Testing AR (1) against MA (1) Disturbances in the Linear Regression Model," Review of Economic Studies, Wiley Blackwell, vol. 54(4), pages 649-63, October.
- Godfrey, Leslie G, 1978. "Testing for Higher Order Serial Correlation in Regression Equations When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1303-10, November.
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