Testing Non-linearity Using a Modified Q Test
AbstractA new version of the Q test, based on generalized residual correlations (i.e. auto-correlations and cross-correlations), is developed in this paper. The Q test fixes two main shortcomings of the Mcleod and Li Q (MLQ) test often used in the literature: (i) the test is capable to capture some interesting non-linear models, for which the original MLQ test completely fails (e.g. a non-linear moving average model). Additionally, the Q test also significantly improves the power for some other non-linear models (e.g. a threshold moving average model), for which the original MLQ test does not work very well; (ii) the new Q test can be used for discrimination between simple and more complicated (non-linear/asymmetric) GARCH models as well.
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Bibliographic InfoPaper provided by Birkbeck, Department of Economics, Mathematics & Statistics in its series Birkbeck Working Papers in Economics and Finance with number 1204.
Date of creation: Mar 2012
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Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-04-03 (All new papers)
- NEP-ECM-2012-04-03 (Econometrics)
- NEP-ETS-2012-04-03 (Econometric Time Series)
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- Maravall, Agustin, 1983. "An Application of Nonlinear Time Series Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(1), pages 66-74, January.
- Lobato I. N., 2001. "Testing That a Dependent Process Is Uncorrelated," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1066-1076, September.
- Serena Ng & Pierre Perron, 2001.
"A Note on the Selection of Time Series Models,"
Boston College Working Papers in Economics
500, Boston College Department of Economics.
- Ana Pérez & Esther Ruiz, 2003.
"Properties of the Sample Autocorrelations of Nonlinear Transformations in Long-Memory Stochastic Volatility Models,"
Journal of Financial Econometrics,
Society for Financial Econometrics, vol. 1(3), pages 420-444.
- Pérez, A. & Ruiz, Esther, . "Properties of the sample autocorrelations of non-linear transformations in long memory stochastic volatility models," Open Access publications from Universidad Carlos III de Madrid info:hdl:10016/4839, Universidad Carlos III de Madrid.
- Dennis Jansen & Casper de Vries, 1988.
"On the frequency of large stock returns: putting booms and busts into perspective,"
1989-006, Federal Reserve Bank of St. Louis.
- Jansen, Dennis W & de Vries, Casper G, 1991. "On the Frequency of Large Stock Returns: Putting Booms and Busts into Perspective," The Review of Economics and Statistics, MIT Press, vol. 73(1), pages 18-24, February.
- Horowitz, Joel L. & Lobato, I.N. & Nankervis, John C. & Savin, N.E., 2006. "Bootstrapping the Box-Pierce Q test: A robust test of uncorrelatedness," Journal of Econometrics, Elsevier, vol. 133(2), pages 841-862, August.
- Escanciano, J. Carlos & Lobato, Ignacio N., 2009. "An automatic Portmanteau test for serial correlation," Journal of Econometrics, Elsevier, vol. 151(2), pages 140-149, August.
- Lobato, I.N. & Nankervis, John C. & Savin, N.E., 2002. "Testing For Zero Autocorrelation In The Presence Of Statistical Dependence," Econometric Theory, Cambridge University Press, vol. 18(03), pages 730-743, June.
- Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
- Runde, Ralf, 1997. "The asymptotic null distribution of the Box-Pierce Q-statistic for random variables with infinite variance an application to German stock returns," Journal of Econometrics, Elsevier, vol. 78(2), pages 205-216, June.
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