Can Portemanteau Nonlinearity Tests Serve as General Mis-Specification Tests? Evidence from Symmetric and Asymmetric GARCH Models
AbstractA number of recent papers have employed the BDS test as a general test for mis-specification for linear and nonlinear models. We show that for a particular class of conditionally heteroscedastic models, the BDS test is unable to detect a common mis-specification. Our results also demonstrate that specific rather than portmanteau diagnostics are required to detect neglected asymmetry in volatility. However for both classes of tests reasonable power is only obtained using very large sample sizes.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by The University of Melbourne in its series Department of Economics - Working Papers Series with number 723.
Length: 12 pages
Date of creation: 1999
Date of revision:
Contact details of provider:
Postal: Department of Economics, The University of Melbourne, 4th Floor, FBE Building, Level 4, 111 Barry Street. Victoria, 3010, Australia
Phone: +61 3 8344 5355
Fax: +61 3 8344 6899
Web page: http://www.economics.unimelb.edu.au
More information through EDIRC
ECONOMIC MODELS ; REGRESSION ANALYSIS ; TESTING;
Other versions of this item:
- Brooks, Chris & Henry, Olan T., 2000. "Can portmanteau nonlinearity tests serve as general mis-specification tests?: Evidence from symmetric and asymmetric GARCH models," Economics Letters, Elsevier, vol. 67(3), pages 245-251, June.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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.:
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
- Olan Henry, 1998.
"Modelling the asymmetry of stock market volatility,"
Applied Financial Economics,
Taylor & Francis Journals, vol. 8(2), pages 145-153.
- Henry, O.T.J., 1995. "Modelling the Assymetry of Stock Market Volatility," Department of Economics - Working Papers Series 487, The University of Melbourne.
- Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993.
"On the relation between the expected value and the volatility of the nominal excess return on stocks,"
157, Federal Reserve Bank of Minneapolis.
- Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
- Engle, Robert F & Ng, Victor K, 1993.
" Measuring and Testing the Impact of News on Volatility,"
Journal of Finance,
American Finance Association, vol. 48(5), pages 1749-78, December.
- Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
- Hsieh, David A., 1993. "Implications of Nonlinear Dynamics for Financial Risk Management," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(01), pages 41-64, March.
- Brooks, Chris & Heravi, Saeed M, 1999. "The Effect of (Mis-Specified) GARCH Filters on the Finite Sample Distribution of the BDS Test," Computational Economics, Society for Computational Economics, vol. 13(2), pages 147-62, April.
- repec:ebl:ecbull:v:3:y:2002:i:29:p:1-9 is not listed on IDEAS
- Jorge Pérez-Rodríguez & Julián Andrada-Félix, 2013. "Estimating critical values for testing the i.i.d. in standardized residuals from GARCH models in finite samples," Computational Statistics, Springer, vol. 28(2), pages 701-734, April.
- O.T. Henry & S. Suardi, 2005. "Testing For Asymmetry In Interest Rate Volatility In The Presence Of A Neglected Level Effect," Department of Economics - Working Papers Series 945, The University of Melbourne.
- Evzen Kocenda & Lubos Briatka, 2004.
"Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power,"
CERGE-EI Working Papers
wp235, The Center for Economic Research and Graduate Education - Economic Institute, Prague.
- Evzen Kocenda & Lubos Briatka, 2004. "Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power," Econometrics 0409001, EconWPA.
- Theodore Panagiotidis, 2005. "Market capitalization and efficiency. Does it matter? Evidence from the Athens Stock Exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 15(10), pages 707-713.
- Theodore Panagiotidis, 2002. "Testing the assumption of Linearity," Economics Bulletin, AccessEcon, vol. 3(29), pages 1-9.
- Belaire-Franch, Jorge & Contreras, Dulce, 2003. "Tests for time reversibility: a complementarity analysis," Economics Letters, Elsevier, vol. 81(2), pages 187-195, November.
- Yi-Ting Chen & Chung-Ming Kuan, 2002. "Time irreversibility and EGARCH effects in US stock index returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 565-578.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Aminata Doumbia).
If references are entirely missing, you can add them using this form.