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Testing for ARCH in the Presence of Nonlinearity of Unknown Form in the Conditional Mean

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  • Andrew P. Blake

    (Bank of England)

  • George Kapetanios

    ()
    (Queen Mary, University of London)

Abstract

Tests of ARCH are a routine diagnostic in empirical econometric and financial analysis. However, it is well known that misspecification of the conditional mean may lead to spurious rejections of the null hypothesis of no ARCH. Nonlinearity is a prime example of this phenomenon. There is little work on the extent of the effect of neglected nonlinearity on the properties of ARCH tests. This paper provides some such evidence and also new ARCH testing procedures that are robust to the presence of neglected nonlinearity. Monte Carlo evidence shows that the problem is serious and that the new methods alleviate this problem to a very large extent.

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Bibliographic Info

Paper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 496.

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Date of creation: Jul 2003
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Handle: RePEc:qmw:qmwecw:wp496

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Keywords: Nonlinearity; ARCH; Neural networks;

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  1. Bera, Anil K & Higgins, Matthew L, 1997. "ARCH and Bilinearity as Competing Models for Nonlinear Dependence," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 43-50, January.
  2. Peguin-Feissolle, Anne, 1999. "A comparison of the power of some tests for conditional heteroscedasticity," Economics Letters, Elsevier, vol. 63(1), pages 5-17, April.
  3. n/a, 2001. "A Timeless Perspective on Optimality in Forward-Looking Rational Expectations Models," NIESR Discussion Papers 154, National Institute of Economic and Social Research.
  4. Bera, Anil K & Higgins, Matthew L & Lee, Sangkyu, 1992. "Interaction between Autocorrelation and Conditional Heteroscedasticity: A Random-Coefficient Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 133-42, April.
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Cited by:
  1. E Pavlidis & I Paya & D Peel, 2009. "Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form," Working Papers 599040, Lancaster University Management School, Economics Department.
  2. repec:lan:wpaper:2596 is not listed on IDEAS
  3. Arouri, Mohamed El Hedi & Hammoudeh, Shawkat & Lahiani, Amine & Nguyen, Duc Khuong, 2013. "On the short- and long-run efficiency of energy and precious metal markets," Energy Economics, Elsevier, vol. 40(C), pages 832-844.
  4. Rico Belda, Paz, 2013. "No linealidad y asimetría en el proceso generador del Índice Ibex35/Nonlinearity and Asymmetry in the Generator Process of Ibex35 Index," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 31, pages 555-576, Septiembr.
  5. Kyrtsou, Catherine, 2008. "Re-examining the sources of heteroskedasticity: The paradigm of noisy chaotic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6785-6789.
  6. Sadeck Melhem & Mahmoud Melhem, 2012. "Comments on “Re-examining the source of Heteroskedasticity: The paradigm of noisy chaotic models”," Working Papers 12-13, LAMETA, Universtiy of Montpellier, revised Apr 2012.
  7. repec:lan:wpaper:2454 is not listed on IDEAS
  8. repec:lan:wpaper:2375 is not listed on IDEAS
  9. repec:lan:wpaper:2373 is not listed on IDEAS
  10. Carlos Escanciano, J., 2008. "Joint and marginal specification tests for conditional mean and variance models," Journal of Econometrics, Elsevier, vol. 143(1), pages 74-87, March.
  11. Sitzia, Bruno & Iovino, Doriana, 2008. "Nonlinearities in Exchange rates: Double EGARCH Threshold Models for Forecasting Volatility," MPRA Paper 8661, University Library of Munich, Germany.

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