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Estimating Semiparametric ARCH (8) Models by Kernel Smoothing Methods

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  • Oliver Linton
  • Enno Mammen

Abstract

We investigate a class of semiparametric ARCH(8) models that includes as a special case the partially nonparametric (PNP) model introduced by Engle and Ng (1993) and which allows for both flexible dynamics and flexible function form with regard to the 'news impact' function. We propose an estimation method that is based on kernel smoothing and profiled likelihood. We establish the distribution theory of the parametric components and the pointwise distribution of the nonparametric component of the model. We also discuss efficiency of both the parametric and nonparametric part. We investigate the performance of our procedures on simulated data and on a sample of S&P500 daily returns. We find some evidence of asymmetric news impact functions in the data.

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Bibliographic Info

Paper provided by Suntory and Toyota International Centres for Economics and Related Disciplines, LSE in its series STICERD - Econometrics Paper Series with number /2003/453.

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Date of creation: May 2003
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Handle: RePEc:cep:stiecm:/2003/453

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Web page: http://sticerd.lse.ac.uk/_new/publications/default.asp

Related research

Keywords: ARCH; inverse problem; kernel estimation; news impact curve; nonparametric regression; profile likelihood; semiparametric estimation; volatility;

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Citations

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Cited by:
  1. Christian M. Dahl & Emma M. Iglesias, 2008. "The limiting properties of the QMLE in a general class of asymmetric volatility models," CREATES Research Papers 2008-38, School of Economics and Management, University of Aarhus.
  2. Gregory Connor & Matthias Hagmann & Oliver Linton, 2007. "Efficient Estimation of a SemiparametricCharacteristic-Based Factor Model of Security Returns," STICERD - Econometrics Paper Series /2007/524, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  3. Oliver Linton & Enno Mammen, 2006. "Nonparametric transformation to white noise," LSE Research Online Documents on Economics 4426, London School of Economics and Political Science, LSE Library.
  4. Jean-Marie Dufour & René García & Abderrahim Taamouti, 2008. "Measuring causality between volatility and returns with high-frequency data," Economics Working Papers we084422, Universidad Carlos III, Departamento de Economía.
  5. Christian Conrad & Enno Mammen, 2008. "Nonparametric Regression on Latent Covariates with an Application to Semiparametric GARCH-in-Mean Models," Working Papers 0473, University of Heidelberg, Department of Economics, revised Jul 2008.
  6. Li, Degui & Lu, Zudi & Linton, Oliver, 2012. "Local Linear Fitting Under Near Epoch Dependence: Uniform Consistency With Convergence Rates," Econometric Theory, Cambridge University Press, vol. 28(05), pages 935-958, October.
  7. Emma M. Iglesias & Oliver Linton, 2009. "Estimation of tail thickness parameters from GJR-GARCH models," Economics Working Papers we094726, Universidad Carlos III, Departamento de Economía.
  8. Woocheol Kim, 2004. "Identification And Estimation Of Nonparametric Structural," Econometric Society 2004 Far Eastern Meetings 733, Econometric Society.

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