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Estimating Semiparametric ARCH (8) Models by Kernel Smoothing Methods Author info | Abstract | Publisher info | Download info | Related research | Statistics Oliver Linton
Enno Mammen
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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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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 2003Date of revision:
Handle: RePEc:cep:stiecm:/2003/453Contact details of provider: Web page: http://sticerd.lse.ac.uk/publications/
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Keywords: ARCH inverse problem kernel estimation news impact curve nonparametric regression profile likelihood semiparametric estimation volatility Other versions of this item:
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references Cited by : (explanations , 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.)
Oliver Linton & Enno Mammen, 2006.
"Nonparametric Transformation to White Noise ,"
STICERD - Econometrics Paper Series
/2006/503, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
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Woocheol Kim, 2004.
"Identification And Estimation Of Nonparametric Structural ,"
Econometric Society 2004 Far Eastern Meetings
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