EconStor >
Queen Mary, University of London >
School of Economics and Finance, Queen Mary, University of London  >
Working Paper Series, School of Economics and Finance, Queen Mary, University of London  >

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10419/62815
  
Title:Testing for ARCH in the presence of nonlinearity of unknow form in the conditional mean PDF Logo
Authors:Blake, Andrew P.
Kapetanios, George
Issue Date:2003
Series/Report no.:Working Paper, Department of Economics, Queen Mary, University of London 496
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.
Subjects:Nonlinearity, ARCH, Neural networks
JEL:C12
C22
C45
Document Type:Working Paper
Appears in Collections:Working Paper Series, School of Economics and Finance, Queen Mary, University of London

Files in This Item:
File Description SizeFormat
377046299.pdf192.34 kBAdobe PDF
No. of Downloads: Counter Stats
Download bibliographical data as: BibTeX
Share on:http://hdl.handle.net/10419/62815

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.