Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/62815
Authors: 
Blake, Andrew P.
Kapetanios, George
Year of Publication: 
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

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