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

U of London Queen Mary Economics Working Paper No. 496

21 Pages Posted: 31 Aug 2003

See all articles by Andrew P. Blake

Andrew P. Blake

Bank of England - CCBS

George Kapetanios

King's College, London

Date Written: July 2003

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.

Keywords: Nonlinearity, ARCH, Neural Networks

JEL Classification: C12, C22, C45

Suggested Citation

Blake, Andrew P. and Kapetanios, George, Testing for Arch in the Presence of Nonlinearity of Unknown Form in the Conditional Mean (July 2003). U of London Queen Mary Economics Working Paper No. 496, Available at SSRN: https://ssrn.com/abstract=425402 or http://dx.doi.org/10.2139/ssrn.425402

Andrew P. Blake

Bank of England - CCBS ( email )

Threadneedle Street
London, EC2R 8AH
United Kingdom

George Kapetanios (Contact Author)

King's College, London ( email )

30 Aldwych
London, WC2B 4BG
United Kingdom
+44 20 78484951 (Phone)

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