Combined Lagrange Multiplier Test for ARCH in Vector Autoregressive Models

Paul Catani, Niklas Ahlgren

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)

Abstract

A combined Lagrange multiplier (LM) test for autoregressive conditional
heteroskedastic (ARCH) errors in vector autoregressive (VAR) models is
proposed by replacing an exact Monte Carlo (MC) test by a bootstrap MC test
when the model includes lags. The test circumvents the problem of high
dimensionality in multivariate tests for ARCH in VAR models. It only
requires computing univariate statistics. A computational advantage is
therefore that the number of parameters to be estimated is independent of
the dimension of the VAR process. The bootstrap MC test is shown to be
asymptotically valid. Monte Carlo simulations show that the test has good
finite-sample properties. The test is robust against a non-normal error
distribution. Two financial applications of multivariate LM tests for ARCH
to credit default swap (CDS) prices and Euribor interest rates are
presented. The results indicate that the errors are skewed and heavy-tailed,
and that there are significant ARCH effects.
Original languageEnglish
Article number4
Peer-reviewed scientific journalEconometrics and Statistics
Volume1
Issue number1
Pages (from-to)62-84
Number of pages23
DOIs
Publication statusPublished - 16.11.2016
MoE publication typeA1 Journal article - refereed

Keywords

  • 112 Statistics and probability
  • ARCH
  • Bootstrap
  • Lagrange multiplier test
  • Monte Carlo test
  • VAR model
  • 511 Economics
  • ARCH
  • Bootstrap
  • Lagrange multiplier test
  • Monte Carlo test
  • VAR model

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