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Size distortion in the analysis of volatility and covolatility effects

  • Christian Gourieroux
  • , Joann Jasiak

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Let us assume that is a consistent, asymptotically normal estimator of a matrix A (where T is the sample size), this paper shows that test statistics used in empirical work to test 1) the noninvertibility of A, i.e. det A = 0, 2) the positivite semi-definiteness A > > 0, have a different asymptotic distribution in the case where A = 0 than in the case where A ≠ 0. Moreover, the paper shows that an estimator of A constrained by symmetry or reduced rank has a different asymptotic distribution when A = 0 than when A ≠ 0. The implication is that inference procedures that use critical values equal to appropriate quantiles from the distribution when A ≠ 0 may be size distorted. The paper points out how the above statistical problems arise in standard models in Finance in the analysis of risk effects.A Monte Carlo study explores how the asymptotic results are reflected in finite sample.

Original languageEnglish
Title of host publicationUncertainty Analysis in Econometrics with Applications
PublisherSpringer Verlag
Pages91-118
Number of pages28
ISBN (Print)9783642354427
DOIs
Publication statusPublished - 1 Jan 2013
Externally publishedYes
Event6th International Conference of the Thailand Econometric Society, TES 2013 - Chiang Mai, Thailand
Duration: 10 Jan 201311 Jan 2013

Publication series

NameAdvances in Intelligent Systems and Computing
Volume200 AISC
ISSN (Print)2194-5357

Conference

Conference6th International Conference of the Thailand Econometric Society, TES 2013
Country/TerritoryThailand
CityChiang Mai
Period10/01/1311/01/13

Keywords

  • BEKK Model
  • Boundary
  • Identifiability
  • Invertibility Test
  • Multivariate Volatility
  • Risk Premium
  • Volatility Transmission

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