GMM estimation of a stochastic volatility model: A monte carlo study

Torben G. Andersen, Bent E. Sørensen

Research output: Contribution to journalArticlepeer-review

210 Scopus citations

Abstract

We examine alternative generalized method of moments procedures for estimation of a stochastic autoregressive volatility model by Monte Carlo methods. We document the existence of a tradeoff between the number of moments, or information, included in estimation and the quality, or precision, of the objective function used for estimation. Furthermore, an approximation to the optimal weighting matrix is used to explore the impact of the weighting matrix for estimation, specification testing, and inference procedures. The results provide guidelines that help achieve desirable small-sample properties in settings characterized by strong conditional heteroscedasticity and correlation among the moments.

Original languageEnglish (US)
Pages (from-to)328-352
Number of pages25
JournalJournal of Business and Economic Statistics
Volume14
Issue number3
DOIs
StatePublished - Jul 1996

Keywords

  • Asymptotic standard errors
  • Generalized method of moments
  • Goodness of fit
  • Simulation techniques
  • Specification tests
  • Weighting matrix

ASJC Scopus subject areas

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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