Department of Economics and Business Economics

The limiting properties of the QMLE in a general class of asymmetric volatility models

Research output: Working paperResearch

  • Christian Møller Dahl, Denmark
  • Emma M. Iglesias, Michigan State University, United States
  • School of Economics and Management
In this paper we analyze the limiting properties of the estimated parameters in a general class of asymmetric volatility models which are closely related to the traditional exponential GARCH model. The new representation has three main advantages over the traditional EGARCH: (1) It allows a much more flexible representation of the conditional variance function. (2) It is possible to provide a complete characterization of the asymptotic distribution of the QML estimator based on the new class of nonlinear volatility models, something which has proven very difficult even for the traditional EGARCH. (3) It can produce asymmetric news impact curves where, contrary to the traditional EGARCH, the resulting variances do not excessively exceed the ones associated with the standard GARCH model, irrespectively of the sign of an impact of moderate size. Furthermore, the new class of models considered can create a wide array of news impact curves which provide the researcher with a richer choice set relative to the traditional. We also show in a Monte Carlo experiment the good finite sample performance of our asymptotic theoretical results and we compare them with those obtained from a parametric and the residual based bootstrap. Finally, we provide an empirical illustration.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages36
Publication statusPublished - 2008

    Research areas

  • Asymmetric volatility models; Asymmetric news impact curves; Quasi maximum likelihood estimation; Asymptotic Theory; Bootstrap

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ID: 11814050