Asymmetric COGARCH processes

Anita Behme, Claudia Klüppelberg, Kathrin Mayr

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Financial data are as a rule asymmetric, although most econometric models are symmetric. This applies also to continuous-time models for high-frequency and irregularly spaced data. We discuss some asymmetric versions of the continuous-time GARCH model, concentrating then on the GJR-COGARCH model. We calculate higher-order moments and extend the first-jump approximation. These results are prerequisites for moment estimation and pseudo maximum likelihood estimation of the GJR-COGARCH model parameters, respectively, which we derive in detail.

Original languageEnglish
Pages (from-to)161-173
Number of pages13
JournalJournal of Applied Probability
Volume51A
DOIs
StatePublished - 1 Dec 2014

Keywords

  • APCOGARCH
  • Asymmetric power COGARCH
  • COGARCH
  • Continuous-time GARCH
  • First-jump approximation
  • GJR-COGARCH
  • GJR-GARCH
  • High-frequency data
  • Maximum-likelihood estimation
  • Method of moments
  • Stochastic volatility

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