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. 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-COGRCH Parameters, respectively, which we derive in detail.     «

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. 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-COGRCH Parameters, respecti...     »