On the Maximum Likelihood Estimator for Irregularly Observed Time Series Data from COGARCH(1,1) Models

Authors

  • Moosup Kim Seoul National University
  • Sangyeol Lee Seoul National University

DOI:

https://doi.org/10.57805/revstat.v11i2.131

Keywords:

COGARCH(1,1) models, maximum likelihood estimation, consistency, asymptotic normality, sampling scheme, irregular time spaces

Abstract

In this paper, we study the asymptotic properties of the maximum likelihood estimator (MLE) in COGARCH(1,1) models driven by L´evy processes as proposed by Maller et al. ([13]). We show that the MLE is consistent and asymptotically normal under some conditions relevant to the moments of the driving L´evy process and the sampling scheme.

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Published

2013-06-24

How to Cite

Kim , M., & Lee , S. (2013). On the Maximum Likelihood Estimator for Irregularly Observed Time Series Data from COGARCH(1,1) Models. REVSTAT-Statistical Journal, 11(2), 135–168. https://doi.org/10.57805/revstat.v11i2.131

Issue

Vol. 11 No. 2 (2013): REVSTAT-Statistical Journal

Section

Article

License

Copyright (c) 2013 REVSTAT-Statistical Journal

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This work is licensed under a Creative Commons Attribution 4.0 International License.