Научный семинар 4 апреля: Владимир Пырлик (CERGE-EI)

Тема: Shrinkage in Estimating High Dimensional Copulas 
Дата и время: 04 апреля 2019 года, 15:00
Место: ул. Кантемировская, д.3 к.1, ауд.339

Международная лаборатория теории игр и принятия решений приглашает принять участие в научном семинаре по экономике.

Дата и время: 04 апреля 2019 года (четверг), 15:00-16:20
Место: ул. Кантемировская, д.3 к.1, ауд.339

Тема: Shrinkage in Estimating High Dimensional Copulas (joint with Stanislav Anatolyev)
Докладчик: 
Рабочий язык: английский

Аннотация:
As a combination of separate marginal distributions and a dependence structure, copulas have proved a convenient framework to synthesize joint distributions, including in high dimensions. Currently, the high dimensional settings analyzed with copulas contain at most several hundred variables, as higher dimensionality appears too demanding for either model selection or estimation. However, the practical application in many fields demands higher dimensionality. In our paper, we propose to adopt recently developed techniques of large covariance matrices estimation for the task of copulas estimation, with the dimensionality of the data going well beyond that studied in the literature. We apply the large covariance matrices shrinkage estimators of Ledoit and Wolf (2004, 2017) to estimate some types of copulas in high dimensions. We consider Gaussian and Student's t copulas as well as their skewed versions and take the dimensionality of the data up to thousands of variables. A simulation study shows that the shrinkage estimation of the large matrix parameters of the copulas significantly outperforms the traditional estimators, including Kendall's rank correlation-based estimator and sample correlation matrix of pseudo-observations.


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