Showing 1 - 10 of 47
Persistent link: https://www.econbiz.de/10009719900
We introduce the notion of realized copula. Based on assumptions of the marginal distributions of daily stock returns and a copula family, realized copula is defined as the copula structure materialized in realized covariance estimated from within-day high-frequency data. Copula parameters are...
Persistent link: https://www.econbiz.de/10009537332
This paper make an overview of the copula theory from a practical side. We consider different methods of copula estimation and different Goodness-of-Fit tests for model selection. In the GoF section we apply Kolmogorov-Smirnov and Cramer-von-Mises type tests and calculate power of these tests...
Persistent link: https://www.econbiz.de/10003953039
Normal distribution of the residuals is the traditional assumption in the classical multivariate time series models. Nevertheless it is not very often consistent with the real data. Copulae allows for an extension of the classical time series models to nonelliptically distributed residuals. In...
Persistent link: https://www.econbiz.de/10012966281
There is increasing demand for models of time-varying and non-Gaussian dependencies for multivariate time-series. Available models suffer from the curse of dimensionality or restrictive assumptions on the parameters and the distribution. A promising class of models are the hierarchical...
Persistent link: https://www.econbiz.de/10012966304
Understanding the dynamics of high dimensional non-normal dependency structure is a challenging task. This research aims at attacking this problem by building up a hidden Markov model (HMM) for Hierarchical Archimedean Copulae (HAC), where the HAC represent a wide class of models for high...
Persistent link: https://www.econbiz.de/10012966319
Persistent link: https://www.econbiz.de/10014391462
Persistent link: https://www.econbiz.de/10003951049
There is increasing demand for models of time-varying and non-Gaussian dependencies for mul- tivariate time-series. Available models suffer from the curse of dimensionality or restrictive assumptions on the parameters and the distribution. A promising class of models are the hierarchical...
Persistent link: https://www.econbiz.de/10003953027
We propose an iterative procedure to efficiently estimate models with complex log-likelihood functions and the number of parameters relative to the observations being potentially high. Given consistent but inefficient estimates of sub-vectors of the parameter vector, the procedure yields...
Persistent link: https://www.econbiz.de/10010235324