scholarly journals Goodness-of-Fit Tests for Copulas of Multivariate Time Series

2010 ◽  
Author(s):  
Bruno Remillard
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Multivariate Time Series ◽  
Goodness Of Fit Tests

scholarly journals Goodness-of-Fit Tests for Copulas of Multivariate Time Series

2017 ◽  
Author(s):  
Bruno Rémillard
Keyword(s):  
Time Series ◽  
Asymptotic Behavior ◽  
Stochastic Volatility ◽  
Goodness Of Fit ◽  
Structural Changes ◽  
Multivariate Time Series ◽  
Measures Of Dependence ◽  
Goodness Of Fit Tests ◽  
Empirical Copula ◽  
Multivariate Stochastic Volatility

In this paper, we study the asymptotic behavior of the sequential empirical process and the sequential empirical copula process, both constructed from residuals of multivariate stochastic volatility models. Applications for the detection of structural changes and specification tests of the distribution of innovations are discussed. It is also shown that if the stochastic volatility matrices are diagonal, which is the case if the univariate time series are estimated separately instead of being jointly estimated, then the empirical copula process behaves as if the innovations were observed; a remarkable property. As a by-product, one also obtains the asymptotic behavior of rank-based measures of dependence applied to residuals of these time series models.

Score based goodness-of-fit tests for time series

2011 ◽  
Vol 21 (4) ◽  
Author(s):  
Shiqing Ling ◽  
Howell Tong
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Goodness Of Fit Tests

scholarly journals A Method for Systemic Risk Estimation Based on CDS Indices

2015 ◽  
Vol 8 (1) ◽  
pp. 103-124
Author(s):  
Gabriel Gaiduchevici
Keyword(s):  
Goodness Of Fit ◽  
Risk Estimation ◽  
Multivariate Time Series ◽  
Tail Dependence ◽  
Dependence Structure ◽  
Parameter Estimates ◽  
Copula Models ◽  
Goodness Of Fit Tests ◽  
Multi Stage ◽  
Stage Estimation

AbstractThe copula-GARCH approach provides a flexible and versatile method for modeling multivariate time series. In this study we focus on describing the credit risk dependence pattern between real and financial sectors as it is described by two representative iTraxx indices. Multi-stage estimation is used for parametric ARMA-GARCH-copula models. We derive critical values for the parameter estimates using asymptotic, bootstrap and copula sampling methods. The results obtained indicate a positive symmetric dependence structure with statistically significant tail dependence coefficients. Goodness-of-Fit tests indicate which model provides the best fit to data.

Goodness‐of‐fit tests for β ARMA hydrological time series modeling

2020 ◽  
Vol 31 (3) ◽  
Author(s):  
Vinícius T. Scher ◽  
Francisco Cribari‐Neto ◽  
Guilherme Pumi ◽  
Fábio M. Bayer
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Time Series Modeling ◽  
Goodness Of Fit Tests

scholarly journals Dependent SiZer: Goodness-of-Fit Tests for Time Series Models

2004 ◽  
Vol 31 (8) ◽  
pp. 999-1017 ◽  
Author(s):  
Cheolwoo Park ◽  
J. S. Marron ◽  
Vitaliana Rondonotti
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Time Series Models ◽  
Goodness Of Fit Tests
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