Artikel
Goodness-of-fit tests for copulas of multivariate time series
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.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 5 ; Year: 2017 ; Issue: 1 ; Pages: 1-23 ; Basel: MDPI
- Klassifikation
-
Wirtschaft
Hypothesis Testing: General
Semiparametric and Nonparametric Methods: General
Statistical Simulation Methods: General
Financial Econometrics
- Thema
-
goodness-of-fit
time series
copulas
GARCH models
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Rémillard, Bruno
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2017
- DOI
-
doi:10.3390/econometrics5010013
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Rémillard, Bruno
- MDPI
Entstanden
- 2017
Ähnliche Objekte (12)
Goodness-of-fit tests for elliptical copulas
Goodness-of-fit tests for copulas of dependent observations
On the robustness of goodness-of-fit tests for copulas
Goodness-of-fit statistics for discrete multivariate data
Goodness-of- fit tests for multivariate copula-based time series models
Goodness-of-fit testing the error distribution in multivariate indirect regression
Goodness-of-fit tests for multivariate copula-based time series models
Bootstrap based goodness-of-fit tests for binary multivariate regression models
Goodness-of-fit tests for neural population models: the multivariate time-rescaling theorem
Parametric versus Nonparametric Goodness of Fit
Goodness of fit for lattice processes
Data-driven goodness-of-fit tests
Goodness-of-fit tests for elliptical copulas
Goodness-of-fit tests for copulas of dependent observations
On the robustness of goodness-of-fit tests for copulas
Goodness-of-fit statistics for discrete multivariate data
Goodness-of- fit tests for multivariate copula-based time series models
Goodness-of-fit testing the error distribution in multivariate indirect regression
Goodness-of-fit tests for multivariate copula-based time series models
Bootstrap based goodness-of-fit tests for binary multivariate regression models
Goodness-of-fit tests for neural population models: the multivariate time-rescaling theorem
Parametric versus Nonparametric Goodness of Fit
Goodness of fit for lattice processes
Data-driven goodness-of-fit tests
Goodness-of-fit tests for elliptical copulas
Goodness-of-fit tests for copulas of dependent observations
On the robustness of goodness-of-fit tests for copulas
Goodness-of-fit statistics for discrete multivariate data
Goodness-of- fit tests for multivariate copula-based time series models
Goodness-of-fit testing the error distribution in multivariate indirect regression
Goodness-of-fit tests for multivariate copula-based time series models
Bootstrap based goodness-of-fit tests for binary multivariate regression models
Goodness-of-fit tests for neural population models: the multivariate time-rescaling theorem
Parametric versus Nonparametric Goodness of Fit
Goodness of fit for lattice processes