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Our approach is based on a dependent multiplier bootstrap and it can be applied to any stationary, strongly mixing time series. The method extends recent i.i.d. results by Kojadinovic et al. (2011) and shares the same computational benefits compared to methods based on a parametric bootstrap. The finite-sample performance of our approach is investigated by Monte Carlo experiments for the case of copula-based Markovian time series models.<\/jats:p>","DOI":"10.1017\/s0266466615000419","type":"journal-article","created":{"date-parts":[[2016,1,29]],"date-time":"2016-01-29T09:49:11Z","timestamp":1454060951000},"page":"292-330","source":"Crossref","is-referenced-by-count":10,"title":["GOODNESS-OF-FIT TESTS FOR MULTIVARIATE COPULA-BASED TIME SERIES MODELS"],"prefix":"10.1017","volume":"33","author":[{"given":"Betina","family":"Berghaus","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Axel","family":"B\u00fccher","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2016,1,29]]},"reference":[{"key":"S0266466615000419_ref3","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466614000115"},{"key":"S0266466615000419_ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2012.12.001"},{"key":"S0266466615000419_ref24","doi-asserted-by":"publisher","DOI":"10.1080\/10920277.1998.10595667"},{"key":"S0266466615000419_ref46","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176343588"},{"key":"S0266466615000419_ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s10463-011-0337-6"},{"key":"S0266466615000419_ref17","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1215\/ijm\/1255987328","article-title":"Copulas and Markov processes","volume":"36","author":"Darsow","year":"1992","journal-title":"Illinois Journal of Mathematics"},{"key":"S0266466615000419_ref40","doi-asserted-by":"publisher","DOI":"10.1081\/ETC-120028836"},{"key":"S0266466615000419_ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmva.2008.05.004"},{"key":"S0266466615000419_ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmva.2008.02.025"},{"key":"S0266466615000419_ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmva.2012.03.001"},{"key":"S0266466615000419_ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2005.07.027"},{"key":"S0266466615000419_ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2005.09.001"},{"key":"S0266466615000419_ref51","doi-asserted-by":"crossref","first-page":"2098","DOI":"10.1214\/aop\/1041903220","article-title":"Weak convergence for weighted empirical processes of dependent sequences","volume":"24","author":"Shao","year":"1996","journal-title":"Annals of Probability"},{"key":"S0266466615000419_ref25","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/82.3.543"},{"key":"S0266466615000419_ref52","doi-asserted-by":"publisher","DOI":"10.1002\/cjs.5540330304"},{"key":"S0266466615000419_ref20","doi-asserted-by":"publisher","DOI":"10.1198\/004017006000000309"},{"key":"S0266466615000419_ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-0099-4_1"},{"key":"S0266466615000419_ref30","doi-asserted-by":"publisher","DOI":"10.1002\/cjs.10110"},{"key":"S0266466615000419_ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmva.2012.01.026"},{"key":"S0266466615000419_ref47","unstructured":"Ruymgaart F.H . 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