Estimation of Copula Models for Time Series of Possibly Different Length

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Testing the Gaussian copula hypothesis for financial assets dependences (2001, unknown): “It would thus seem natural to first filter the data using an ARCH or GARCH process (as in Patton (2001)) and then to apply our testing procedure to the residuals.”
Common Factors in Conditional Distributions for Bivariate Time Series (2006, methodology): “We employ the multi-stage maximum likelihood estimator presented in Patton (2001).”
The Joint Distribution of Stock Returns is Not Elliptical (2010, unknown): “But instead of trying to understand the economic or financial mechanisms that lead to some particular dependence between assets and construct copulas that encode these mechanisms, the methodology has been — as is sadly often the case — to brute force calibrate on data copulas straight out from stati”
Simple Tests for Models of Dependence between Multiple Financial Time Series, with Applications to U.S. Equity Returns and Exchange Rates (2004, methodology): “Similar evidence for the dependence between exchange rates was reported in Patton (2002a).”
Measuring financial contagion:a copula approach (2007, background): “Patton (2001a, 2001b) pioneered the study of time-varying copulas10.”
Modelling the Dynamic Dependence Structure in Multivariate Financial Time Series (2007, methodology): “One might be interested in looking at the tail dependence instead of correlation, in which case a Joe–Clayton copula can be used (Patton, 2001).”