Empirical Process of the Squared Residuals of an ARCH Sequence

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Goodness-of-Fit Tests for Copulas of Multivariate Time Series (2017, unknown): “[4], the distribution of the empirical process of GARCH residuals in the univariate case (or their squares) is not trivial.”
Recent Advances in ARCH Modelling (2007, methodology): “1) was introduced by Robinson (1991) in the context of testing for strong serial correlation and has been subsequently studied by Kokoszka and Leipus (2000) in the change-point problem context.”
Detection of multiple change-points in multivariate time series (2006, unknown): “, Chu [10], Kokoszka and Leipus [24, 25], Horváth, Kokoszka and Teyssière [21], Kokoszka and Teyssière [26], Berkes et al.”
SEQUENTIAL CHANGE-POINT DETECTION IN GARCH(p,q) MODELS (2004, background): “…limit theorem with the Wiener process in the limit because of the presence of extra terms in their covariance structure~se , e+g+, Boldin, 1998; Horváth, Kokoszka, and Teyssière, 2001; Koul, 2002, Ch+ 8; Berkes and Horváth, 2003; Kulperger and Yu, 2003!+ Thus the approach of Chu et al+ ~1996!…”
Changes of structure in financial time series and the GARCH model (2004, methodology): “Among them we mention the approach that uses the sequential empirical process for the residuals of an ARCH process; see Horváth et al. [26].”