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Functional data analysis (FDA) is a part of modern multivariate statisticsthat analyses data providing information about curves, surfaces or anythingelse varying over a certain continuum. In economics and empirical finance weoften have to deal with time series of functional data, where we cannot easilydecide, whether they are to be considered as homogeneous or heterogeneous. Atpresent a discussion on adequate tests of homogenity for functional data iscarried. We propose a novel statistic for detetecting a structural change infunctional time series based on a local Wilcoxon statistic induced by a localdepth function proposed by Paindaveine and Van Bever (2013).

Detecting a Structural Change in Functional Time Series Using Local Wilcoxon Statistic