Authors: Schnurr, Alexander
Dehling, Herold
Title: Testing for structural breaks via ordinal pattern dependence
Language (ISO): en
Abstract: We propose new concepts in order to analyze and model the dependence structure between two time series. Our methods rely exclusively on the order structure of the data points. Hence, the methods are stable under monotone transformations of the time series and robust against small perturbations or measurement errors. Ordinal pattern dependence can be characterized by four parameters. We propose estimators for these parameters, and we calculate their asymptotic distributions. Furthermore, we derive a test for structural breaks within the dependence structure. All results are supplemented by simulation studies and empirical examples. For three consecutive data points attaining different values, there are six possibil- ities how their values can be ordered. These possibilities are called ordinal patterns. Our first idea is simply to count the number of coincidences of patterns in both time series, and to compare this with the expected number in the case of independence. If we detect a lot of coincident patterns, this means that the up-and-down behavior is similar. Hence, our concept can be seen as a way to measure non-linear ‘correlation’. We show in the last section, how to generalize the concept in order to capture various other kinds of dependence.
Subject Headings: time series
non-linear correlation
near epoch dependence
limit theorems
URI: http://hdl.handle.net/2003/33883
http://dx.doi.org/10.17877/DE290R-6810
Issue Date: 2015
Appears in Collections:Sonderforschungsbereich (SFB) 823

Files in This Item:
File Description SizeFormat 
DP_0515_SFB823_Schnurr_Dehling.pdfDNB361.17 kBAdobe PDFView/Open


This item is protected by original copyright



All resources in the repository are protected by copyright.