Title: Forecasting correlation structures
Authors : Schüle, Martin
Ott, Thomas
Schwendner, Peter
Proceedings: Proceedings of the 2016 international symposium on nonlinear theory and its applications
Conference details: 2016 International Symposium on Nonlinear Theory and Its Applications, NOLTA2016, Yugawara, Japan, 27-30 November 2016
Publisher / Ed. Institution : IEICE
Issue Date: 2016
License (according to publishing contract) : Licence according to publishing contract
Type of review: Peer review (Abstract)
Language : English
Subjects : Complex systems; Forecasting; Econometrics
Subject (DDC) : 500: Natural sciences and mathematics
Abstract: Often the signature of a complex system is a couple of empirically found time series. As the exact processes generating these series are often unknown, one contents oneself with mere data analysis, i.e., an analysis of the statistical features of the time series. Beyond the individual statistical characteristics of the time series, a key tool to investigate the structural behaviour of the complex system is considering the correlation structure, i.e. the system of pairwise correlations between the time series.
Departement: School of Management and Law
Organisational Unit: Institute of Applied Simulation (IAS)
Publication type: Conference Paper
URI: https://digitalcollection.zhaw.ch/handle/11475/13153
Appears in Collections:Publikationen School of Management and Law

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.