Predictive power of the ZEW sentiment indicator: Case of the German automotive industry

Homolka, Lubor; Pavelková, Drahomíra

dc.title	Predictive power of the ZEW sentiment indicator: Case of the German automotive industry	en
dc.contributor.author	Homolka, Lubor
dc.contributor.author	Pavelková, Drahomíra
dc.relation.ispartof	Acta Polytechnica Hungarica
dc.identifier.issn	1785-8860 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued	2018
utb.relation.volume	15
utb.relation.issue	4
dc.citation.spage	161
dc.citation.epage	178
dc.type	article
dc.language.iso	en
dc.publisher	Budapest Tech
dc.identifier.doi	10.12700/APH.15.4.2018.4.9
dc.relation.uri	https://www.uni-obuda.hu/journal/Issue83.htm
dc.relation.uri	https://www.uni-obuda.hu/journal/Homolka_Pavelkova_83.pdf
dc.subject	market sentiment	en
dc.subject	automotive industry	en
dc.subject	ZEW	en
dc.subject	DAX	en
dc.subject	VAR	en
dc.subject	Granger causality	en
dc.description.abstract	This paper presents an analysis of German automotive industry and its connection to the market sentiment indicator ZEW. The analysis spans a period of the last decade and is divided into Pre-Crisis, Crisis and Post-Crisis periods. Research questions related to the predictive power of ZEW indicator on macro level indicators (composite DAX and GDP), sector indicator (technology-oriented companies TecDAX) and a selected automotive manufacturer (BMW) were answered. We found that ZEW index had foreseen the economic crisis starting in the March 2008 three months ahead of its start, but failed to see an upcoming economic recovery. We fit two models to estimate whether ZEW index can be used as a standalone forecasting instrument or whether inclusion of lagged values of other variables improves forecasting ability. We conclude that predictions from the ZEW-only models are worse in the test sample than those of the more complex model. We provide further evidence in form cross-correlations and causality analysis in the Granger sense. The study concludes with Impulse Response Function analysis. This analysis found that reaction of TecDAX on change of ZEW is strongest amongst studied variables. © 2018, Budapest Tech Polytechnical Institution. All rights reserved.	en
utb.faculty	Faculty of Management and Economics
dc.identifier.uri	http://hdl.handle.net/10563/1008198
utb.identifier.obdid	43879413
utb.identifier.scopus	2-s2.0-85052659266
utb.identifier.wok	000442389300009
utb.source	j-scopus
dc.date.accessioned	2018-10-03T11:13:02Z
dc.date.available	2018-10-03T11:13:02Z
dc.description.sponsorship	16-25536S, GACR, Grantová Agentura České Republiky; GA CR, GACR, Grantová Agentura České Republiky
dc.description.sponsorship	Czech Science Foundation (GA CR) [16-25536S]
utb.contributor.internalauthor	Homolka, Lubor
utb.contributor.internalauthor	Pavelková, Drahomíra
utb.fulltext.affiliation	Lubor Homolka, Drahomíra Pavelková Tomas Bata University in Zlín, Faculty of Management and Economics, Mostní 5139, 760 01 Zlín, Czech Republic [email protected], [email protected]
utb.fulltext.dates	-
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utb.fulltext.sponsorship	The authors are thankful to the Czech Science Foundation (GA CR), project No. 16-25536S: “Methodology of Developing a Predictive Model of Sector and Company Performance in the Macroeconomic Context”, for financial support of this research.
utb.wos.affiliation	[Homolka, Lubor; Pavelkova, Drahomira] Tomas Bata Univ Zlin, Fac Econ & Management, Mostni 5139, Zlin 76001, Czech Republic
utb.scopus.affiliation	Tomas Bata University in Zlín, Faculty of Management and Economics, Mostní 5139, Zlín, 760 01, Czech Republic
utb.fulltext.projects	16-25536S