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DC poleHodnotaJazyk
dc.contributor.authorDajčman, Silvo
dc.contributor.authorKavkler, Alenka
dc.date.accessioned2016-01-21T08:47:48Z
dc.date.available2016-01-21T08:47:48Z
dc.date.issued2014
dc.identifier.citationE+M. Ekonomie a Management = Economics and Management. 2014, č. 1, s. 104-120.cs
dc.identifier.issn1212-3609 (Print)
dc.identifier.issn2336-5604 (Online)
dc.identifier.urihttp://www.ekonomie-management.cz/download/1395653309_b494/09_Wavelet+Analysis+Of+Stock+Return+Energy+Decomposition+And+Return+Comovement.pdf
dc.identifier.urihttp://hdl.handle.net/11025/17545
dc.format17 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherTechnická univerzita v Libercics
dc.relation.ispartofseriesE+M. Ekonomie a Management = Economics and Managementcs
dc.rights© Technická univerzita v Libercics
dc.rightsCC BY-NC 4.0cs
dc.subjectStřední a Východní Evropacs
dc.subjectburzovní výnosycs
dc.subjectvlnová analýzacs
dc.titleWavelet analysis of stock return energy decomposition and return comovement: a case of some central european and developed european stock marketsen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedIn this article we investigate comovement of the three Central and Eastern European (CEE) stock markets (Slovenia, the Czech Republic and Hungary) with certain developed European stock markets (Austria, France, Germany and the United Kingdom) through the novel approach of maximal overlap discrete wavelet transform (MODWT). We use two features of MODWT to explore energy decomposition of stock market returns at different time scales and to apply methodology of [29] to study comovement between investigated stock markets. We show that most of the energy (variability) of stock market return series is captured by scale 1 (which correspond to 2–4 days return dynamics) and scale 2 (which correspond to 4–8 days return dynamics) MODWT coefficients. MODWT details are used to show that comovement between stock markets is scale- dependent and declines from raw (daily) return series to first- and second-scale reconstructed return series. The findings of the survey then have important implications for foreign financial investors who already hold international portfolios that exactly replicate those of non-Czech or non- Hungarian stock markets: international investing in the Czech or Hungarian stock markets with investment horizons corresponding to scale 2 (4 to 8 days) brings greater international diversification benefits than shorter (2 to 4 day horizon) international trading diversification strategies. The Slovenian stock market differs from the Czech and Hungarian markets also in this respect, as when the scale is increased the benefits of diversification are reduced. We also find that the volatility of Slovenian stock index returns is less synchronized with other observed stock return series. Interestingly, the Czech and Slovenian stock markets seem to comove with the Austrian stock market to a greater extent than with other developed stock markets.en
dc.subject.translatedCentral and Eastern Europeen
dc.subject.translatedstock market returnsen
dc.subject.translatedwavelet analysisen
dc.identifier.doidx.doi.org/10.15240/tul/001/2014-1-009
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Číslo 1 (2014)
Číslo 1 (2014)

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  1. DSpace at University of West Bohemia
  2. Publikace ZČU / UWB Publications
  3. Časopisy ZČU / UWB Journals
  4. Ekonomie a management
  5. 2014
  6. Číslo 1 (2014)