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dc.contributor.authorKılcı, Esra N.en_US
dc.date.accessioned2020-08-21T10:57:32Z
dc.date.available2020-08-21T10:57:32Z
dc.date.issued2020en_US
dc.identifier.citationKilci, E. N. (2020). Forecasting Stock Market Indices with the Composite Leading Indicators: Evidence from Turkey. Sosyoekonomi, 28(43), 119-134. doi:10.17233/sosyoekonomi.2020.01.07en_US
dc.identifier.issn1305-5577
dc.identifier.urihttp://dx.doi.org/10.17233/sosyoekonomi.2020.01.07
dc.identifier.urihttps://hdl.handle.net/20.500.12294/2510
dc.description.abstractThe objective of this study is to evaluate the empirical performance of composite leading indicators (CLIs) in forecasting stock market indices for Turkey in the period from 2007:03 through 2019:07. After examining the stationarity of the series by using Narayan and Popp (2010) and Enders and Lee (2012) Fourier ADF unit root tests, the causality relationship from the composite leading indicators to stock market indices are tested by employing Enders and Jones (2016) Fourier Granger causality test. The results support the evidence of a causality relationship from composite leading indicators to BIST100, BIST Financial and BIST Industrial Indexes under structural breaks.en_US
dc.language.isoengen_US
dc.publisherSosyoekonomi Soc.en_US
dc.relation.ispartofSosyoekonomien_US
dc.identifier.doi10.17233/sosyoekonomi.2020.01.07en_US
dc.identifier.doi10.17233/sosyoekonomi.2020.01.07
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectComposite Leading Indicatorsen_US
dc.subjectStock Market Indicesen_US
dc.subjectStructural Breaksen_US
dc.titleForecasting Stock Market Indices with the Composite Leading Indicators: Evidence from Turkeyen_US
dc.typearticleen_US
dc.departmentİktisadi ve İdari Bilimler Fakültesi, Uluslararası Ticaret ve Finans Bölümüen_US
dc.identifier.volume28en_US
dc.identifier.issue43en_US
dc.identifier.startpage119en_US
dc.identifier.endpage134en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.institutionauthorKılcı, Esra N.en_US


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