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dc.contributor.authorPopov, Valentin Mina
dc.date.accessioned2017-10-22T23:31:59Z
dc.date.available2017-10-22T23:31:59Z
dc.date.issued2016
dc.identifier.citationPopov , V M 2016 , ' Correlation estimation using components of Japanese candlesticks ' Quantitative Finance , vol. 16 , no. 10 , pp. 1615-1630 . DOI: 10.1080/14697688.2016.1157625en
dc.identifier.issn1469-7688
dc.identifier.otherPURE: 241427323
dc.identifier.otherPURE UUID: bfeae549-0820-4c19-93d5-5157ebb1552b
dc.identifier.otherScopus: 84964447012
dc.identifier.urihttp://hdl.handle.net/10023/11901
dc.description.abstractUsing the wick's difference from the classical Japanese candlestick representation of daily open, high, low, close prices brings efficiency when estimating the correlation in a bivariate Brownian motion. An interpretation of the correlation estimator in Rogers and Zhou (2008) in the light of wicks' difference allows us to suggest modifications, which lead to an increased efficiency and robustness against the baseline model. An empirical study on four major financial markets confirms the advantages of the modified estimator.en
dc.format.extent16en
dc.language.isoeng
dc.relation.ispartofQuantitative Financeen
dc.rights©2016, Informa UK Limited, trading as Taylor & Francis Group. This work is made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at www.tandfonline.com / https://dx.doi.org/10.1080/14697688.2016.1157625en
dc.subjectJapanese candlesticksen
dc.subjectCorrelationen
dc.subjectEstimationen
dc.subjectBrownian motionen
dc.subjectJump diffusionsen
dc.subjectQA Mathematicsen
dc.subjectNDASen
dc.subject.lccQAen
dc.titleCorrelation estimation using components of Japanese candlesticksen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.identifier.doihttps://doi.org/10.1080/14697688.2016.1157625
dc.description.statusPeer revieweden
dc.date.embargoedUntil22-10-20


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