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A Comparative Study on the Forecasting Performance of Range Volatility Estimators using KOSPI 200 Tick Data

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dc.contributor.author김은영-
dc.contributor.author박종해-
dc.date.accessioned2022-12-27T05:23:01Z-
dc.date.available2022-12-27T05:23:01Z-
dc.date.issued2009-
dc.identifier.issn1225-0759-
dc.identifier.issn2734-0759-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/26522-
dc.description.abstractThis study is on the forecasting performance analysis of range volatility estimators(Parkinson, Garman and Klass, and Rogers and Satchell) relative to historical one using two-scale realized volatility estimator as a benchmark. American sub-prime mortgage loan shock to Korean stock markets happened in sample period(January 2, 2006~March 10, 2008), so the structural change somewhere within this period can make a huge influence on the results. Therefore sample was divided into two sub-samples by May 30, 2007 according to Zivot and Andrews unit root test results. As expected, the second sub-sample was much more volatile than the first sub-sample. As a result of forecasting performance analysis, Rogers and Satchell volatility estimator showed the best forecasting performance in the full sample and relatively better forecasting performance than other estimators in sub-samples. Range volatility estimators showed better forecasting performance than historical volatility estimator during the period before the outbreak of structural change(the first sub-sample). On the contrary, the forecasting performance of range volatility estimators couldn’t beat that of historical volatility estimator during the period after this event(the second sub-sample). The main culprit of this result seems to be the increment of range volatility caused by that of intraday volatility after structural change.-
dc.format.extent21-
dc.language영어-
dc.language.isoENG-
dc.publisher한국재무관리학회-
dc.titleA Comparative Study on the Forecasting Performance of Range Volatility Estimators using KOSPI 200 Tick Data-
dc.title.alternativeA Comparative Study on the Forecasting Performance of Range Volatility Estimators using KOSPI 200 Tick Data-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.bibliographicCitation재무관리연구, v.26, no.2, pp 181 - 201-
dc.citation.title재무관리연구-
dc.citation.volume26-
dc.citation.number2-
dc.citation.startPage181-
dc.citation.endPage201-
dc.identifier.kciidART001363064-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorRange Volatility Estimator-
dc.subject.keywordAuthorTwo-scale Realized Volatility Estimator-
dc.subject.keywordAuthorForecasting Performance-
dc.subject.keywordAuthorKOSPI 200-
dc.subject.keywordAuthorRange Volatility Estimator-
dc.subject.keywordAuthorTwo-scale Realized Volatility Estimator-
dc.subject.keywordAuthorForecasting Performance-
dc.subject.keywordAuthorKOSPI 200-
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