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A Comparative Study on the Forecasting Performance of Range Volatility Estimators using KOSPI 200 Tick Data
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 김은영 | - |
| dc.contributor.author | 박종해 | - |
| dc.date.accessioned | 2022-12-27T05:23:01Z | - |
| dc.date.available | 2022-12-27T05:23:01Z | - |
| dc.date.issued | 2009 | - |
| dc.identifier.issn | 1225-0759 | - |
| dc.identifier.issn | 2734-0759 | - |
| dc.identifier.uri | https://scholarworks.gnu.ac.kr/handle/sw.gnu/26522 | - |
| dc.description.abstract | This 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.extent | 21 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | 한국재무관리학회 | - |
| dc.title | A Comparative Study on the Forecasting Performance of Range Volatility Estimators using KOSPI 200 Tick Data | - |
| dc.title.alternative | A Comparative Study on the Forecasting Performance of Range Volatility Estimators using KOSPI 200 Tick Data | - |
| dc.type | Article | - |
| dc.publisher.location | 대한민국 | - |
| dc.identifier.bibliographicCitation | 재무관리연구, v.26, no.2, pp 181 - 201 | - |
| dc.citation.title | 재무관리연구 | - |
| dc.citation.volume | 26 | - |
| dc.citation.number | 2 | - |
| dc.citation.startPage | 181 | - |
| dc.citation.endPage | 201 | - |
| dc.identifier.kciid | ART001363064 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.subject.keywordAuthor | Range Volatility Estimator | - |
| dc.subject.keywordAuthor | Two-scale Realized Volatility Estimator | - |
| dc.subject.keywordAuthor | Forecasting Performance | - |
| dc.subject.keywordAuthor | KOSPI 200 | - |
| dc.subject.keywordAuthor | Range Volatility Estimator | - |
| dc.subject.keywordAuthor | Two-scale Realized Volatility Estimator | - |
| dc.subject.keywordAuthor | Forecasting Performance | - |
| dc.subject.keywordAuthor | KOSPI 200 | - |
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