Forecasting the KOSPI200 spot volatility using various volatility measures

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dc.contributor.authorChun, Dohyunko
dc.contributor.authorCho, Hoonko
dc.contributor.authorRyu, Doojinko
dc.date.accessioned2018-12-20T05:08:43Z-
dc.date.available2018-12-20T05:08:43Z-
dc.date.created2018-12-03-
dc.date.created2018-12-03-
dc.date.issued2019-01-
dc.identifier.citationPHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, v.514, pp.156 - 166-
dc.identifier.issn0378-4371-
dc.identifier.urihttp://hdl.handle.net/10203/247595-
dc.description.abstractThis study examines the volatility forecasting performance of various historical and implied volatility measures. We compare the informational efficiency of lagged realized volatility, GARCH-family volatilities, out-of-the-money (OTM) and at-the-money (ATM) implied volatilities, and the market volatility index (VKOSPI) using univariate and encompassing regression analyses. We find that historical and implied volatility both have good predictive ability, but are biased estimators of future volatility. Furthermore, the information content of the implied volatility constructed from slightly OTM options encompasses that of the deep OTM and ATM options. In general, the VKOSPI exhibits the best forecasting performance among the volatility measures analyzed in this study. However, incorporating GJRGARCH volatility, which exhibits the best performance among the GARCH-family volatilities, in the prediction model possibly improves the explanatory power of the VKOSPI. (C) 2018 Published by Elsevier B.V.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE BV-
dc.titleForecasting the KOSPI200 spot volatility using various volatility measures-
dc.typeArticle-
dc.identifier.wosid000450137000016-
dc.identifier.scopusid2-s2.0-85053847810-
dc.type.rimsART-
dc.citation.volume514-
dc.citation.beginningpage156-
dc.citation.endingpage166-
dc.citation.publicationnamePHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS-
dc.identifier.doi10.1016/j.physa.2018.09.027-
dc.contributor.localauthorCho, Hoon-
dc.contributor.nonIdAuthorRyu, Doojin-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorEncompassing regression-
dc.subject.keywordAuthorGARCH-
dc.subject.keywordAuthorImplied volatility-
dc.subject.keywordAuthorVolatility forecasting-
dc.subject.keywordAuthorVKOSPI-
dc.subject.keywordPlusSTOCK-MARKET VOLATILITY-
dc.subject.keywordPlusIMPLIED VOLATILITY-
dc.subject.keywordPlusINFORMATION-CONTENT-
dc.subject.keywordPlusSTOCHASTIC VOLATILITY-
dc.subject.keywordPlusASSET RETURNS-
dc.subject.keywordPlusOPTION PRICES-
dc.subject.keywordPlusCONDITIONAL HETEROSKEDASTICITY-
dc.subject.keywordPlusEMERGING MARKETS-
dc.subject.keywordPlusINDEX OPTIONS-
dc.subject.keywordPlusDYNAMICS-
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