Measuring Volatility Clustering in Stock Markets

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dc.creatorOh, Gabjin
dc.creatorKim, Seunghwan
dc.creatorEom, Cheoljun
dc.creatorKim, Taehyuk
dc.date2007-09-15
dc.date.accessioned2026-07-07T12:05:25Z
dc.date.available2026-07-07T12:05:25Z
dc.descriptionWe propose a novel method to quantify the clustering behavior in a complex time series and apply it to a high-frequency data of the financial markets. We find that regardless of used data sets, all data exhibits the volatility clustering properties, whereas those which filtered the volatility clustering effect by using the GARCH model reduce volatility clustering significantly. The result confirms that our method can measure the volatility clustering effect in financial market.
dc.identifierhttps://arxiv.org/abs/0709.2416
dc.identifierhttp://arxiv.org/abs/0709.2416
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/208373
dc.subjectStatistical Finance
dc.subjectData Analysis, Statistics and Probability
dc.titleMeasuring Volatility Clustering in Stock Markets
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