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Measuring Volatility Clustering in Stock Markets

Author

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  • Gabjin Oh
  • Seunghwan Kim
  • Cheoljun Eom
  • Taehyuk Kim

Abstract

We 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.

Suggested Citation

  • Gabjin Oh & Seunghwan Kim & Cheoljun Eom & Taehyuk Kim, 2007. "Measuring Volatility Clustering in Stock Markets," Papers 0709.2416, arXiv.org.
    • Handle: RePEc:arx:papers:0709.2416
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    File URL: http://arxiv.org/pdf/0709.2416
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