Measuring Volatility Clustering in Stock Markets
Statistical Finance
2008-12-02 v1 Data Analysis, Statistics and Probability
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.
Cite
@article{arxiv.0709.2416,
title = {Measuring Volatility Clustering in Stock Markets},
author = {Gabjin Oh and Seunghwan Kim and Cheoljun Eom and Taehyuk Kim},
journal= {arXiv preprint arXiv:0709.2416},
year = {2008}
}