A GARCH-based method for clustering of nancial time series: International stock markets evidence

In this paper, we introduce a volatility-based method for clustering analysis of …nancial time series. Using the generalized autoregressive conditional heteroskedasticity (GARCH) models we estimate the distances between the stock return volatilities. The proposed method uses the volatility behavior of the time series and solves the problem of di¤erent lengths. As an illustrative example, we investigate the similarities among major international stock markets using daily return series with di¤erent sample sizes from 1966 to 2006. The data were divided into two sample periods: previous and subsquent to the terrorist attack on September 11, 2001. From cluster analysis in the period before 9-11, most European markets countries, United States and Canada appear close together, and most Asian/Paci…c markets and the South/Middle American markets appear in a distinct cluster. After 9-11, the European stock markets have become more homogenous, and North American markets, Japan and Australia seem to come closer.