Clustering financial time series: New insights from an extended hidden Markov model
A model-based clustering technique is used in mining financial time series data. The model allows unobserved heterogeneity between and within time series. In the analysis of stock markets, the best model has two groups and three regimes. The model performs well in capturing different regime dynamics of stock markets.
hidden markov model data mining stock indexes latent class model regime-switching model