CiteSeerX — A Six State HMM for the S&P Stock Market Index
The unique characteristic of HMMs is the fact that the underlying system state is not directly observable. In this research, we utilize the existing Hidden Markov chain mathematical techniques to model the dynamic behavior of selected stock market equities. In particular, various methods will be research The Hidden Markov Models HMMs provide a flexible general purpose approach for modeling various dynamic systems that can be observed through univariate or multivariate time series.
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