A new estimation method for regime-switching autoregressive density functions
Although the regime-switching autoregressive model is a popular topic in economic literature, the estimation of this model with small sample sizes has rarely been addressed in financial areas. This model, also referred to as the autoregressive hidden Markov, and its associated estimation method can also be found in speech recognition literature. After careful examination of the estimation method in speech recognition literature, we learn that a non-ignorable approximation occurs, which can only be justified under the circumstances of extremely long data sequences in the field of speech recognition. For this reason, we develop an original parsimonious estimation method for the autoregressive linear regime-switching model in economic fields. The positive semi-definite correlation matrix issue is considered and addressed in our estimation method. Stability and accuracy is also examined.
regime-switching autoregressive model hidden markov speech recognition financial model correlation matrix adjustment