This paper develops an efficient approach to model and forecast time-series data with an unknown number of change-points. Using a conjugate prior and conditional on time-invariant parameters, the predictive density and the posterior distribution of the change-points have closed forms. The...

Traditional methods used to partition the market index into bull and bear regimes often sort returns ex post based on a deterministic rule. We model the entire return distribution; two states govern the bull regime and two govern the bear regime, allowing for rich and heterogeneous intra-regime...

This paper proposes an infinite dimension Markov switching model to accommodate regime switching and structural break dynamics or a combination of both in a Bayesian framework. Two parallel hierarchical structures, one governing the transition probabilities and another governing the parameters...

This paper develops a methodology for nonparametric estimation of a polarization measure due to Anderson Ge and Leo (2006) based on kernel estimation techniques. We give the asymptotic theory of our estimator, which in some cases is non standard due to boundary value problems. We also propose a...