Abstract: 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 dynamics. Our model can capture bear market rallies and bull market corrections. A Bayesian estimation approach accounts for parameter and regime uncertainty and provides probability statements regarding future regimes and returns. Applied to 123 years of data our model provides superior identification of trends in stock prices.
Keywords: Markov switching, bear market rallies, bull market corrections, Gibbs sampling
JEL Classification: C11; C22; C50; G10