Investigating stock market behavior using a multivariate Markov-switching approach

By stressing the latent nature of expected return and risk, we develop a two-step procedure for obtaining new insights into the properties of financial returns. The first step consists in achieving a time-constant classification of stocks into homogenous groups under the risk-return profile, thus providing innovative measures of expected return and risk. In the second step, we investigate the dynamic behavior of the stocks belonging to each group using multivariate Markov-switching models. We find evidence of different dynamic properties across groups of stocks and common dynamic properties within groups which can be exploited for both interpretative and predictive purposes