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 about the properties of financial returns. The first step consists in achieving a time-invariant 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 by using multivariate Markov-switching models. We find evidence of different dynamic features across groups of stocks and common dynamic properties within groups which can be exploited for both interpretative and predictive purposes.