Markov chains are the stochastic processes that have many application areas. The data that belong to the system being analyzed in the Markov chains stem from a single source. The multivariate Markov chain model is a model that is used for the purpose of showing the behavior of multivariate categorical data sequences produced from the same source or a similar source. In this study we explain the multivariate Markov chain model that is based on the Markov chains from a theoretical standpoint in detail. As for an application, we take on the daily changes that occur in the S&P-500 Index in which the shares of the 500 greatest companies of the United States of America are traded and the daily changes that occur in the UK FTSE 100 Index as two categorical sequences. And we display the proportions that show how much they influence each other via a multivariate Markov chain model.
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