Stock market analysis with a Markovian approach: Properties and prediction of OMXS30

Abstract: This paper investigates how Markov chain modelling can be applied to the Swedish stock index OMXS30. The investigation is two-fold. Firstly, a Markov chain is based on index data from recent years, where properties such as transition matrix, stationary distribution and hitting time are studied. This first investigation shows, for example, signs of volatility clustering and a steady-state distribution that indicates a positive long term trend for OMXS30. Secondly, the predictive ability of a Markov model, consisting of a voting ensemble of ten Markov chains, is evaluated. The results show that a Markov model with six states has a prediction accuracy slightly above the performance of random chance. Moreover, there was no considerable difference in prediction accuracy between models with Markov chains of first and second order.