A markov model for investigating the stock market volume behavior

In recent decades, the stock market prediction has become a high research area due to its immense importance not only for every profitable industry, but also for shareholders and investors to hug out a self-assured decision for a good investment into the stock market. This paper provides a discrete time stochastic model for the behavior analysis of stock market volume, applying the Markov model. The proposed model is validated in terms of model assumptions to predict the stock market behavior. An illustration, the top ten largest global banks’ stock market behaviors through the steady-state distributions and expected number of transitions are discussed. Wherein the secondary datasets for 505 days of volumes from 1 of January 2014 to 31 of December 2015, 2 year duration are used in each bank.