Abstract:
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 1st of January 2014 to 31st of December 2015, 2 year duration are used in
each bank.
