Abstract
The research study is to construction of a hidden Markov model (HMM) for
monthly closing prices of the Bombay Stock Exchange (BSE) and Indian
Bank. The transition states of BSE are taken as hidden and the
transition states of BSE to Indian bank are taken as visible. The
parameters of the HMM namely initial probability vector (IPV),
transition probability matrix (TPM) and observed probability matrix
(OPM) obtained by assuming the discrete Markov chains among (i) within
hidden states (Increment, Remain Same &Decrement in BSE) and (ii)
between hidden and observed states (Gain, Normal &Fall in Indian
bank) respectively. Probability distributions for one month ahead are
developed separately on Gain, Normal & Fall states. Explicit
mathematical relations of different statistical measures and the
Person‟s coefficient are explored for observing the behaviour of Gain,
Normal and Fall states in the monthly closing price of Indian bank.
Numerical computations are done for proper understanding of the
constructed models. These models will be helpful for the long-term
business investors for getting the indicators on when to sell and when
to buy the shares observing the probability of emission states. This
study is useful for portfolio managers for guiding the investors.
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