Open AccessStochastic Modeling in Stock Market Trend Prediction
Author(s) -
N. Sonai Muthu,
AUTHOR_ID,
K. Senthamarai Kannan,
K. Karuppasamy,
Deneshkumar Venugopal,
AUTHOR_ID,
AUTHOR_ID,
AUTHOR_ID
Publication year - 2021
Publication title -
ymer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.103
H-Index - 5
ISSN - 0044-0477
DOI - 10.37896/ymer20.12/66
Subject(s) - notice , econometrics , stock market , markov chain , hidden markov model , stock exchange , incentive , economics , stock (firearms) , financial economics , computer science , mathematics , statistics , artificial intelligence , engineering , finance , microeconomics , geography , mechanical engineering , context (archaeology) , archaeology , political science , law
n Modern centuries a lot of predicting techniques take been proposed and applied for the stock market movement prediction. In this paper, the pattern examinations of the financial exchange forecast are introduced by utilizing Hidden Markov Model with the one day distinction in close incentive for a particular period. The likelihood esteems π gives the pattern level of the stock costs which is determined for all the notice arrangement and stowed away successions. It supports for decision makers to make decisions in case of indecision on the basis of the proportion of probability values found from the steady state probability distribution.