Abstract

Selling or buying a share in a stock market is now a matter of scientific decision-making mechanism. Investors are badly in need of the advice of mathematical model developers for understanding the pulse of the market. It leads to more attention from model builders to assess the market behavior. Hidden Markov models (HMMs) are inherent structures to spell out the linkage between invisible influencing factors on visible resulting states. Finance investment processes with two hidden and two visible states are formulated for obtaining the model and exploring the dynamics of gain/pain in the stock value. A generalized mechanism for a sequence of ‘n’ transactions with two visible states is modeled. Probability distributions for the single, of length two and three visible states are derived. Mathematical formulae for different statistical measures and various generating functions for the corresponding probability distributions are obtained in this paper. Understanding the model’s notion from a layman’s point of view, an empirical study was carried out with real-time historical stock market data of Reliance Industries limited. The pivotal objective of this study is to estimate the model parameters that measure the holistic changes in money values of different shares in a stock market. The finance and portfolio managers can make use of this study for designing optimal resource planning by understanding the relations of invisible factors to visible states. The development of user interface dynamic dashboards will make this work more popular and reachable to the community at large.

Author: Tirupathi Rao Padi, Gulbadin Farooq Dar and Sarode Rekha

Received on: September, 2022

Accepted on: January, 2023