Markov Chain Model for NIFTY50 Index

Abstract

For the last two decades, financial market forecasting has been one of the sensational topics in research, but the market prediction is not easy because of its uncertainty. Though the trend is uncertain by its nature, some researcher is attempted to trace the movement with more accuracy. This study focuses on creating and analyzing a stochastic model that employs the Markov Chains method to anticipate stock prices on the stock exchange. By supposing that prices fluctuate have the feature of Markov dependence with their transition probabilities, study, four states are determined to construct the Markov model in this study. The daily fluctuations in the NIFTY 50 Index, which includes the top 50 firms of Indian stocks are tracked and analyzed. The TPM and IPV, the anticipated number of transitions, and the expected number of return times are established.