Analyzing SBI Share Price Volatility: A Novel Mathematical Exploration with the Markovian Model

By transferring inactive cash from surplus to deficit units in the economy, the stock market plays a significant part in facilitating financial transactions in developing as well as developed nations. Stock market forecasting is observed as one of the most difficult undertakings in today's financial sector. As a result, much emphasis has been placed on scrutiny and prediction of future standards and performance of the financial time series. Business cycles, interest rates, monetary policy, general economic conditions, traders' expectations, political events, and so on influence the stock market. Academic studies show that market price fluctuations are not random, but rather follow a highly non-linear, dynamic pattern. The aim of this written paper is to use a Markov model to detect volatility in SBI share prices. Markov chains are commonly used to describe a wide range of real-world scenarios including randomness. They are used in a variety of sectors, ranging from search engine page ranking to the investigation of genetics in biology. They are frequently used throughout the finance and economics fields to describe unpredictability and anticipate the value of assets in addition to the changes in macroeconomic circumstances such as recession and expansion cycles.