A stochastic process, sometimes called a random process, is a family (collection) of random variables that exhibits the evolution of some random values ​​over time. There are two categories of stochastic processes: A discrete-time stochastic process described as a sequence of random variables known as a time series (Markov chain). The values ​​of the variables change at fixed points of time. Continuous-time stochastic processes are presented as a function whose values ​​are random variables with certain probability distributions. The values ​​of the variables change continuously over time. Good examples of stochastic process among many are exchange rate and stock market fluctuations, blood pressure, temperature, Brownian motion, random walking. A Markov chain is a stochastic process in which the past history of the variables is irrelevant. and only the present value is important for predicting the future one. Then the Markov chain property can be expressed as: Pr⁡(X_(n+1)=x┤| x┤|....