This paper describes a pairs trading strategy using cointegration approach. If cointegrated pairs are thought of as such pairs, whose linear combination is a stationary process, that is, a process with stable statistical properties, then any deviation from these characteristics will be transient. If you know that such a deviation has happened, that is, a departure from the long-term equilibrium, you can forecast the direction of stock price movements and execute lucrative trades accordingly. When the difference between stock prices exceeds the prediction, we must sell the overpriced asset and acquire the undervalued one, then close the deals when the price ratio returns to long-term equilibrium. This is one form of statistical arbitrage trading strategy. During the research, it was discovered that cointegration is dependent on a variety of factors, including the time period under consideration, and that this is not the only issue. When more recent data is given more weight, it is suggested that methods for determining cointegration be developed. The importance of setting the conditions for entering and terminating a transaction, as well as the possibility of “disappearing” cointegration are also noted as issues with employing cointegrated pairings for pair trading.