Evolving Technical Trading Strategies Using Genetic Algorithms: A Case About Pakistan Stock Exchange

Basit Tanvir Khan, Noman Javed, Ambreen Hanif, Muhammad Adil Raja

Abstract: Finding optimum trading strategies that maximize profit has been a human desire since the inception of the first stock market. Many techniques have been employed ever since to accomplish this goal without sacrificing much computational power and time. In this paper, Genetic Algorithms (GAs) are used to achieve the aforementioned objectives. The performances of trading strategies devised by the GA are compared with the performance of the infamous Buy and Hold (B&H) Strategy. The stocks on which the performances are compared belong to Pakistan Stock Exchange (PSX). The strategies generated by GA outperform the B&H strategies on these stocks.