New investor behavior in capital market "algorithmic trade"

Advances in communication technologies and digitalization of stock markets have reduced the costs of accessing the markets. One of the important developments in recent years is algorithmic trading, which increases the speed of data processing by investors, reduces the cost of implementing trading strategies and accelerates the trading of securities. Trading algorithms have the potential to handle the vast majority of all trades, which has revolutionized the capital markets. It is thought that algorithmic trading applications will help capital markets work more effectively and efficiently by eliminating market inefficiencies. In this study, a simple moving average genetic algorithm was used. The algorithm has been applied to an investment in the BIST 30 index portfolio designed in different short-term and long-term (position) scenarios. As a result of the application of the genetic algorithm, the returns and performances of the investment in different scenarios were analyzed. According to the results of the research; In investments made in the BIST 30 index portfolio in different scenarios, positive or negative returns at different rates can be obtained by using similar or different SMA genetic algorithms. The results show that algorithmic trading transactions applied to the buying and holding of the BIST 30 index portfolio can provide better returns and performances than normal trading transactions.