Designing and Presenting Trading Strategies Based on Algorithmic Transactions in Iran's Capital Market

Algorithmic trading has a significant share in global markets. These types of transactions are also emerging in the domestic financial and capital markets. In this regard, in this study, to design and present several algorithms and trading strategies and implement and output five of the most important of these strategies using the Python programming language and compare their profitability. Has been. The study's statistical population includes all companies listed in the Iranian capital market. The sampling method is a stock selection from 30 large companies on the Tehran Stock Exchange index. The present research is applied in terms of purpose and terms of data collection, survey, and cross-sectional, in terms of subject, field, and time in terms of retrospective research. The results show that he used a different trading strategy in algorithmic trading to optimally use and compare and earn dividends of stocks traded in the future of the Iranian capital market. In the present study, five types of studies are implemented on one of the symbols of the Tehran Stock Exchange (Fars). One of the most practical strategies is to follow the trend that is welcomed by traders.