Designing and Evaluating Trading Strategies Based on Algorithmic Trading in Iran’s Capital Market

One of the important factors for achieving profitability in financial markets is the ability to respond quickly and accurately to market events, which can only be accomplished by thoroughly examining all aspects of the market. Nowadays, the use of trading algorithms has become essential to tackle this challenge. Trading algorithms can be defined as computer-controlled transactions that are monitored and executed through algorithms. Depending on their type and purpose, these algorithms analyze various aspects of the market and, based on predefined strate gies, make decisions and generate signals for order placement. The utilization of algorithmic trading is rapidly expanding worldwide, particularly in robust and developed financial markets. Proper implementation of algorithmic trading reduc es transaction costs and enhances investors accuracy in their investments. One of the most commonly employed strategies in algorithmic trading is the trend following strategy, which is favored by many traders. This strategy can be imple mented in various ways and using different trading tools. In this study, five types of these strategies were examined and implemented on one of the most actively traded symbols on the Tehran Stock Exchange. The objective of this study is to implement popular strategies in algorithmic trading and provide an overview of algorithmic trading, its strategies in the Iranian stock market, and an analysis of its advantages and disadvantages. The study adopts a cross-sectional retrospective and field survey approach in terms of its applied purpose and data collection.