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

Advances in Mathematical Finance and Applications

مقاله 20، دوره 8، شماره 2، مرداد 2023، صفحه 703-718   

نوع مقاله: َApplied-Research Paper

شناسه دیجیتال (DOI): 10.22034/amfa.2022.1943966.1651

نویسندگان

Hamidreza Kordlouie^{* 1}؛ Abbas Salehi Fard²؛ Mahdi Ebrahimi Moghaddam³؛ Shadi Shahverdiani⁴

¹Eslamshahr Branch, Islamic Azad University

²Department of Humanities, Shahr-e-Quds Azad University, Iran.

³Department of Humanities, Shahr-e-Quds Azad University, Iran

⁴Islamic Azad University of Shar-e-Ghods

چکیده

One of the important factors in making a profit through financial markets is a quick and correct response to market events, which is possible only by examining all aspects of the market. Today, to solve this challenge, the use of trading algo-rithms has become inevitable and can be considered as transactions made by computers that these transactions are controlled and reviewed through algorithms. Depending on their type and purpose, these algorithms examine different aspects and, according to the strategies defined for them, make decisions and signal by order registration. These trading methods are growing rapidly in the world, espe-cially in strong and developed financial markets. Proper implementation of algo-rithmic transactions reduces transaction costs and increases the accuracy of inves-tors in their investments. One of the most widely used of these strategies is the trend-following strategy, which is welcomed by many traders. This strategy can be implemented in different ways and through different trading tools. In the pre-sent study, five types of them were examined and implemented on one of the most traded symbols of the Tehran Stock Exchange. The purpose of this study is to implement some of the popular strategies in algorithmic trading along with the introduction of algorithmic trading, its strategies in the Iranian stock market, which includes the study of its advantages and disadvantages. The present study is a cross-sectional retrospective and field survey in terms of applied purpose and in terms of data collection.

کلیدواژه‌ها

Algorithmic Trading؛ Auto-mated Trading؛ Trading Strate-gies؛ Capital Market؛ Python

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