Designing and Evaluating Trading Strategies Based on Algorithmic Trading in Iran's Capital Market
محورهای موضوعی : Financial EngineeringHamidreza Kordlouie 1 , Abbas Salehi Fard 2 , Mahdi Ebrahimi Moghaddam 3 , Shadi Shahverdiani 4
1 - Eslamshahr Branch, Islamic Azad University
2 - Department of Humanities, Shahr-e-Quds Azad University, Iran.
3 - Department of Humanities, Shahr-e-Quds Azad University, Iran
4 - Islamic Azad University of Shar-e-Ghods
کلید واژه: Python, Capital Market, Auto-mated Trading, Algorithmic Trading, Trading Strate-gies,
چکیده مقاله :
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.
[1] Egham Reyhani, N., Nonlinear relationship between purchasing volume on stock prices in Tehran Stock Exchange, The 2nd National Conference on New Research in Accounting and Management in the Third Millennium, Karaj, 2018.
[2] Amrollahi Bioki, S., Khazanedai, M., A review of algorithmic transactions, Bourse Economic Journal, 2010, No. 94.
[3] Rastegar, M. A., Rahyani, Eghbal, N., Big order division strategy to reduce market reaction cost and investigate the intraday model of average market reaction and trading volume for accepted shares in Tehran Stock Exchange, The 4th International Conference on Management, Entrepreneurship and Economic Development, Takestan. 2018.
[4] Seyed Hosseini, M. M., Ahmadi, Z., Algorithmic stock transactions, Research Management, Development and Islamic Studies of Securities and Exchange Organization. 2014.
[5] Dastri, M., Fallahpour, S., Tehrani, R., Mehregan, M.R., High-frequency pair trading algorithm using fuzzy statistical quality control, Financial engineering and securities management, 37(9), P.23-41
[6] Gol Arzi, G., Ziachi, A., Study of Collective Behavior of Investors in Tehran Stock Exchange with an Approach Based on Trading Volume, Journal of Financial Research, 2014, 16(2), P.371-359
[7] Ahmadpour, A., Nasiri, M., Study of the effect of block transaction prices in the Iranian stock market, Journal of Financial Research, 2016, 18(1), P.23-38
[8] Mukerji, P., Chung, C., Walsh, Timothy., Xiong, Bo., The Impact of Algorithmic Trading in a Simulated Asset Market, Journal of Risk and Financial Management, 2019
[9] Fukuma, N., Kadogawa,Y., An Overview of Algorithmic Trading in Foreign Exchange Markets and Its Impacts on Market Liquidity, Bank of japan review, Japan, 2020
[10] Aldridge, I., High-Frequency Trading- A Practical Guide to Algorithmic Strategies and Trading Systems, 2015, Wiley, 2009
[11] Hervani, M., Khalili Araghi, M., Designing an algorithmic trading strategy with the introduction of moderating moving average indicator (AMA) to predict future stock price movement in Iran’s capital market. The 1st International Conference on Challenges and New Solutions in Industrial Engineering and Management and Accounting, Sari. (2020).
[12] Lo, A. W., Mamaysky, H., & Wang, J., Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation, The journal of finance, 1002-1012, 2000.
[13] Teixeira, L. A., De Oliveira, A. L. I., A method for automatic stock trading combining technical analysis and nearest neighbor classification, Expert systems with applications, 6885-6890, 2010.
[14] Preis, T., Moat, H. S., Stanley, H. E., Quantifying trading behavior in financial markets using Google Trends, Scientific reports, 1684, 2013.
[15] Fong, K. Y., Parwada, J. T., Yang, J. W., Algorithmic Trading and Mutual Fund Performance, 2018.
[16] Ponomarev, E.S., Oseledets, I.V., Cichocki, A.S., Using Reinforcement Learning in the Algorithmic Trading Problem, Journal of Communications Thechnology and Electronics, Russia, 2019.
[17] Abbasian-Naghneh, S., Tehrani, R., Tamimi, M. The Effect of JCPOA on the Network Behavior Analysis of Tehran Stock Exchange Indexes. Advances in Mathematical Finance and Applications, 2021, 6(3), P. 465-477, Doi: 10.22034/amfa.2019.1873319.1258
[18] Zanjirdar, M. Overview of Portfolio Optimization Models. Advances in Mathematical Finance and Applications, 2020, 5(4), P. 419-435. Doi: 10.22034/amfa.2020.674941
[19] Zangenehmehr, P., Farajzadeh, A. On Solutions of Generalized Implicit Equilibrium Problems with Application in Game Theory. Advances in Mathematical Finance and Applications, 2022, 7(2), P. 391-404. Doi: 10.22034/amfa.2021.1935453.1617
[20] Izadikhah, M. DEA Approaches for Financial Evaluation - A Literature Review, Advances in Mathematical Finance and Applications, 2022, 7(1), P. 1-36, Doi: 10.22034/amfa.2021.1942092.1639
[21] Agah, M., Malekpoor, H., Bagheri, A., Investigating the Effect of Financial Constraints and Different Levels of Agency Cost on Investment Efficiency. Advances in Mathematical Finance and Applications, 2017, 2(4), P. 31-47. Doi: 10.22034/amfa.2017.536264
[22] Karbasi Yazdi, H., Mohammadian, M., Effect of Profitability Indices on the Capital Structure of Listed Companies in Tehran Stock Exchange. Advances in Mathematical Finance and Applications, 2017, 2(3), P. 1-11. Doi: 10.22034/amfa.2017.533085
[23] Ahmadi, R., Kordloei, H., The Effect of Financial Distress on the Investment Behavior of Companies Listed on Tehran Stock Exchange. Advances in Mathematical Finance and Applications, 2018, 3(4), P. 17-28. Doi: 10.22034/amfa.2019.565459.1108