Designing a model for financial analysis and market player behavior in the stock market with an agent-based simulation approach

Subject Areas :

Seyed Farhad Gooran Heydari ¹ , Abbas Toloui eshlaghi ² , Ahmad Ebrahimi ³ , Mohammad Reza Motadel ⁴

1 - دانشجوی دکتری مدیریت فناوری اطلاعات علوم و تحقیقات تهران
2 - Professor, Department of Information Technology Management, Faculty of Management and Economics, Science and Research Unit, Islamic Azad University of Tehran, Iran
3 - Assistant Professor, Department of Industrial management and technology, Faculty of Management and Economics, Science and Research Unit, Islamic Azad University of Tehran, Iran
4 - Faculty Member

Received: 2024-06-27 Accepted : 2024-08-05 Published : 2024-02-20

Keywords: Agent-based simulation, stock exchange, macroeconomic variables, behavioral finance,

Abstract :

Given the importance of financial markets in the country's economic development and the inherent complexities of the economy and market microstructure due to the significant role of human behaviors, it seems necessary to design a simulated model that can surpass these complexities and provide control by analyzing the role of active players in the stock market. In this regard, leveraging the capabilities of agent-based modeling and simulation, we have embarked on designing a model for financial analysis of the country's stock market. After understanding the market structure and organization, we delve into the understanding of the microstructure and pricing mechanisms, moving from a qualitative and inductive approach to observing, studying, and investigating market realities relative to broader predictions and characteristics, and presenting a conceptual model. Through a comparative study, we analyze and compare artificial markets and combine human behavior with quantitative and qualitative research methods using a combinatory approach, utilizing simulation technology as a third scientific research method in addition to comparative and inductive approaches. The research is descriptive and applied in nature. For simulation, all influencing factors of the model and their interactions are determined and simulated as an object-oriented programming in NetLogo software. Model validation (according to the proposed framework and method by William Rand and Ronald Rust) and sensitivity analysis (following the systematic approach proposed by Borganoff for model validation) have been carried out. The results of the research show a significant correlation between the activities of market makers, portfolio managers, investment funds, and the average growth of the overall index, which is presented in all stages of the analytical and visual reports on the various ratios of their presence in the model.

References:

مختاربند، محمود، تهرانی، رضا، العبودة، منال. (1403). برآورد تأثیر عوامل بنیادین کلان اقتصادی بر بازار سرمایه (رویکرد داده‌های ترکیبی تواتر متفاوت). تحقیقات مالی DoI:10.22059/frj.2024.368065.1007538
ستوده رضا، هیراد علیرضا، براهویی پیرنیا بهاره. (1403). تبیین الگوی رفتاری تصمیم‌گیری سرمایه‌گذاران در بازار سرمایه کشور، پژوهش های مالی و رفتاری شماره 1 دوره 4، https://sanad.iau.ir/Journal/fbra/Article/1105360
وکیلی فرد حمیدرضا، خوشنود مهدی، فروغ نژاد حیدر، اصولیان محمد.(1393). مدل سازی مبتنی بر عامل در بازار های مالی. فصلنامه علمی پژوهشی دانش سرمایه گذاری
حبیبی مریم، برومندنیا علی، هارون آبادی علی. (1400). ارائه روش جدید به منظور مقابله با حملات منع خدمت توزیع شده در شبکه های نامدار با شبیه سازی عامل بنیان، فناوری اطلاعات و ارتباطات انتظامی، سال دوم، شماره دوم تابستان1400
محمدپور احمد،صادقی رسول،رضایی مهدی(1389). روش‌هاي تحقيق تركيبي به عنوان سومين جنبش روش شناختي. تهران: جامعه شناسی کاربردی. شماره دوم.
قربانی ناصر، بابائی ابراهیم. (1394). بررسی کارائی الگوریتم EMA در حل مسائل بهینه سازی. کرمانشاه : کنفرانس ملی فن آوری، انرژی و داده با رویکرد کامپیوتر.
آذر عادل ، سارنج علیرضا، صادقی مقدم علی اصغر، رجب زاده علی، معزز هاشم .(1397). مدلسازی عامل گرای رفتار سهامداران در بازار سرمایه ایران. فصلنامه تحقیقات مالی دوره ۲۰ شماره ۲
كياني رضا.(1396).بررسي فعاليت بازارگردان ويژه در بورس اوراق بهادار. تهران: سازمان بورس اوراق بهادار: مركز تحقيقات وتوسعة بازار سرماية ايران
کیائی‌علی،صندوق‌های‌سرمایه‌گذاری‌مشترک،ابزاری برای سرمایه‌گذاران ریسک‌گریز و بدون تخصص(1389).تهران: دانش حسابرسی سال دهم
هادی پور, حسن, پایتختی اسکویی, سیدعلی, علوی متین, یعقوب, رحمانی, کمال الدین. (1400). عوامل موثر بر شاخص بی‌ثباتی در بورس .مطالعات مدیریت صنعتی
ولی زاده, فرزانه, محمدزاده, امیر, صیقلی, محسن, ترابیان, محسن. (1400). ارائه مدلی برای پیش‌بینی عوامل مؤثر بر ریسک سقوط قیمت سهام. چشم انداز مدیریت مالی,
فخاری, حسین, نصیری, مهراب. (1399). تأثیر عملکرد شرکت بر ریسک سقوط آتی قیمت سهام. راهبرد مدیریت مالی, 8(3), 43
ابراهیمی، مهرزاد. (1398) بررسی تاثیر متغیرهای کلان اقتصادی بر بازار سهام ایران با استفاده از الگوریتم های داده کاوی. اقتصاد مالی شماره 49
Gao, Kang, Vytelingum, Perukrishnen, Weston, Stephen, Luk, Wayne and Guo, Ce (2024) 'High-Frequency Financial Market Simulation and Flash Crash Scenarios Analysis: An Agent-Based Modelling Approach' Journal of Artificial Societies and Social Simulation . DOI:10.18564/jasss.5403
Muhammad Asif Khan, Saima Aziz, Shahid Mehmood and Anita Tangl (2024). Role of behavioral biases in the investment decisions of Pakistan StockExchange investors: Moderating role of investment experience. Investment Management and Financial Innovations. doi:10.21511/imfi.21(1).2024.12
Tina Comes and Frances Brazier.(2023). A Methodology to Develop Agent-Based Models for Policy Support Via Qualitative Inquiry. Delft University of Technology, Netherlands Other articles by these authors Journal of Artificial Societies and Social Simulation 26 (1) 10.
Mizuta Takanobu، Kosei Takashima، Isao Yagi .Instability of financial markets by optimizing investment
strategies investigated by an agent-based model. (2022).Computational Intelligence for Financial Engineering and Economics.
Mizuta Takanobu.(2022). A Brief Review of Recent Artificial Market Simulation (Agent-Based Model) Studies for Financial Market Regulations and Rules.Available Sadek Benhammada ،Frédéric Amblard. (2021). An Agent-Based Model to Study Informational Cascades in Financial Markets. New Generation Computing.
Fouad Ben Abdelaziz ،Fatma Mrad.(2021). Multiagent systems for modeling the information game in a financial market. International Transactions in Operational Research.
Mizuta Takanobu.(2021).An Agent-Based Model for Designing a Financial Market That Works Well. IEEE Symposium Series on Computational Intelligence, Computational Intelligence for Financial Engineering and Economics (CIFEr).
Agliari, A., Naimzada, A., & Pecora, N. (2018). Boom-bust dynamics in a stock market participation model with heterogeneous traders. Journal of Economic Dynamics.
Ponta, L., Pastore, S., & Cincotti, S. (2018).Static and dynamic factors in an information based.
Matthew Duffin، John Cartlidge.(2018). Agent-Based Model Exploration of Latency Arbitrage in Fragmented Financial Markets. IEEE Symposium Series on Computational Intelligence
Muhammad Hanif، Arshad Bhatti.(2018). Causality among Stock Market and Macroeconomic Factors: A Comparison of Conventional and Islamic Stocks. Journal of Islamic Business and Management.
McNeil, Alexander J.; Frey, Rüdiger; Embrechts, Paul. (2005). Quantitative risk management: concepts, techniques and tools. Princeton University Press. pp. 2–3. ISBN 978-0-691-12255-7.
Horcher, Karen A. (2005). Essentials of financial risk management. John Wiley and Sons. pp.1–3. ISBN 978-0-471-70616-8
C. M. Macal and M. J. North. (2007). Agent-based modeling and simulation: Desktop ABMS, Winter Simulation Conference.
Rand, W., & Rust, R. T. (2011). Intern . J . of Research in Marketing Agent-based modeling in marketing : Guidelines for rigor. International Journal of Research in Marketing,
Emanuele Borgonovo،· Marco Pangallo، Jan Rivkin، Leonardo Rizzo، Nicolaj Siggelkow.(2022).Sensitivity analysis of agent‑based models: a new protocol. Computational and Mathematical Organization Theory 28:52–94
Edwin Achorn. (2004). Integrating Agent-Based Models with Quantitative and Qualitative Research Methods. Faculty of Education Monash University association for active educational researchers northwestern. ‏
Gilbert N., and Troitzsch K.(2008). Simulation For The Social Scientist. NewYork: Open University Press.
R. Axelrod. (2003). Advancing the Art of Simulation in the Social Sciences. Japanese Journal for Management Information System, Special Issue on Agent-Based Modeling,
Lev Muchnik, Yoram Louzoun, Sorin Solomon.(2006). Agent Based Simulation Design Principles-Applications to Stock Market ،. Practical Fruits of Econophysics