The dynamics of the capital market is recognized as a key factor in the economic growth of countries. The reactions of stock market participants to changes in macroeconomic variables can have both positive and negative effects on the market. Identifying existing threats and transforming them into opportunities is of particular importance. Purpose: Given the complexities of financial market structures and human behaviors, designing a simulation model to manage these complexities appears to be essential. This research focuses on the development of a model for the financial analysis of the country's stock market. Design and methodology: After examining the market structure and price microstructures, broader characteristics have been predicted using a qualitative and inductive approach, resulting in a conceptual model design. The analysis and comparison of artificial markets, along with a comparative study and the use of a mixed-method approach to integrate human behaviors with quantitative and qualitative research techniques, constitute the next steps of this research. Ultimately, simulation technology has been utilized as a third method in scientific research approaches. The research is considered descriptive and practical in its objectives. For simulation purposes, the effective factors and their interactions have been identified and implemented as programming objects in NetLogo. The model validation has been conducted based on the proposed methods of Ronald Rust and William Rand, and sensitivity analysis has been performed according to Borgonov's systematic approach. Findings: The findings indicate the impact of macroeconomic variables on the decisions of marketmakers, portfolio managers and investment funds concerning the growth of the overall stock index.
Heydari et al. (2025) studied this question.