Designing a Financial Market Analysis Training Model for Institutional Investors Based on Market Forecasting and Data-Driven Learning
Pages 1-17
https://doi.org/10.22034/lss.2026.590426.1075
Razie Jahani, Ali Najafi Moghadam, Nowrouz Nourollahzadeh
Abstract This research aims to design a financial market analysis training model to improve the quality of institutional investors’ investment decisions. By examining the stock trends, gold, foreign exchange, and housing markets, this research has evaluated the future status of these markets as a basis for investment decision-making training. The results show that the stock market has experienced significant growth in different periods, including 2004, 2011, 2014, 2016, and 2019, and the peak of this trend in 2019 was accompanied by the recording of historical records of the Tehran Stock Exchange; However, after that, this market entered a period of stagnation and did not experience significant growth. The foreign exchange market also experienced relative growth in the first half of 2026, but then faced a downward trend. On the other hand, the housing and stock markets are still in a recession in 2026. Accordingly, the proposed model for teaching financial market analysis by emphasizing trend analysis, market forecasting and risk assessment can improve the decision-making ability of institutional investors and provide the basis for optimizing investment portfolios. Based on the forecasting results, a financial market analysis training model was proposed consisting of four main learning modules: market trend analysis, forecasting interpretation, risk assessment and portfolio diversification, and investment decision-making. The model integrates real market data, forecasting techniques, and case-based learning approaches to enhance institutional investors’ analytical competencies.
















