Development of a Comprehensive Model for Predicting Stock Prices in the Stock Market Using an Interpretive Structural Modeling Approach

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Department of Industrial Management, Faculty of Management and Accounting, Rasht Branch, Islamic Azad University, Rasht, Iran.

2 Associate Prof., Department of Industrial Management, Faculty of Management and Accounting, Rasht Branch, Islamic Azad University, Rasht, Iran.

3 Assistant Prof., Department of Accounting, Faculty of Accounting, Nowshahr Branch, Islamic Azad University, Nowshahr, Iran.

10.22059/frj.2023.364348.1007501

Abstract

Objective
This study aims to create a comprehensive stock price prediction model for the Tehran Stock Exchange by employing both fuzzy Delphi and interpretive structural modeling techniques. The research is innovative in that it incorporates all relevant factors from technical, fundamental, macroeconomic, and sentiment perspectives for stock price forecasting. This integration is facilitated through mathematical hierarchical modeling to pinpoint the most significant and responsive criteria for predicting stock prices.
 
Methods
Initially, due to potential uncertainties in expert responses, the fuzzy Delphi method was employed. Data analysis identified 54 stock price prediction criteria extracted from the literature. These were presented in two stages to experts and investors in the Tehran Stock Exchange industry as well as university professors. Accordingly, 15 criteria were selected as the most significant and influential, including five technical indicators: exponential moving average, price channel, relative strength, on-balance volume, and price. Additionally, the exchange rate from the macroeconomic component; trading volume from the behavioral component; price-to-earnings ratio, operating profit margin, gross profit margin, sales growth rate, dividend per share, earnings per share, and purchase per share from the fundamental component were chosen. Subsequently, using interpretive structural modeling, the relationships among them were examined and a hierarchical model was established. Interpretive structural modeling aids in determining the sequence and purpose of complex interrelationships among elements within a system.
 
Results
The findings from the interpretive structural modeling revealed that the price-to-earnings per share ratio and the money flow index are positioned at the bottom of the hierarchy, indicating they possess a high driving force in influencing stock prices. Because the product pricing methods of organizations have a significant impact on purchases by investors, the expansionary or contractionary monetary policy plays a crucial role in pricing. The criteria at the bottom of the hierarchy include the exchange rate, a key macroeconomic factor, along with the relative strength indicator and the exponential moving average, both of which are considered significant technical indicators. The findings of this research provide organizations, investors, and active industries in the stock market with a hierarchical model of the most significant factors influencing stock prices in the Tehran Stock Exchange.
 
Conclusion
The results from interpretive structural modeling show that macroeconomic variables such as inflation rate, liquidity growth rate, and exchange rate can significantly influence stock prices. This influence occurs because individuals maintain diverse portfolios of cash, stocks, bank deposits, participatory bonds, gold, and foreign currency. Additionally, these variables impact the financial health of economic enterprises, which in turn affects their stock values.

Keywords

Main Subjects

References

 
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Financial Research Journal
Volume 26, Issue 3
2024
Pages 630-650

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