Evaluating the Approach of Active and Passive Investors in Detecting Ponzi Patterns for Capital Market Financial Decision-Making
Keywords:
Active investors, passive investors, Ponzi pattern detectionAbstract
The objective of this study was to evaluate the differences between active and passive investors in detecting Ponzi patterns and to determine the reliability of their approaches in capital market financial decision-making. This semi-experimental and ex post facto study was conducted using data from 103 companies listed on the Tehran Stock Exchange over the period 2019–2024, resulting in 515 firm-year observations. A composite Ponzi detection index was developed based on five indicators, including financial risk identification, financial sensitivity, financial crisis, bankruptcy risk, and key performance indicators. Data analysis was performed using leptokurtic distribution modeling, quantile regression, nonlinear GARCH modeling, and artificial neural network analysis. Additionally, to distinguish between investor types, the Markowitz portfolio model was used to represent active investors, and the Sortino portfolio model was used to represent passive investors. Model evaluation criteria included the coefficient of determination, mean squared error, and mean absolute error. Inferential analysis revealed that the financial risk identification index had the highest predictive power in detecting Ponzi patterns among the evaluated indicators. Quantile regression results confirmed that the proposed composite index significantly explained Ponzi-related financial risk compared to the overall market index. Furthermore, comparative analysis of portfolios showed that the Markowitz portfolio had a significantly higher coefficient of determination and predictive reliability than the Sortino portfolio, indicating superior effectiveness of active investors in identifying and managing Ponzi-related risks. The findings confirmed a statistically significant difference between active and passive investor approaches in detecting Ponzi patterns. The results demonstrated that active investors have greater capability than passive investors in detecting Ponzi patterns and evaluating associated financial risks, and the use of financial risk-based analytical models can significantly improve financial decision-making quality and enhance capital market efficiency.
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Copyright (c) 2025 Ahmad Tavakoli (Author); Allah Karam Salehi (Corresponding author); Alireza Aghabeiki Alughareh, Shahrokh Bozorgmehrian (Author)
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