Evaluation of the Asset Pricing Model Based on Multiple Factors for Predicting Stock Returns in the Iranian Capital Market

Introduction : The main objective of this study is to evaluate the efficiency of multifactor models in predicting stock returns in the Iranian capital market. In this regard, the study aims to examine the role of various factors such as company size, book-to-market ratio, profitability, and investment policies in explaining stock returns and to determine their ability to explain return behavior in specific Iranian market conditions by comparing these models with single-factor models. It is also expected that in this regard, stock return prediction can provide investors, financial managers, and economic policymakers with a more accurate analytical tool and help improve the decision-making process. In the meantime, asset pricing models have been considered as one of the main axes in financial studies, and numerous efforts have been made to improve their explanatory power and predictability. The first serious attempt in this field was the single-factor capital asset pricing model (CAPM), which, despite its historical importance and wide applications, was unable to explain all changes in stock returns. This limitation led researchers to develop multi-factor models. The capital market, as one of the main pillars of the financial system, is also facing severe fluctuations such as structural risks and being affected by macroeconomic developments. In such a context, relying on multi-factor models can increase the accuracy of predicting stock returns and lead to a deeper understanding of investment risks and opportunities. The capital market, as one of the main pillars of the financial system, is also facing severe fluctuations such as structural risks and being affected by macroeconomic developments. In such a context, relying on multi-factor models can increase the accuracy of predicting stock returns and lead to a deeper understanding of investment risks and opportunities.

Methodology: The present study, in terms of data collection, is an exploratory approach and the research design is based on descriptive-correlation monitoring and is classified as fundamental research in terms of its purpose. The research data is collected based on actual stock market information and includes financial statements, audit reports, and information available in the official trading databases of the Stock Exchange. The statistical population of the study includes all companies listed on the Tehran Stock Exchange, approximately 550 companies. This population was studied over a 14-year period from 2009 to 2023. In order to increase the volume of data and improve the accuracy of the analyses, each fiscal year was divided into two six-month periods so that changes in stock returns and the factors affecting them could be tracked in more detail. Despite some limitations and inconsistencies in the available information on the companies, specific criteria were considered for sample selection. Finally, using the systematic elimination method, a sample of 130 companies was selected whose data was completely and reliably available. Data analysis was performed using analysis software. Here, first, in order to analyze the resulting data using Eviews10 software, the data were organized and interpreted in terms of alignment with the objectives.

Results: Based on the results of descriptive statistics, various financial, economic, stock market, corporate governance, and auditing variables show different patterns of stability and volatility. Stock returns are relatively stable and have less volatility, while financial structure and liquidity levels experience more variability. In the stock market, market value and liquidity have had the highest dispersion, which indicates high market risk and volatility, while the market growth rate has enjoyed relative stability. In the economic variables section, inflation has had the highest variability and acts as a variable affecting other indicators. Also, in the corporate governance area, the number of board members has fluctuated more, but the ownership structure and institutional ownership have shown relative stability. On the other hand, the variables related to the quality of financial reporting and auditing have changed slightly, which indicates the existence of standard frameworks and procedures in this area, and also due to the selection of the panel data model, in order to select a fixed effects model against a random effects model, the Hausman test is performed. The results of the Chow test in each model show that the probability error level of this test is less than 5 percent, so the fixed method is accepted in this test. In regression analysis, the results showed that most of the studied variables have a positive and significant relationship with stock returns. Variables such as the efficiency of the audit process with a coefficient of 0.8981, the liquidity level with a coefficient of 0.8978, and the market with a coefficient of 0.8122, have a high impact and have shown their high importance with a t-statistic above 3 and a significance of less than 0.005. Also, the financial risk ratio and auditor expertise have a significant effect on stock returns. The model's coefficient of determination of 0.944 indicates its high power in explaining changes in stock returns, and the adjusted coefficient of determination of 0.984 also indicates the acceptable predictive power of the model

Discussion : Based on the research results, multi-factor asset pricing models provide an efficient framework for predicting stock returns in the Iranian capital market. Unlike single-factor models such as CAPM that only consider market risk, the findings show that stock returns are affected by a set of financial, market, economic, governance, and audit factors. In the financial dimension, indicators such as capital structure, liquidity, net income, return on assets ratio, and debt-to-asset ratio have a significant effect on returns and indicate the importance of financial health and resource management. In the market domain, variables such as market return, growth opportunity, and book-to-market ratio with positive and significant coefficients confirm the role of market forces and investor expectations. From an economic perspective, factors such as inflation rate, economic growth, and cost changes have a high impact on stock performance and reveal the importance of macro conditions. In addition, the corporate governance structure, including board independence, ownership structure, and institutional ownership, increases transparency and reduces risk. Also, the quality of financial reporting and auditor independence are directly related to investor confidence and improved returns.