Investigating the Impact of Macroeconomic Variables on the Systematic Risk of the Top 50 Companies in the Iranian Stock Exchange: A Bayesian Model Averaging Approach

Since unsystematic risk can be mitigated through diversification of the asset portfolio, the focus of researchers and investors has increasingly shifted towards systematic risk and its determinants. The global financial crisis of 2007 brought significant economic turmoil and triggered a substantial chain reaction within the financial sector, which further amplified the emphasis on systematic risk as a critical factor related to financial stability. Consequently, due to the growing significance of systematic risk and the necessity for companies to respond appropriately, it becomes imperative to investigate the factors that influence systematic risk. In fact, an understanding of the factors impacting the level of systematic risk is a prerequisite for the implementation of effective risk management measures.



Moreover, beta, as a measure of systematic risk, cannot be directly assessed through stock price movements for unlisted firms, presenting challenges in estimating the cost of capital and the relative risk profiles of these entities. Therefore, the development of a model capable of predicting systematic risk using macroeconomic variables is a research priority. The multitude of variables that potentially affect systematic risk necessitates experimental research to identify the most salient among them. Despite the extensive body of research examining the determinants of systematic risk in corporate stock, there exists a paucity of theoretical modeling addressing the macroeconomic determinants of this variable. Furthermore, existing studies often rely on an arbitrary selection of independent variables without comprehensive theoretical foundations.



There exists considerable debate regarding the variables influencing systematic risk and their inclusion in the model. These differing viewpoints have resulted in disparate outcomes across various studies. Given the importance of systematic risk and the lack of comprehensiveness in prior research, the present study employs the Bayesian Model Averaging (BMA) approach to analyze the effects of macroeconomic variables on the systematic risk of companies listed on the Tehran Stock Exchange during the period from 2015 to 2015, encompassing a total of 72 periods. Recognizing that the values of macroeconomic variables are consistent for all companies within a given year, cross-sectional analysis is deemed inadequate. Thus, this research utilizes the systematic risk of a sample portfolio of stocks over time, specifically selecting a common portfolio comprising 50 actively listed companies in the Iranian stock market.



Accordingly, the dependent variable in this study is the beta of the portfolio comprising the 50 most active stocks, with 14 macroeconomic variables identified as potential explanatory variables. The findings indicate that among the variables examined, a total of eight variables exert the most significant influence on systematic risk. Notably, the housing rental price index and the consumer price index rank first and second, respectively, in their impact. The average coefficient for the housing rent variable is positive, while the average coefficient for the consumer price index is negative. Following these, the unemployment rate and the amount of foreign assets held by the banking system rank third and fourth, respectively; the average coefficient for the unemployment rate is positive, whereas foreign assets exhibit a negative average coefficient. Liquidity is positioned fifth with a positive coefficient. Lastly, government expenditures and the price of gold coins serve as the sixth and seventh explanatory variables, respectively, with PIP values exceeding 0.5, demonstrating negative and positive average effects on the systematic risk of the stock portfolio comprising the top 50 companies.