An Examination of the Validity of Systematic Risks for Nonfinancial Firms

Purpose: This study empirically investigates the macroeconomic and institutional determinants of systematic risk for non-financial firms listed on the Dow Jones and NASDAQ indices over the period 2000Q4 to 2023Q1. Employing both historical beta and stochastic beta estimations, the study provides a comprehensive analysis of how external economic conditions and governance quality shape firms’ exposure to market-wide risk. Design/methodology/approach the study utilized panel data regression models, incorporating macroeconomic indicators like GDP growth, inflation, the Effective Federal Funds Rate (EFFR), unemployment rate, and the Volatility Index (VIX), as well as institutional quality proxies drawn from the Worldwide Governance Indicators (WGI), including regulatory quality, political stability, and voice and accountability. Findings reveal that EFFR consistently exerts a statistically significant and negative effect on systematic risk, while inflation displays a positive but model-sensitive relationship. Institutional variables, particularly regulatory quality, political stability, and voice and accountability, are found to significantly reduce systematic risk, underscoring the stabilizing role of strong governance structures. In contrast, GDP growth and unemployment exhibit fragile or inconsistent associations with beta, suggesting context-dependent effects. By integrating traditional and simulation-based approaches to risk estimation, this study enhances the understanding of systematic risk under uncertainty and highlights the importance of institutional environments in moderating market volatility. Contribution: This paper contributes meaningfully to the existing literature and to financial practice by providing a comprehensive and empirically grounded assessment of the determinants of systematic risk for non-financial firms in developed markets. Its importance lies in several key dimensions. First, the paper addresses a critical research gap by focusing on the differential impact of macroeconomic factors on systematic risk, measured via both historical and stochastic beta. While most prior studies focus on financial firms or rely solely on conventional beta estimations, this research introduces a broader perspective by including non-financial sectors and incorporating parameter uncertainty through Monte Carlo simulation. This enhances the robustness and generalizability of the findings.