PURPOSE: Political uncertainty strongly affects corporate performance and portfolio returns in emerging capital markets, yet validated political risk indicators have rarely been integrated into efficiency-based portfolio optimization. This study proposes a risk-adjusted data envelopment analysis (DEA)–Malmquist framework for portfolio selection in the Iranian capital market.
DESIGN/METHODOLOGY/APPROACH: Political risk indicators were identified through a systematic literature review and validated by an eleven-member expert panel using the content validity ratio and content validity index. The validated indicators were then entered as additional inputs into an input-oriented super-efficiency DEA model, and dynamic performance was assessed with the Malmquist productivity index. The framework was applied to panel data for 106 firms listed on the Tehran Stock Exchange and Iran Fara Bourse over 2009–2023, and the resulting efficiency and productivity measures were used to construct a twenty-stock portfolio.
FINDINGS: Risk-adjusted super-efficiency scores differ substantially across firms and industries, and productivity change varies widely, driven by both technical efficiency change and technological change. The selected twenty-stock portfolio is weighted toward pharmaceutical and automotive-parts firms that combine relatively high efficiency and productivity growth with lower exposure to political shocks.
RESEARCH IMPLICATIONS: Treating political risk as an explicit component of efficiency measurement, rather than as an external factor, offers investors, portfolio managers, and policymakers a structured decision-support tool for building more resilient portfolios in politically uncertain environments.
ORIGINALITY/VALUE: The study combines expert-validated political risk indicators, super-efficiency DEA, and the Malmquist productivity index within a single portfolio-selection framework for an emerging market exposed to sanctions and policy uncertainty.