LAUSR

PurposeThe authors provide a comparative analysis between emerging and developed financial markets in terms of the effects of political risks on stock market returns and volatility. The authors also examine whether this impact depends on the nature of political risks. Therefore, this study aims to detect which financial markets are the most profitable and the riskiest in terms of political risks.Design/methodology/approachThe authors investigate the impact of political risks on the excess stock market return and its conditional volatility using the generalized ARCH model for a sample of 46 developed and emerging markets over a period ranging from 1995 to 2019. In order to test how the nature of political risks affects equity excess returns and volatility differently in different markets, the authors employ (1) a composite political risk score, (2) the four subgroups of political risks as defined by Bekaert et al. (2005, 2014) and (3) the individual dimensions of political risks.FindingsThe findings indicate that the composite political risk is priced into both stock markets. The effect of political risks is positive for excess returns and negative for volatility. The authors show that the political risk leads to more volatility in developed markets. Nevertheless, the effect of individual components varies according to the market category.Practical implicationsThe authors provide a framework for predicting market returns and volatility using changes in the political risk of the country. The findings help investors make investment decisions based on the political decisions of governments. In other words, investors should consider political uncertainty when determining their expected earnings.Originality/valueThe authors engage monthly panel data methodology in terms of the political risk stock market relationship. In addition, the authors consider recent and very long data covering the period 1995–2019. Furthermore, this study combines three various political risk measures, and both equity returns and volatility.