Non-Pecuniary Risk, ESG Ratings, and Expected Stock Returns

Portfolios incorporating environmental, social, and governance (ESG) criteria present distinct, unobserved risks, the empirical quantification of which has proven challenging. This difficulty stems from sustainable investment strategies being guided by both financial objectives and investors’ non-pecuniary preferences, which fundamentally alter a portfolio’s risk and return characteristics. To address this, we propose a novel methodology that identifies latent, ESG-specific risk factors by applying sparse principal component analysis (SPCA) to two-dimensional portfolio returns. Unlike approaches that rely on subjective judgment, our method extracts risk dimensions inherent to the return data itself. Our analysis reveals that the resulting firm-specific SPCA beta plays a dual role: it explains performance differentials across ESG-rated portfolios and exhibits a statistically significant, negative association with expected individual stock returns. The robust predictive performance of this SPCA-based risk factor confirms its practical utility for analyzing and managing diversification in ESG investing.