Do investors in clean energy ETFs herd? The role of climate risks

Abstract

PURPOSE : This study aims to investigate herding behaviour in US Clean Energy (CE) exchange-traded funds (ETFs) and examine the role of climate risks in influencing such behaviour over the period from May 1, 2016, to June 19, 2024. DESIGN/METHODOLOGY/APPROACH : We employ a baseline herding model and extend it to examine asymmetric effects across market conditions. The analysis incorporates time-varying herding measures and examines the impact of both transitional and physical climate risks on herding probability using regression techniques. FINDINGS : The baseline model reveals significant herding behaviour in CE ETFs. The extended model indicates that herding is present in both down and up markets, with a stronger effect in down markets, suggesting asymmetry. Herding is also found to be time-varying. Notably, high levels of transitional climate risk reduce the probability of herding in CE ETFs, whereas physical climate risk does not exert any significant impact on herding probability. RESEARCH LIMITATIONS/IMPLICATIONS : The study focuses specifically on US CE ETFs over a defined period, which may limit generalizability to other markets or asset classes. The findings provide insights into the behavioural dynamics of sustainable investment markets during periods of varying climate risk. PRACTICAL IMPLICATIONS : The results suggest that high levels of transitional climate risk encourage market efficiency in CE ETFs and promote climate hedging behaviour by investors. This has important implications for portfolio managers and policymakers in understanding market dynamics in sustainable finance. ORIGINALITY/VALUE : This study provides novel empirical evidence on the relationship between climate risks and herding behaviour in CE ETFs, contributing to the growing literature on behavioural finance in sustainable investment markets.