The Performance of ESG ETFs vis-à-vis non-ESG ETFs in Hong Kong

Gerasimos G. Rompotis
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Gerasimos G. Rompotis: Department of Economics, National and Kapodistrian University of Athens, Athens, Greece

Climate Economics and Finance, 2024, vol. 2, issue 1, 12-23

Abstract: The performance of ETFs in Hong Kong that apply environmental, social and governance (ESG) criteria to make their investment decisions is examined in this study. The performance of these ETFs is assessed against the performance of competitive non-ESG ETFs. The study period spans from 1/12/2022 to 29/2/2024. From a methodological perspective, raw returns, tracking errors and risk-adjusted returns are computed. Raw returns are computed in percentage terms with daily close trade prices. Tracking error is calculated as the difference in daily returns between ETFs and Hang Seng Index, which is used as a proxy for the entire stock market of Hong Kong. Risk-adjusted returns include Sharpe, Treyor, Modigliani & Modigliani, and Information Ratios. A simple regression model is applied too, via which the daily excess return of each ETF, that is the return above the risk-free rate, is regressed on the corresponding return of the market index. The empirical results indicate that the ESG ETFs clearly underperform their non-ESG peers, also being a little riskier and more expensive than them. In particular, the average daily return of ESG ETFs is equal to -0.058%, while the respective return of non-ESG ETFs is slightly better at -0.033%. At the cumulative level, the average return of ESG ETFs is equal to -19.22%, while the respective return of the non-ESG ETFs amounts to -12.41%. When it comes to risk, the ESG group presents an average measure of 1.572%, whereas the non-ESG group has an average risk of 1.490%. In regard to expenses, the average management fee of the ESG ETFs is equal to 0.18%, while the average management fee of the non-ESG peers is 0.09%.

Keywords: ETFs; Sustainable Investing; Performance; Risk-Adjusted Return; Hong Kong (search for similar items in EconPapers)
Date: 2024
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