Return and Volatility Properties Comparison of High-ESG Rating and Low-ESG Rating Exchange-traded Funds (ETFs)

John Francis T. Diaz, Michael N. Young and Yogi Tri Prasetyo
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John Francis T. Diaz: Asian Institute of Management, Makati, Philippines
Michael N. Young: Mapua Institute of Technology, Manila, Philippines
Yogi Tri Prasetyo: Yuan Ze University, Taoyuan, Taiwan, China

Financial Economics Letters, 2024, vol. 3, issue 2, 55-75

Abstract: This study compares return and volatility performance of exchange-traded funds (ETFs) with high-ESG (Environment, Social, and Governance) rating vs. low-ESG rating. The paper also examines time-series data predictability by identifying their positive dependence and volatility asymmetry properties, and examines the performance of two combinations of short-memory models i.e., autoregressive moving average and exponential generalized autoregressive conditional heteroskedasticity (ARMA-EGARCH); autoregressive moving average and asymmetric power autoregressive conditional heteroskedasticity (ARMA-APARCH) and two long-memory models, autoregressive moving average and fractionally integrated exponential generalized autoregressive conditional heteroskedasticity (ARFIMA-FIGARCH); and autoregressive fractionally-integrated moving average and asymmetric power autoregressive conditional heteroskedasticity (ARFIMA-APARCH). The study found that low-ESG rating ETFs on average have slightly significant higher returns and also lower volatility compared to their high-ESG rating counterparts. Evidence of asymmetric volatility properties are also present on both high-ESG and low-ESG rating ETFs returns. The study also observed that for both high-ESG and low-ESG rating ETFs denote a stationarity, but non-invertible process in their returns. Results can provide fresh understanding in the topic of leverage effects and volatility that can open future research channels to academicians.

Keywords: High-ESG and low-ESG rating ETFs; volatility clustering; asymmetric volatility (search for similar items in EconPapers)
Date: 2024
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