ESG investment is a strategy that considers environmental, social, and governance factors when making financial decisions. This study examines how seasonal anomalies, including the day of the week and the month of the year, influence the return and volatility of ESG.
The linear and non-linear GARCH models are used to analyse the daily data from April 1, 2011, to December 31, 2024, to investigate the existence of seasonal anomalies in ESG stocks.
The results from the linear and non-linear GARCH models reveal the existence of the DOW and MOY effects. Additionally, the study underscores a leverage effect, suggesting that positive news elevates volatility less than negative news.
The research emphasises significant implications for investors, portfolio managers, and policymakers regarding ESG investments. The DOW and MOY effects suggest that participants can enhance their strategies by utilising seasonal trends, especially the positive returns observed on Tuesdays and Fridays. The leverage effect highlights the necessity of risk management during market downturns, and acknowledging the July effect alongside the negative volatility experienced in June and October enables effective portfolio adjustments.
This study is groundbreaking. It is the first to examine the impact of seasonal anomalies on the ESG index's returns and volatility. By exploring the ESG index in relation to seasonal anomalies, this research fills a notable gap in the literature, employing both linear and nonlinear GARCH models. The objective is to analyse how these seasonal anomalies influence the ESG index.
