Wavelet analysis and the financial performance of ESG strategies

Michaela M. Kiermeier

Chapter 13 in Handbook of ESG Investing, 2026, pp 315-360 from Edward Elgar Publishing

Abstract: This study examines the relationship between Environmental, Social, and Governance (ESG) information and financial performance in Europe using wavelet-based multiresolution analysis. By combining an event study approach with the Maximal Overlap Discrete Wavelet Transform (MODWT), the analysis isolates reactions to ESG-related signals and captures the temporal structure of abnormal returns. ESG signals are derived from price movements of STOXX Global ESG Leaders indices, and portfolios are constructed based on top and bottom LSEG Refinitiv ESG ratings. The results indicate that ESG effects are not short-lived but develop over medium– to long-term horizons. Environmental and social signals are gradually incorporated into asset prices under stable market conditions, while governance-related effects are more volatile and pronounced in poorly rated firms. The study contributes a novel methodological perspective by linking signal-driven performance responses with the time-frequency characteristics of returns, offering insights into the persistence of ESG information and the timing relevance of its market impact.

Keywords: Event study; Performance; ESG ratings; European stocks; Wavelet analysis (search for similar items in EconPapers)
Date: 2026
ISBN: 9781035322770
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