Predictive Power of ESG Factors for DAX ESG 50 Index Forecasting Using Multivariate LSTM
Manuel Rosinus; Jan Lansky · 2025 · International Journal of Financial Studies
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Abstract
As investors increasingly use Environmental, Social, and Governance (ESG) criteria, a key challenge remains: ESG data is typically reported annually, while financial markets move much faster. This study investigates whether incorporating annual ESG scores can improve monthly stock return forecasts for German DAX-listed firms. We employ a multivariate long short-term memory (LSTM) network, a machine learning model ideal for time series data, to test this hypothesis over two periods: an 8-year analysis with a full set of ESG scores and a 16-year analysis with a single disclosure score. The evalu
Abstract by Manuel Rosinus; Jan Lansky, International Journal of Financial Studies (2025) — licensed CC BY 4.0.
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Metadata source: DOAJ · DOI 10.3390/ijfs13030167