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WASTE indexes published research — it does not host or republish full papers. Each entry is a metadata record compiled from open scholarly databases; the abstract is shown in full only where the paper is openly licensed, otherwise a short excerpt under fair use. Classifications are automated and approximate.

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Predictive Power of ESG Factors for DAX ESG 50 Index Forecasting Using Multivariate LSTM

Manuel Rosinus, Jan Lansky · 2025 · International Journal of Financial Studies

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

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