
ESG Research
ESG Research
Systematic ESG Integration for Sustainable Investing
ESG considerations represent one of the four dimensions of our ultimate investment objectives, alongside alpha generation, risk management, and liquidity. Regarding the investment process, our research suggests that ESG brings a sustainable dimension to stock selection that supports socially responsible investing while helping to reduce long-term investment risks and optimise fund returns.
We integrate all ESG considerations into our systematic approach to stock selection. By leveraging our Deep Learning platform and the combination of structured and unstructured data, we seek to identify opportunities for sustainable alpha generation within our dynamic equity universe.

ESG Research
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Through our ESG research, we aim to deepen understanding of how environmental, social, and governance factors shape long-term value creation.
A Leading Approach to ESG Integration
Abstract
ESG data growth offers new investment dimensions but presents challenges. We introduce ESG shortcomings and value-added inputs for stock selection.
Real-Time Climate Controversy Detection
Abstract
ClimateControversyBERT detects corporate climate controversies in real time, showing significant negative market impacts for committed firms.
AI for ESG Integration: Training Machines to Predict Sustainable Alpha
Abstract
Our deep learning framework combines ESG and traditional factors, modeling their interactions for optimal stock selection and portfolio construction.
Beyond ESG Rating: The Real Impact of Good Governance
Abstract
SFDR regulation improves transparency in sustainable investment and prevents greenwashing. We analyze its impact on return and style biases.
A Deep Learning Framework for Climate Responsible Investment
Abstract
We integrate structured and unstructured climate data into quantitative investing, demonstrating low-carbon portfolios with attractive returns.