This project develops data-driven trading signals by extracting and quantifying narratives from social media. Using advanced NLP and AI methods, we study how online sentiment, attention, and framing translate into market movements and investment behavior.

Hate Radar is an AI-based platform for the real-time detection and monitoring of online hate speech. The project combines natural language processing, machine learning, and large-scale data collection to identify harmful content, track emerging narratives, and support evidence-based policy and intervention design.

“Talking to Machines” explores how interactions with artificial intelligence affect human financial decisions. The project brings together an international team of academic and industry researchers to design AI-driven experiments, with findings published in leading social science journals and used to inform public policy and large-scale behavioral interventions.

This project develops open-source (R-based) tools for currency trading and hedging strategies tailored to small and medium enterprises and pension funds. We focus on univariate and multivariate approaches, drawdown management, and tail-risk protection to improve resilience against exchange-rate volatility.