Timing Factor Risk and Factor Returns with AI
Project Description
In the Innosuisse innovation project "Timing Factor Risk and Factor Returns with AI" (no. 123.049 IP-SBM), the University of Liechtenstein and LLB Asset Management jointly develop data-driven methods for modern, sustainable portfolio management. The project is funded by the Principality of Liechtenstein through the Office of Economic Affairs (AVW) and Innosuisse. At its heart is the question of how reliably factor premia, risk drivers, and market regimes can be predicted over time - and how that knowledge can be turned into better investment decisions. The project connects current asset-pricing research with the practice of portfolio management: it studies classical, statistical, and ESG-related factors, identifies risks for which investors are not compensated, and examines how such risks can be deliberately reduced. Forecasting and timing approaches - from transparent rules to modern machine-learning methods - are tested under realistic conditions and translated into concrete, explainable portfolio decisions. The result is a reproducible, practice-ready toolkit for dynamic, factor-based, ESG-integrated investing - academically grounded and immediately applicable.
