NLP and Sentiment Analysis in Investment Management

Together with SFI Prof. Norman Schürhoff (University of Lausanne) and Dr. Matthias Uhl (UBS Asset Management), we will approach a competitive edge using machine learning/artificial intelligence (ML/AI) and natural language processing (NLP) techniques that investment professionals are seeking to gain.

The past decade has witnessed an explosion in the amount of data produced by companies and individuals, newspapers such as the Financial Times and The Wall Street Journal, and web presences such as Google, Wikipedia, and X. The recent widespread availability of text-based data has coincided with major advances in the fields of ML/AI and especially in NLP.

The analysis of sentiment in natural language holds the promise of addressing a range of challenges faced by the banking and financial sectors. Can investment managers use sentiment analytics to "look through" noise in financial markets? Can they identify longer-term cycles in news sentiment data and formulate a model that pinpoints longer-term trends in the data to address the market-timing challenges faced by asset managers?

• Further information & Resistration

Swiss Finance Institute

in collaboration with the Fondation Genève Place Financière