Chair description
Can we predict stock returns? How can we best model the time-varying volatility of asset returns? How do stock returns comove during periods of economic distress? What factors drive the cross-sectional variation in asset returns? These are typical questions in financial economics. Financial econometrics develops the models and methodological tools needed to answer them.
While data-driven since its inception, financial econometrics is now increasingly shaped by the chal-lenges and opportunities of big data. The growing availability of large and previously inaccessible datasets—such as high-frequency quotes and trade data, order book data, and financial text—has opened the door to a wide range of novel research areas. At the same time, machine learning meth-ods offer new opportunities for modeling, prediction, and pattern recognition in financial data.
Research
Projects
Launched in 2020, Monitoring Consumption Switzerland is a project that uses payment data to shed light on consumer spending in Switzerland. In 2025, we introduced the Consumer Spending Index for Switzerland.
Matthias Fengler has been granted a number of projects supported by the Swiss National Foundation:
Professor of Econometrics
Personal Assistant
Assistant to Prof. Fengler