How can we best model time-varying volatility patterns of stock returns? How do stock returns comove in times of economic distress? What factors drive returns and volatility of a financial asset cross-sectionally? These are typical questions of interest in financial economics. Financial econometrics develops the models and methodological tools to answer them.
While data driven from its early days, financial econometrics is nowadays heavily influenced by the mounting challenges of big data. The growing access to huge and hitherto unavailable data sets, such as high-frequency quotes and trade data, order book data, or financial text data, has opened a gateway to a fascinating range of new research areas.
Monitoring Consumption Switzerland is a project that uses payment data to shed light on consumer spending in Switzerland. Particular focus is the Covid19 crisis and its economic impact. The data are updated weekly and thus yield insights into the development of the crisis and the economic recovery at “high frequency”. At HSG, the project is powered by Martin Brown (SoF) and Matthias Fengler, together with Robert Rohrkemper (Senior Data Scientist, Worldline) and Rafael Lalive (University of Lausanne).
Current teaching activities range from introductory time series and data analytics classes at the Bachelor’s level to Master’s level classes in time series analysis, multivariate analysis, financial econometrics, and asset pricing.