Chair of Financial Economics and Risk Management

Since 2014, Prof. Dr. Maxim Ulrich heads the KIT Chair of Financial Economics and Risk Mangement. Prior to 2014, Prof. Dr. Maxim Ulrich was Tenure-Track Assistant Professor at the Graduate School of Business of Columbia University in New York. During this time, he taught numerous investment and asset pricing related courses at the MBA, Executive MBA, PhD and Master level. Prof. Ulrich has presented his research work on finance conferences such as the AFA, WFA, EFA, EEA and NBER Asset Pricing Meetings and published his work in the Journal of Monetary Economics and the Review of Derivatives Research.

The Chair of Financial Economics and Risk Management analyzes how economic risks affect financial markets. The Chair hosts two research groups.

The C-RAM (“Computational Risk and Asset Management”) research group leverages financial economic thinking with data science, machine learning and high-performance computing aspects to extract risk and asset management related information from financial, economic and alternative data. In recent work, we have shown how to use options- and survey data to extract a model-free term structure of dividend risk premiums. In other work we have used textual analysis to analyze the impact of ECB speeches onto different asset classes.

The AI-Finance (“Artificial Intelligence for Financial Markets”) research group focuses on developing artificial intelligence for finance and business data. Traditional finance data is characterized by a low signal to noise ratio. Machine Learning and AI concepts from computer science are developed for high signal to noise data. The AI-Finance Group analyzes how to improve such concepts to make them applicable for finance and business data. In recent work we have been analyzing how to set-up mixture-density networks with neural networks to provide superior forecasts of equity return densities.

Both research groups benefit from a Big Data research infrastructure that hosts high-frequency option, stock and bond market data for international markets.

Research insights from both research groups feed in real-time into our teaching efforts. The C-RAM group focuses in particular on the BSc Module on Financial Data Science. The AI-Finance group focuses primarily on the MSc Module on Advanced Financial Machine Learning