Career

Professor Maxim Ulrich

My passion for financial markets began in my early school years. Before finishing high school, I experienced the Asian- and Russian- financial market crisis, and the ups and downs of Neuer Markt. I have learned early on what it feels like to lose 80% of invested capital. These painful experiences and somewhat irrational price movements sparked a deep desire to truly understand price fluctuations and the underlying causes of asset return volatility. 

By the time I started university in 1999, I was eager to find a program that emphasized quantitative financial economics, but such offerings were (to my knowledge) non-existent in Germany. Years later, my academic journey led me to a pioneering DFG-funded PhD program in Financial Economics and Monetary Policy, where I specialized in financial engineering, theoretical macroeconomics, and numerical mathematics. Still to this day, I share great memories of these five years. 

Anecdotally, an experience late one winter night, describes my PhD time pretty accurately. While programming an estimation algorithm in C++ for a self-developed macro-finance asset pricing model, I chose to ignore the arrival of first responders on university campus. Absorbed in my research, I was unaware of an ongoing fire evacuation at around midnight and was eventually discovered by a firefighter as I made myself noticeable hours later. At around five in the morning it was safe to leave the building and the police advised me to go home to get some sleep. This anecdote illustrates my deep commitment to research, a feature that has shaped my academic career.

In 2008, I achieved what was deemed impossible: I was offered a position as a Tenure-Track Assistant Professor in Finance at Columbia University’s Graduate School of Business. This once-in-a-lifetime opportunity in the heart of New York City was particularly meaningful, as five years earlier, during my PhD program's assessment center, I was told that this was an entirely unrealistic goal. During my five years at Columbia Business School, I developed my expertise in teaching and research, transitioning from a PhD researcher into a faculty member at one of the world's top business schools. My experience teaching MBAs, Executive MBAs, Master's, and PhD students profoundly influenced my pedagogical approach to teaching quantitative finance concepts to a diverse audience.

My move to KIT was a homecoming in many ways. I consider KIT the birthplace of quantitative financial economics in Germany. Many of Germany’s quantitative finance professors, as well as some in the U.S., studied at KIT. Moreover, two of my PhD friends went on to work at Germany’s first and most renowned quantitative asset management firm, co-founded by a group of KIT finance PhD alumni.

At KIT, I uphold the Humboldt tradition of research-driven teaching, with a unique focus on quantitative and IT-oriented financial market content. I aim to equip students with the necessary skills, tools, and intuition to engage in frontier research and quant hedge fund work. For instance, we recently published a research article in the prestigious Review of Derivatives Research journal on a topic that required us to validate option pricing models using an unprecedented half a billion option prices. One of the two co-authors was a KIT Master's student who contributed during his class-time research at KIT. I am very excited to bring these research-based teaching concepts to KIT’s Bachelor program with my newly designed course on Financial Data Science.

To improve as a financial market business school scholar, I have gained additional practical experience through the foundation of two all-equity-financed fintech startups in the area of option analytics and financial literacy. I have also accumulated further practical experience through significant investments in stocks, futures, options, commodities, real estate, and crypto. Additionally, I have collaborated with Eurex’s and the ECB’s risk analytics teams to educate professionals and help develop cutting-edge big data solutions to pressing practical problems faced by large financial market players. More recently, I have been contacted by international hedge funds to assist with various modeling questions in the area of financial machine learning. I have pursued these projects not for financial gain but for the intellectual challenge and the opportunity to enrich my teaching and research at KIT.

At KIT, I serve as Professor of Risk Management and Financial Economics. I am also responsible for the Financial Engineering program track for KIT’s Hector Business School MBA program. More recently, I have initiated a PhD program for students interested in finance and machine learning. Currently, we have a vibrant group of international PhD students from China, Vietnam, Iran, Singapore and Germany. It is a great privilege and joy to contribute to KIT’s excellent teaching offerings at the Bachelor’s, Master’s, Executive Master’s, and PhD levels to improve the young generation’s understanding of Financial Data Science and Financial Machine Learning. I am deeply grateful to the Chair’s Förderverein for additional research funding and Deutsche Börse for their generous support with high quality market data. A special thanks to Landesbank Baden-Württemberg (LBBW) for donating PhD scholarships for the mentioned PhD program on Machine Learning and Data Science for Financial Markets.