Meet the June 2022 First in Class Award Winner

My educational background is somewhat unusual for this career path. I have not graduated in physics, engineering, or even economics. Instead, I have bachelors and master’s degrees in sociology from Vienna University. Therefore, my view on the financial markets is strongly influenced by a social science perspective. I have always been curious about how people form and act on their beliefs and views in everyday life. In the context of financial markets, this includes how and why people trade their assets, including their views about the future, the economy, and so forth. These are interesting questions in fields like sociology and philosophy, where you think deeply about rationality and decision-making processes. It also leads to behavioral finance and Game Theory, of course. I became interested in quantitative modeling because you are only able to mitigate behavioral traps and trade successfully when you have an economically sound quantitative model in the background for your financial decision-making. 

Along the way, I acquired additional education in finance. However, in order to move further into quant finance, I needed to develop more domain-specific knowledge. Through my work in sociology, I already had a specialization in quantitative methods, with a lot of statistics. I’d also had exposure to machine learning, including deep learning. So, I thought about all of my educational options, but I was concerned that if I took an additional master’s degree in finance or data science, it might not have the direct application to financial markets that I was looking for. The CQF, on the other hand, comes with exactly the combination of the theoretical foundations and the practical knowledge needed in applications to real-world use cases. 

As I started the primers before the CQF, I found that the Math was difficult at first, but I liked it very much and my curiosity kept me going. I also felt a very good connection with the program philosophy. The CQF is very strong in applied mathematics and I learned a lot of it in connection with various investment problems. 

Over the course of the program, my favorite modules were the ones covering portfolio management and machine learning because they were directly applicable to my current role. I also enjoyed the module on options theory and advanced volatility modeling because it provides an in-depth source of analytical and numerical solutions to option pricing that you can use in practice straight away. With the more practical view on concepts like complete markets and arbitrage, I also gained a better understanding of the dynamics within financial markets, while the machine learning lectures have guided me to approach them from the perspective of a multi-agent problem. Receiving the CQF First-In-Class award is a significant milestone in my career, reflecting my dedication to self-improvement and professional advancement. I am applying what I have learned in the CQF now and am confident that it will have a lasting relevance as my career evolves.

For people enrolled on the CQF, I would recommend that you make the effort to attend the online lectures live if possible. I did the program alongside my full-time employment. Naturally, it’s quite a challenging schedule, but you can ask questions and since all of the faculty members are experts in their fields, they provide great answers.  During the program, I spent most of my weekends reading the books and doing all of the exercises as well. I think that level of commitment is necessary to benefit from the full CQF experience. The effort is worth it in the end because the CQF will definitely help you find new directions for your career in quant finance.