05.07.2024From PhD at University of Zurich to tenure track career in the USA

Dr. Marlon Azinovic
UZH, Department of Finance: PhD in Banking and Finance (2016 to 2021)
UZH, Department of Economics: Postdoctoral Researcher (2021 to 2022)
Visiting Postdoc at the University of Pennsylvania, Department of Economics (2022 to 2024)
Starting in 2024: Assistant Professor (Tenure-Track), University of North Carolina at Chapel Hill, USA

Read an excerpt of the interview below or download the full interview (PDF, 239 KB)

Q: Dr. Azinovic, what motivated you to pursue a PhD in Banking and Finance at the University of Zurich? 

A: Coming from Physics, I thought it was amazing that I could first take classes before delving into research in a new field. When I saw the research done at UZH, by Felix Kübler and his PhD students and postdocs at that time, I knew that it would be very exciting for me to work on computational economics. 

Q: What made you switch from Physics at ETH to the world of finance?

A: My girlfriend's studies in Banking and Finance at UZH sparked my interest. Additionally, I believe economics and finance are crucial for understanding and addressing global issues like inequality and climate change. The interdisciplinary nature of the field also appealed to me.

Q: Would you like to share some highlights or memorable experiences from your time as a PhD student at the University of Zurich/Department of Finance?

A: The first year was incredibly fun, and I made lifelong friends. A significant highlight was when Felix Kübler agreed to be my advisor. The most magical moment was when Luca, Simon, and I first started working on deep learning-based solution methods to compute equilibria in economic models and we quickly managed to so solve models, which were beyond what people could solve at that time.

Q: Tell us about your doctoral research (title), highlights, and contributions you made to your field during your PhD studies?

A: My thesis, Essays in Computational Macro Finance, comprised three chapters. In the first, we used deep learning to compute equilibria. Computing an equilibrium in our setting means finding functions such that they fulfill a set of functional equations. The second chapter involved working on a model with various risks and trading technologies across households. The third chapter focused on the effect of uncertainty shocks on different age groups.

Q: How did your PhD experience at the University of Zurich's Department of Finance (UZH DF) prepare you for your current job placement?

A: My PhD experience was crucial. I learned about economic models and research, and I was surrounded by brilliant and supportive people who helped me improve my research and prepare for the job market.

Q: How would you describe your research evolution, from your summer research project to your job market paper?

A: In my summer research paper, I used policy time iteration, which is closely related to the deep learning-based method that later became my first publication in economics. This project was the perfect starting point for delving into numerical methods for financial economics.

Q: What motivated you to pursue an academic career?

A: When I started my PhD, I was not even aware that aiming for an academic career was an option. I think economics is an amazing subject. We use tools from computer science, statistics, linear algebra and many more fields to find substantiated scientific answers to the most pressing questions. Being able to do this as a job is an absolute privilege, I could not envision a better job.

Q: How did the puzzle pieces from UZH DF to Econ to Penn to University of North Caroline at Chapel Hill (UNC) fit together?

A: Each step was necessary for my development as an economist. I was fortunate to be surrounded by supportive and knowledgeable economists who helped improve my research and understanding of the field.

Q: What are your current research interests, and how do they align with the ongoing projects at UNC?

A: My research focuses on household heterogeneity and aggregate fluctuations. UNC Chapel Hill has researchers working on related topics, and I am excited to collaborate with them and explore new areas like deep learning and quantum computing.

Q: What advice would you give to current PhD students in Finance aiming for academic positions?

A: Don't be scared if you can’t solve your model. Simplify if you can and don’t be shy to try ambitious projects or to talk to senior people for advice, since they can give you amazing advice. Don’t be scared if your paper is lacking. Every paper has weaknesses, and you are a better economist for knowing the weaknesses of yours. If you know how to address them in the future, even better. Also, remember to smile and look into the camera during interviews.

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