I am from Cameroon and completed my high school degree there. I then came to Paris, where I did mathematics and economics at the University of Paris-1 Pantheon-Sorbonne. After my master degree, I decided to go on to an engineering school, so I graduated in telecommunications and started working as a business analyst at a bank in Paris. After gaining some work experience, I went back to school to pursue a Ph.D. in finance, and at the end of my Ph.D., I began to consider the CQF because I had the feeling that I had learned a lot about the theoretical aspects. Still, I wanted to have more practical experience in quantitative finance. I decided to enroll, and it has worked out very well, as the CQF gave me greater understanding and confidence. I already had strong technical and theoretical knowledge, and the CQF gave me the tools to leverage those skills practically.
I already had strong technical and theoretical knowledge, and the CQF gave me the tools to leverage those skills practically.
I enjoyed all of the lectures, especially the one on the Black Scholes model; when you truly understand that, it's like a light goes on. Then we moved on to interest rate and credit risk modeling – there was just a continuous flow of learning and analysis of these models.
After the CQF, I joined a company in France in asset management on research, developing a top-down asset management process based on views models (Black-Litterman, Copula Opinion Pooling), and doing quantitative support for the asset managers for about three years. Then I joined the World Bank treasury, where I was on the quant team in charge of strategic asset allocation, helping central banks to develop their framework. I did that for three years, and then I moved to the risk management team because I wanted to understand the World Bank's liquid portfolio better. That team is in charge of risk, focusing on credit, market, and counterparty risks. I stayed there for three years, still supporting central banks on risk budgeting and credit risk frameworks, leading the counterparty risk for the World Bank's funding portfolio, and developing relative strategies on the interest curve for the asset management team. Now, I have transitioned to something completely different, still within the World Bank Treasury. As a Banker, I'm advising developing countries on leveraging the World Bank's financings; part of this involves understanding their debt management strategy to provide risk management solutions for interest rate and currency risks in their lending portfolio. The work I completed during the CQF, especially on interest rate modeling and credit risk, has been valuable in these roles and overall. In my current capacity, I don't do much quant work, but thanks to the CQF, I have deep quant knowledge that helps in supporting World Bank's country clients in their debt management strategy and concept like hedging. This is an excellent example of how training in quant finance can lead you to work on global economics.
The work I completed during the CQF, especially on interest rate modeling and credit risk, has been valuable in these roles and overall.
I would encourage people considering the program to focus a good part of their attention on programming. I suspect it's something that the current CQF students do spend a lot of time on because you cannot be a quant without having good coding skills. The CQF itself has dedicated modules on this, and there are also special lectures in the CQF Lifelong Learning offerings. I learned Python by looking at those videos; there is a lot of great material there. Since the CQF program is so intensive and passes so quickly, it can be hard to master all of the skills you are interested in. However, you can always return to these subjects later using the Lifelong Learning library and devote yourself to the areas of greatest interest to you.