Playing with Programming on the CQF
At the beginning of my career, I worked in London developing software for banks and insurance companies. I then moved into a role at IBM, focusing on capital markets clients. I had graduated from a university in Bologna, Italy with a master’s degree in theoretical physics, where I studied quantum mechanics. I had very good training in technology and math and, in those days, we were doing lots of Java and C++ and working with enterprise architectures, but no one told me about quantitative finance when I was taking physics. This was something I discovered later on and then I felt that I was missing the piece that connects the math of quantitative finance, the technology, and the capital markets together. My job was interesting, but I wanted to learn more about how things were applied on the trading floors and to the structures of credit and risk that we were advising on.
So, I started searching for a specialized type of master’s degree that could give me a better understanding of the mathematical underpinnings and the applied angles that mattered in this environment. I have always been interested in doing a PhD too, but it's difficult to switch fields and you have to consider the amount of time it takes to complete such a program. I was looking for something that I could do while still maintaining my career at IBM and I clearly wanted to focus on financial products. I was particularly interested in commodity trading, which I found intriguing because of its complexity. Another area for me was the energy trading space and the risk involved with trading around that, which was part of the work with the capital markets team at IBM. Further education would help drive deeper knowledge of these subjects for my work with clients and I would be able to talk to quants and traders at a deeper level as well.
As it was, I joined the CQF in 2008 and felt that this was the perfect solution. I enjoyed the lectures very much and found that there was great clarity in the teaching. The program was extremely practical, and also encouraged you to play with things like Monte Carlo and Excel spreadsheets. At the time, I had done plenty of work with real programming languages, but I actually had not spent much time with Excel and VBA; finding out what you could do with them was a big discovery for me. Of course, now we have Python to work with too; I have followed the changes in the CQF curriculum and know that it is staying up with the latest developments in data science and machine learning, which are shaping the industry today. For the CQF delegates, this is definitely important and helps develop the skills of the data scientist, a role which is very hot in the market these days.
For people who are considering the CQF now, I would say it is challenging and very rewarding. For me, it was a journey of discovery that more than met my expectations; it was a productive time and I still recall the joy of learning in those classes. The CQF requires a lot of discipline and if you have an intense job, it will push you quite hard. But if you have a passion for learning, and especially for the math behind the models in finance, you will truly benefit from the experience.
To find out how you could transform your career with the CQF program, please download a brochure or join the next online information session to hear more and ask questions to the CQF Program Director.