Q&A with a Quant: David Feng Xue

July 2021

What was the catalyst behind your move into quantitative finance? 

I think it was curiosity. I graduated with an engineering degree, and only joined the financial industry by some random chance. I had planned to go back to school for an advanced degree during my time as an engineer, but I interviewed for a position at a financial software trading company and was offered a role as a software consultant. I immediately realized it was quite a good match to my personality and skillsets – since I am always willing to explore new things and quite good at picking up different ideas. Most importantly, I love taking up new challenges. 
 

You have had an interesting career trajectory, why did you decide on your latest role in banking?

I am an expert in derivatives trading and products. Before I took up my current role in a local bank, I had spent over a year at a fintech firm - helping them to roll out a first-of-a-kind algorithm for trade compression and risk minimization. Managing a small quant team is a brand-new challenge and I decided to take it as a natural progression of my career.
 

What’s a typical day like for you? 

I run a typical sell-side global market quant team. Every day we need to maintain the Profit & Loss & Risk report from the quant system for all trading desks. We are also involved in internal projects related to product and analysis. Currently we are revamping the legacy system and quant library to the industry standard, and seeking to improve the global market capacity in terms of pricing and product offering. 
 

What in particular is interesting about AI?

This is still a relative new area where the traditional derivative trading business will and must focus on in the next a few years. In fact, for hedge funds trading derivatives, they are using Artificial Intelligence (AI) and Data Mining (DM) techniques widely in their day-to-day business. There are also challenges for sell-side banks to fully adopt this new idea. All in all, we should try to improve the analytics and then spend more time on using AI or DM to come out with trading ideas rather than based on traders’ hunches. 
 

What do you enjoy and dislike most about your work as a quant? 

I always enjoy what I do. The happiest moment is when I have solved a tricky issue, or complete some task where other people can’t. This has gratifyingly happened a lot in my career.

 

What in your opinion are the skillsets that are required to be successful in quantitative finance? 

Stay hungry, stay humble, and most importantly understand your own limit. 
 

You previously earned the Certificate in Quantitative Finance (CQF). Where did the CQF add value in your career path?

CQF is an excellent online-based course. The syllabus is up to date and lecturers are all experienced. It has a final project and paper exam, which completes the learning process in a good way. It really opened a door for me, and showed me that I can be a good quant although I am not from a pure math background. 
 

How important is continuous learning for you to achieve your career goals? 

This is the key to any success in all types of training. 
 

What are your hobbies or interests outside work, and how have they helped you in your work as a quant?

Sports such as jogging, swimming and basketball – as well as catching up with friends are great stress relievers from work. This social interaction provides many opportunities for sharing ideas and thinking outside the box. This has helped me, for example, to resolve some issues in my work in financial engineering. It's very important not to be confined by a quantitative or mathematical domain.
 

Who do you admire in the world of quantitative finance?

Patrick Hagan and Paul Wilmott.