Q&A: Zhiyong Duan, Executive Director, Quantitative Research, J.P. Morgan
Describe your career path.
I joined the derivatives research group at J.P. Morgan in 2002 after graduate school. Initially, I worked on structured credit products' pricing and then in 2004, as a joint venture, our subgroup merged with a risk group and our focus shifted to risk. In 2005, I was promoted to vice president and the group was combined with derivatives research and became the quantitative research group. In 2007, I started to manage a small team, and this year I was promoted to executive director.
What is a typical day like for you?
My day runs from about 9 a.m. to 6 p.m. Other than conference calls and meetings, my schedule is flexible and most of my time is spent on various research projects. A typical day would depend on where we are in a particular project. Our group serves internal clients, so at the beginning of a project, I often interact closely with these clients for information gathering which helps expand my knowledge base. As we get further into a project, I become more involved with modeling and implementation. Although there are still some communications with clients to keep them informed, most of the time my team works independently, much in the way a school research project operates, except the deadlines are tighter and we may need to work on multiple projects simultaneously. Once the project nears completion, we'll interact closely with our clients again to deliver the results and help them understand the numbers.
How has your work in quantitative research changed?
Within the quantitative research group, there are a range of quantitative roles. When I first joined J.P. Morgan, my job was to support structured credit trading, mainly on price development. The emphasis was on a consistent price relative to other products. The models were built to be able to calibrate to the relevant market observables, and then used to price the product appropriately. After moving to the risk side, we began providing quantitative support for risk management by building models and systems that help us better quantify and understand the tail risk. Regulatory capital and the internal economic capital calculations are some examples. My role became much more about building simulation models based on historical data to account for market dynamics and required broader thinking. Recently, I worked on a project for our retail business where we developed a model for housing price index and unemployment rate so we could simulate them forward and then use the scenarios to evaluate the portfolio's tail risk.
Any advice for undergraduate students wanting to pursue a career in quantitative research?
I would encourage both undergraduate and graduate to get a flavor of quantitative research by reading professor Steven Shreve's lecture note "Stochastic Calculus and Finance" (available online), which starts with a simple discrete time model and contains detailed calculations, so that you can identify areas to improve. Some programming training is also helpful for future model implementation.
What are the most important skills for a career in quantitative research?
If you're interested in problem solving and model building, then quantitative research is right for you. When we interview candidates, we look for mathematical skills and problem solving ability. These should be part of your training in graduate school throughout your studies and thesis research. If you have these skills, be sure to show them on your resume and emphasize the role that quantitative work played in your research. However, don't exaggerate your skills. For example, if you don't know much about derivatives pricing, don't represent yourself as an expert. It's important that people interviewing you have the right expectations based on your abilities. Be sure to highlight any recognition you received for your work. All of these things will help you distinguish yourself from other candidates. Once you start working, the most important thing is to earn the trust of your manager and colleagues. You must demonstrate that you have enough quantitative skills to handle the job so that your team trusts you and the results you provide. You own your projects and you need to be self-directed. You are the one who is most familiar with your projects, so you become the expert and are responsible for finding ways to solve problems.