Quantitative analysts, or ‘quants’ are in demand. But it is not just about numbers
On the splash page of SMU’s Quantitative Finance (QF) discipline is the following paragraph:
“In the fast-paced world of finance, technological advances and regulatory requirements drive the banking industry to the point where mathematical and statistical modeling had already become a necessity. A talented person with strong quantitative skills is highly sought after by hedge funds and banks.”
“For QF, programming is one of the fundamental skills you need to learn,” explains Dr Shirley Huang, Area Coordinator of QF and Associate Professor of QF (Education). “You will be taught Excel VBA and Python programming. If you think you are weak in programming before taking QF courses, you will definitely not be weak in programming after you have taken QF courses.”
QF in the real world
Prof. Huang made those remarks at the recent QF July Forum 2020 webinar where questions were asked about the programming skills required to be quantitative analysts, or quants. There were also queries about the relationship between quants and data analytics/coding skills.
“Quants make use of data analytics and coding skills to solve practical financial problems in the market,” explains Dr. Tee Chyng Wen, MQF Academic Director and Associate Professor of QF (Practice). “Both data analytics and programming languages are vast subjects by themselves.
“Our focus as quants is not so much about building a database from scratch, or assessing the quality of a given programming language’s compiler or interpreter. We are problem solvers – we want to use the best tools to do our job.”
That assessment is supported by SMU alumni Chuan Dewei, who graduated in 2017 after majoring in QF. Pointing to a typical job ad for a quant, “problem-solving skills and the ability to deploy those skills during time-sensitive situations” ranked high among the requirements.
Chuan also pointed out the kinds of companies and jobs some of his fellow QF graduates have found themselves in: Banks (Sales, trading, risk, research etc.); Trading funds (DRW, Flow Traders, Dymon etc.); and as Developers (Lazada, Stashaway etc.)
“It could be the intellectual challenge or the remuneration, or even pure interest, but these are some jobs that many QF graduates gravitate towards,” explains Chuan, who is current a FX Money Markets Trader at UBS. “Besides problem-solving, employers will ask for hard skills such as programming in languages such as Python and analysing data sets.
“Lastly, you’ll need communication skills. If you have very good ideas, you need to communicate them to your team and your clients.”
Fellow QF graduate Ray Yeo, who is AVP, Traded Credit Risk Methods at DBS, highlighted a course mate who moved to Hong Kong to work at the city’s tourism board before moving to another industry in Japan. “QF is very versatile, you can apply it many different areas, not just in finance,” he notes.
For Yeo, QF is not just about technical skills but about a mindset to deal with an increasingly complex world.
“QF can’t help you to adapt but QF training can help give you the mindset and mental agility to navigate complexity,” he says. “QF helps in three ways: Structured thinking; Critical thinking; and an Analysis toolbox.
“Structured thinking and critical thinking are somewhat different. Structured thinking is about having a particular sequence or order of what to think about. Critical thinking on the other hand is about considering whether the assumptions you have in any analysis are sound, and how you link different parts of your analysis together.
“Analysis toolbox is the set of mathematical tools that help you quantify any situation that is precise and understandable.”
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Last updated on 31 Aug 2020 .
