Lessons learned from being the ‘dumbest’ person in the room – Quant Simplified
This is perhaps an outlier to all my other posts in the QuantSimplified series — one that does not have anything to do with quantitative methods or theory, but a personal reflection (in fact I was contemplating whether to include this or not). A lot had happened in my life at the point of writing: not only have I officially graduated from my Master’s degree in quantitative finance, I have also hit my 1st year milestone as a quantitative analyst. I felt motivated to write about some reflections I had over the past one year whilst on the job. This will be a relatively short article (I promised!), and the following is some key lessons.
The dumbest person in the room
The title of this article might have raised some eyebrows, especially since it kinda went against conventional impressions. Financial engineers were recognised as the “rocket scientists” of Wall Street, and many may regard quants as a group of people who are so well-educated and have attained too high an academic qualification to be called the dumbest person in the room.
This title was inspired by a fellow quant who constantly reminded me that humility is the essence of being a quant — a quant/ scientist is someone who consciously recognises that there are always more brilliant things/ people out there, and knowledge is a constant pursuit. No one is ever too smart, and a real quant always recognises that one can always be better, but never the best. This doctrine is perhaps one of my biggest takeaways in my first year being a quantitative analyst, one that keeps me grounded and constantly stay curious and work hard.
Equally important, in practice there are indeed situations that a quantitative analyst may be the dumbest person in the room. When solving certain problems, a quantitative analyst often starts from zero ground — one may be totally new to the domain of the problem and may not have the required contextual knowledge. In such cases, a quantitative analyst does begin as the dumbest person in the room filled with experts that have the required subject matter expertise.
In such situations, it is essential for quantitative analysts to ask the right questions, and here comes the second learning.
Dumb, but not dumb
When one thinks of a quant, one may imagine a person sitting in front of a computer the whole day facing lines of codes in fancy colors. Well, that is probably accurate, but that is not all to the work of quants. Quants cannot remain quiet and be isolated in a corner. Like in all other roles, communication is key.
Quants are problem solvers; and with all problem solving it requires active listening and prompting right questions. There are many situations in which the problem may be unprecedented, and each stakeholder may hold some key information that could shed light on the potential solutions. Quants being the owners of tools that could qualify as solutions would need to communicate and prompt the right questions in pursuit of that solution. This requires superior problem-framing skills that give one clarity to the essence of the problem, coupled with strong communication in order to prompt the key information leading to the solution.
Apart from communicating to facilitate problem solving, quants need to be the sales person for their solutions. Many solutions are made of advanced mathematical models that not everyone is trained to understand intuitively. In order to keep things moving, quants need to be able to simplify the explanation such that key stakeholders are able to follow the essence of the solutions — techniques like analogies are effective. It is important also to know what is essentially critical and what can, or must not, be reduced. As a quote famously attributed to Albert Einstein reads, “Everything should be made as simple as possible, but no simpler”.
Limitations are more important than solutions
As a matter of fact, in most situations a quant faces there is no perfect solutions. Mathematics, being a man-made tool, ultimately attempts to describe a much more complex and unpredictable world that we live in. Many models and solutions are but an approximation given the best information one has at any point in time. It is important for one to acknowledge that one is wrong; the key is to not be too wrong.
Henceforth, understanding the limitation to a solution is more important than the solution itself. In the same spirit, a more complicated or over-engineered solution or structure may not necessarily be the best, as the more complicated a solution is the more limitations one can expect. Important concepts like principles of parsimony and Pareto’s principles that one learns from econometrics and economics really come into play.
Being owners of the solutions, it is a quant’s responsibilities to always bear in mind and communicate the limitations of a solution, and to stop when progress results in more limitations than the benefits the solution may yield.
I hope that in this simple reflection post one may find some points that resonate well and provide some affirmations and suggestions on the challenges facing quantitative analyst regardless of background or industry. The key message of this post is to highlight the following:
- Despite being a numerical work, never forget to work on communication skills
- For aspiring quants — do not only focus on the fanciness of models/ solutions, but be aware and have one’s eyes peeled on the limitations of each model
- Most importantly, be humble and stay curious
For more content on how to be a successful quant, please check out Igor Tulchinsky’s Finding Alpha, Chapter 32 on “The Seven Habits of Highly Successful Quants”.
Thanks for reading, and looking forward to feedback and opinions! :)
