As some of my friends are aware, I resigned from my position at a high-frequency trading (HFT) firm six months ago and am currently in a transitional phase, contemplating my next move. After much introspection, I have decided to pursue a career in quantitative trading for the foreseeable future, which could potentially span the next 1-2 years.
The trading industry has garnered a negative reputation in the aftermath of the 2008 financial crisis and Michael Lewis' book “Flash Boys,” which I find to be somewhat inaccurate and sloppy. Some people who know me are surprised by my decision and often inquire, “Why do you want to work in the trading industry? Do you only care about making money? That’s not like you.”
While I have explained my rationale to a few close friends, I believe it would be beneficial to articulate it in a detailed blog post for two reasons. Firstly, I can easily direct people to this article in the future when they ask me the same question. Secondly, writing things down can help clarify my thoughts.
Firstly, for those unfamiliar with the term, quant trading involves using algorithms to trade securities such as stocks and options. It can take many different forms, but the common goal is to make the market more efficient by reducing the spread between the best buy and best ask prices. This benefits retail investors, who are able to get a fairer price for the securities they wish to buy.
So, why did I choose to pursue quant trading as my career path? There are a few reasons.
Firstly, I have always been a competitive person, and the zero-sum nature of quant trading appeals to me. It requires constant engagement and forces you to stay sharp, as you are always competing against others in the market. However, it is important to maintain a healthy competitive spirit and not let it consume your life.
Secondly, the engineering challenges involved in quant trading are incredibly complex and fascinating. Unlike building external products for the mass market, which can operate at the millisecond level, quant trading operates at the microsecond level, meaning you need a deep understanding of hardware and system architectures in order to optimize performance. This level of technical complexity attracts some of the smartest people in the industry.
Finally, from a research perspective, trading is essentially a multi-agent game with ever-changing rules and constraints, and the goal is to make a profit over a given time horizon. This presents a fascinating challenge in terms of building intelligent machines that can outperform humans with a success rate of 51% or higher, without human intervention. As someone who is passionate about building intelligent machines, this is a motivating goal.
In terms of my career trajectory, I am currently open to taking risks and exploring opportunities with smaller firms or even starting my own venture. While this may limit my options, I am playing the long game and am confident that I will eventually return to the field of quant trading even if I have to take a side step now and then. I will keep on playing and there’s one more reason which I will reveal as a follow up to this blog post if I become successful in my endeavours.