Equities market offers a broad range of career opportunities. If you are in the business development, strategy or technical side of the business, this article will tell you how to make the switch to the profit earning side. Good working knowledge of the industry is what gives you an immense boost.
You understand the functionalities of the market framework and the workflow at the exchange. You already have knowledge of what effects the long-standing positions of the listed firms. Formulating a trading strategy and applicable technical understanding (like programming languages and platforms) is what is needed to become a quant. Identify your financial goals, draft your own strategy, acquire the technical acumen and you are good to go.
Read on to know how Maxime Fages, who comes from a strong M&A and corporate strategy background, enrolled with QuantInsti®. After the certification, Maxime started his own quant research firm. Derek, Maxime’s partner in this new initiative is also a QuantInsti® alumnus and the two of them met during the certification course. Their venture, Golden Compass, is doing excellently and is now one of our hiring partners.
Here’s a detailed discussion with Maxime Fages
I’m French but have been living in Singapore for over 4 years. In fact, my wife, my son Leon and myself are PR, and Singapore feels more and more like home to us. I have always had a deep interest in tech. I’m an engineer by training, and I love to experiment with new frameworks for processing or visualization at home. To take a break, I produce electronic music, surf or, closer to home, I’ve discovered Brazilian Jiu-Jitsu and I love it.
Tell us something about yourself?
I came from the M&A side of things. I had been putting prices on an asset for a large transaction, and eventually had the opportunity to go to a start-up fund. While my role was initially one of a specialist, I quickly took over a significant portion of the portfolio construction. The risk profile of an emerging fund is critical, and I quickly found out that I needed new tools and concepts to manage it. Even though I had (and probably still do have) a very good command of Excel, the amount of data and processing required simply was too much. I discovered R, and a number of very interesting concepts to price risk; for example, Expected Shortfall.
When did you discover your passion for financial markets? (Especially, Quantitative and Algorithmic trading)
After that experience, I have worked at the Chicago Mercantile Exchange, managing strategy for Asia. It is an incredible company with undeniably the broadest product scope, and I very much enjoyed the work there. I did research on the microstructure of the CME product during Asian trading hours because what is more important to a client than liquidity?
How did you come across QuantInsti's EPAT™ programme?
I was keen to look at the execution side of things and looked for a program. I heard about it through a prop trading client and the format, scope, and duration fit what I wanted.
It was rough! Managing personal research while having a regular job, and spending Saturdays and Sundays on web conferences was demanding. On the plus side, most of the content was very novel for me and given by faculty who are practitioners. I found them accessible, and keen to answer questions after class, by email or even taking calls.
How was your learning experience?
I was particularly keen to work with execution systems, to move beyond the hosted server model and to gauge machine learning potential. By then, I was interacting with Derek very frequently, trading research papers or interesting githubs. We had an ambitious scope so we asked, and were granted to work as a team. We ended up with an interesting trading system using cloud-based models in order to trade the WTI intraday.
After EPAT™, we kept on experimenting. After over 6 months of chat on TeamViewer and WeChat, we also finally met in person. We met in Bangkok, as it was midway between Singapore and Beijing and it was pretty surreal! One of the things we have in common is that we’re futures and options guys, and while quantitative technique and Algorithmic trading are going mainstream, Futures are still less accessible.
When and how did you come up with the idea of starting your own quant research firm?
So, in more than one way, Golden Compass stems from our passion for futures, and our desire to share the many incredibly cool things that can be done trading futures. We have ambitious plans for the future, including open-sourcing a full research to trading stack, complete with portfolio simulation and reporting. For now, though, we address a need that we felt as a client for Derek, and as a strategist for me. Exchanges, brokers and asset managers are all conscious of the increasingly sophisticated demands of their clients. In-house research is expensive and increasingly regulated. They, therefore, need a reliable provider to design content that is salient and actionable about the products they distribute.
Incredibly satisfying! We are unfortunately bound by strict NDAs, but we do have a couple large regional exchanges as clients and we see the nature of their work increasingly testing our skills. We have a solid infrastructure, and extraordinary talent (including some we hired through QI). Long days, and nights too, but it’s incredibly exciting.
How has been the journey so far with your initiative Golden Compass?
The whole asset management industry is under pressure. The Boston Consulting Group released an interesting report where they outline the structural changes in the industry. Net AuM flows have been slow for over a decade, and the product mix is shifting toward passive or cheaper options. That puts the margin of AM under pressure, and everybody is watching costs. Systematic funds have resisted fairly well in this context, but I do strongly believe that a lot of asset allocators and even individuals want now to do their own smart beta or alpha whenever possible.
How does the future look like? (For company and overall industry)
This is a positive trend for us since we produce research that is meant to bring traders closer to actionable solutions. The next step is to open-source quantitative tech, and we also have been approached to write strategies. This is the future, though, and for now, we need to manage the growth and sales pipeline.
Primarily, it was an incredible encounter with Derek in my case, but I also appreciate the growing reach of the alumni. I also have called in the faculty or QuantInsti’s team for support and always got solid answers. Classes are very interesting and provide a very good lay of the land. Of course, if you want to become a dispersion strategy expert or an execution strategy tenor, you need to put more work but at least you’re generally oriented.
How has EPAT™ helped you? Would you recommend it to others?
Motivation for aspiring quants or entrepreneursDo you also dream to become a quantitative trader or start your own trading firm? We are sure Maxime’s story emboldens your plans. Join our strong base of leading alumni and global faculty. Check out the Executive Programme in Algorithmic Trading (EPAT™). The course covers training modules like Statistics & Econometrics, Financial Computing & Technology, and Algorithmic & Quantitative Trading. EPAT™ equips you with the required skill sets to be a successful trader. Enroll now!
Do share your comments and experiences as an Algorithmic trader/Quant. We would love to hear about your inspiring career journey!