Today we bring you the story of EPATian Steven Downey, who hails from the US, is based in the UAE and has spent more than a decade in finance and investment.
Steven is passionate about investing and aspires to the highest level of ethics and financial competency. A Chartered Financial Analyst (CFA) charter holder and a Chartered Market Technician (CMT) holder, he is a self-taught quantitative analyst. He is also pursuing an MBA from the London Business School.
We caught up with Steven over a call to learn about his journey and growth, as well as how he has achieved so much in such a short span of his career. This is how the call went.
Hi Steven, tell us about yourself!
Hi! I’m Steven Downey. I’ve been in the UAE for 7 years, and I'm originally from America. I have 3 young kids, one 5-year-old and a couple of 2-year-old twins. I play a lot on my hands and knees with them. I have a great wife who challenges me professionally, intellectually, and morally as a parent.
I love learning different perspectives, even contradictory perspectives - not about investments but also in life. I read different philosophies, from Sun Tzu’s ‘the Art of War’ or Confucius to ‘Jesus of Nazareth’ and modern-day scepticism, besides other things like economics, fiction, and nonfiction.
From a young age, I wanted to work in the investment industry. I cared about the idea of seeing wealth grow, and I was fascinated by the concept of compound interest. I wanted to help people manage money and make sound financial choices.
You’ve done your CFA, CMT, MBA and are established as a Portfolio Manager. How did you get into Algorithmic Trading?
Going into university, I realized I wanted to grow as a portfolio manager or an investment analyst. I started the CFA and later CMT program after graduating. I worked in the account and securities trading department of a US firm called Charles Schwab. I later moved to the UAE, worked in corporate finance, and eventually got back into asset management.
4 or 5 years ago, I started following investors like Corey Hoffstein (CEO of Newfound Research) and Marcos Lopez De Prado, and it has been great learning from their experiences.
I've seen that many times, in investing, people will believe in an idea just because they heard some principle from someone. It’s usually not backed by data. I was having a conversation with my friend about gold as an inflation hedge, and he said, “maybe it works, but I’ve never seen the data to back it up.”
This conversation started me on a path to challenge my thinking and start looking at what the data says. I wanted to test an idea myself and see if an investment strategy works and if an investment relationship is statistically significant.
I asked around a few of the Quants and several friends in the industry. I started learning R based on their advice, but I realized that Python was the premier language of finance.
I wanted to understand investing and trading from a different perspective, starting from the fundamentals to technical to quantitative trading. If there was a skill or a tool that would help me as an investor, I wanted to get it. I was looking around the internet for a cost-effective way to learn Python, and that’s when I found out about QuantInsti.
I thought EPAT was a good choice considering the content, the value, and the cost. I needed the formal training - because I felt I couldn't get to where I wanted to be if I was learning on my own. I initially started learning Python on my own and used EPAT to formalize and structure my learning.
Presently, I am working at Mada Capital as a Portfolio Manager. We are a young firm and have around $140 million assets under management, and we’re trying to grow it to half a billion in the next year. Our clients are based out of the Arab Gulf and Egypt, and I’m in charge of building multi-asset portfolios.
I’m also pursuing an Executive MBA from London Business school.
I want to keep growing intellectually, reach my limit, and know that I pushed myself instead of having regrets later.
What change has EPAT brought in your professional life?
The thing I like about algo trading is the ability it gives me to test an idea systematically and verify its efficacy. For example, when I did my EPAT project, I was curious if we could use ML and fundamental data to build a value portfolio that generates alpha.
I like the idea of building something and testing it instantly.
I felt EPAT was worth my time and money, and I’m a satisfied customer. When I was interviewing for my current role back in August, one of the things my current boss noticed was my research publication - which was basically my EPAT project.
I improved it and got some outside feedback. One of the organizations I respect decided to publish my work on their website. I also did a few blog-type posts on Medium that got a lot of traction. I put these on my CV and this enhanced my career opportunities.
We also did discretionary research on gold and different companies and utilized systematic thought processes and coding in python to test the relationship between oil and ExxonMobil, or trend following strategy on gold as an asset class, for example.
Usually, an investment bank or a research firm might use chart overlays to find correlations, but we take it a step further to find statistical significance and actually find out if money can be made after transactions cost and things like that.
Recently there is a lot of concern in the markets about inflation. I was curious to see if I could produce an inflation forecasting model using Gradient Boosting or Random Forest python libraries.
I didn’t feel that my discretionary inflation forecasts were better than the markets, but maybe I could use the programming skills I picked up from QuantInsti and build a 90% confidence interval model for inflation. These are the sort of things I'm doing for work.
Is there any particular feature of EPAT that you really value?
The one feature that was really helpful was the syllabus of EPAT.
It was structured to progress from building systematic strategies in excel and moving it to python. It started simply by building a strategy on excel, understanding the mechanics, the win ratio, and the stop-loss, and translating it to Python code.
One of the significant concerns for me was learning how to build systematic strategies.
There are many other features, but the way QuantInsti managed to teach systemic strategy building was very helpful. I had a lot of difficulties figuring this out as there weren't a lot of free resources that gave the code and guided me through the process step by step. After that, I learned that I could take an idea like how to build a breakout model on a random S&P stock and run that program on a large data set. This was very satisfying.
The EPAT course helped me become aware of different types of volatility strategies and short-term mean reversion strategies out there. I haven’t personally developed any in-house strategies to execute on this. Still, it has helped in terms of what sort of managers to allocate capital to and realize the areas where I should be competing.
Right now, the firm I work at does not have the capacity to pull off any systematic volatility or mean reversion algo trading, but we may in the future.
At the end of the day, if you’re in the age group of 55-60 and you’ve taken the traditional finance route,you can just complete your CFA and CMT and not worry about anything else.
But when you’re my age in the middle of my career, spending 6 to 12 months to learn the programming skills will help me for the rest of my career.
All the young people who graduate from universities start learning Python and go on to work in hedge funds. I can either adapt or become a dinosaur.
Right now, you need to constantly upskill and develop a more balanced skill set. It’s great if you’re really good at discretionary fundamental analysis, but if you look at the top firms in terms of returns, you see these big quant firms like Renaissance Technologies.
If you have someone that’s done the CFA and can do fundamental analysis and the person next to them can do the same thing, plus they can code and program, who’s more valuable?
It’s the person that has more skills.
The way I see it - is that you spend a little time and money investing in yourself, and that’s going to pay dividends for the rest of your career.
- If you’re really ambitious, get your Masters in Computational Finance.
- If you have an Engineering degree, go for a Master's in Computational Finance
- And then there are traditional finance folks.
But, there’s a lack of people that can do both.
I want to be able to do a fundamental valuation of a company in excel or by hand and be able to form systematic strategies. I want to know how to do both because when I manage a team, I want to be able to speak both languages.
What is your message to the aspiring Quants out there?
Some people are motivated by career and survival of the fittest mentality, but for me, an additional motivation that can be inspiring is being curious and being hungry to learn more.
For me, it was that if I learn a skill, I'm more powerful. I can understand more and do more things. I didn’t do it primarily because I wanted to have a job in 5 or 10 years.
I’ve done my CFA and CMT, but there was this area of investing called Quantitative Investing that I didn’t know much about. I wanted to learn because I thought there was value for me in the field. It is essential to be curious.
There are a lot of people that do EPAT but never use Python for the rest of their careers, but if you're curious, you say, “I want to apply this concept in a new way.”
It's the idea of never wanting to stay in the same spot but constantly developing and growing.
There were many dry spots in my career, and part of my thinking when I got into EPAT at QuantInsti and Algo Trading was:
I can’t control circumstance and what happens to me, but I can control what I do about it, what I learn, and the skills I acquire.
I always think, “How can I have more skills to become more valuable and effective as a worker?” I think of skills in terms of Role Playing Games; when a player gets a new sword or a new gun, they become more powerful and get to a higher level.
You add more skills to your tool shed, and there will come a time when you're exploring 10-20 strategies and stick to a rigorous scientific and systematic methodology, and you don’t find anything that works, but you keep moving forward. A lot of it is perseverance.
I think it’s two-fold: you have to learn to keep going and not quit even when it’s discouraging, or you feel like your career is not working, or you’re in a dry spot.
But, at the same time, you have to keep moving forward and learn and upskill. You have to add skills to your repertoire that are satisfying for you regardless of whether it helps your career, but also look good on the CV and open doors for you. The perseverance and the drive to stay curious are vitally important.
Consistent learning and upskilling are what gives an edge to your learning and help you progress in your profession while being ready for the future. Your learning experiences and approach towards your profession are pretty contagious, Steven. We’re sure a lot of our readers would have a lot to take away from your experiences. Thank you for your time.
The Executive Programme in Algorithmic Trading (EPAT) is a comprehensive course covering topics ranging from Statistics & Econometrics to Financial Computing & Technology, including Machine Learning and more. Start your quest to upgrade your knowledge of Algorithmic Trading with EPAT. Check it out here.
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