Is it possible for an IT professional to also be a successful high-frequency trader?
Absolutely!
With 17+ years of experience in Information Technology and Investment Banking, Praveen Singh is also a result-driven, ambitious Electronic Trading expert with an excellent track record of delivering cost-effective, high-performing solutions in all global hubs (Japan, Hong Kong, Australia, AMER, EMEA).
His rich experience also includes designing DMA, HFT and ULL (FPGA solution) offerings for Japanese markets and working as Vice President in top global companies such as Credit Suisse and Deutsche Bank.
Let's follow his journey into algo trading.
Hi Praveen, tell us about yourself!
My name is Praveen Singh, I am from India and I'm working in Japan since the last 14 years. I graduated in 2004, from a college named Army Institute of Technology, Pune.
After graduation, I worked in Pune and Bangalore for 3 years. Then I came to Japan in 2008 and since then I've been based there. So over the years, I have been working on the development of market connectivity.
I come from an IT background and I had a lot of interest in algo trading, and strategy backtesting. As a result, I came across QuantInsti which is a unique organisation that I haven't seen anywhere else. I got intrigued, did some research, and made the decision to enroll in their programme where I can benefit from the experience shared by the industry specialist who actually will help me achieve my goals.
Engineering to Finance - How did that happen?
I did my graduation in electronics and telecommunications but my special interest was in microcontrollers and robotics. I had a team in college where we made robots and represented these robots in established tech fests organised by leading Indian institutes.
There were only two companies in Pune that did placements for robotics and in my final year I got selected for one of them. When I joined as a fresher in the organisation, I started to feel that my technical abilities weren't utilised and that made me feel frustrated.
I was part of that organisation for 3 months and then started looking for companies in the field of robotics. Unfortunately, they were not hiring at that time and I had also started to feel a bit of pressure from all sides.
I always had the curiosity to work in a startup and that's where I was exposed to finance. I worked in a startup for 3 years. In our organization, I started getting involved with clients and developing trading applications, which helped me connect to finance.
I gave up my Robotics ambition and wanted to become a financial specialist where I can make smart applications that can help me make money.
What has your journey of learning Algo Trading been like?
After 3 years at the startup, I joined Deutsche Bank in Japan as a client connectivity engineer. My responsibility was to build and customize client connectivity applications and enable our firm to provide a platform for our clients who want to trade with our organization.
Over time my role increased and I was made responsible for the electronic trading platform for the Japan equities franchise in the firm. Like other firms, our firm was also offering algos for the clients to trade.
This was a black box to me. People talk about algos and various schemes like how different clients wanted VWAP or percentage volume or a particular strategy for their trade, etc.
These terms made me curious and I wanted to know what they meant and more importantly how it affects trading decisions. I spoke to my mentors and came to know that there is a special group called a quant group that sits with our organisation and they design these strategies.
I started to read books and tried to understand how this all worked. To be a successful electronic trading lead for a franchise it became a necessity for me to know details of algos and their behaviour being offered by the organisation.
My understanding increased regarding algorithmic strategies. However, I was not satisfied with just that. I felt that I wanted to know more about it and that's where QuantInsti came into the picture. The reason to know more about algorithmic trading and strategies was that -
- I wanted to learn more about this domain
- Quants have a large income
- The demands of the quant jobs in the market were increasing
- I desired of starting a trading firm
Since I am in a financial organisation in Japan, we are not allowed to trade directly or do exchanges. But cryptos came in and people had exceptions to these policies. I wanted to learn and use that to see whether with that learnings I can make more money.
That’s how I came across a unique organisation that was dedicated to algorithmic trading, QuantInsti and their programme called EPAT. It is an opportunity to learn from the experts. I can always read various books but coming from experts and specialists was game-changing for me.
What were your challenges while learning EPAT?
One of the reasons I joined this course was because of the success stories that I had read on your blog. They inspired me and made me realise that anyone can learn algorithmic trading.
Another best thing about the course was the faculty members such as Dr E. P. Chan. I have read a few books like Winning Strategies and Their Rationale by Ernie Chan and Algorithmic Trading by Ernie Chan.
I researched before I joined the course. They had a primer that was mandatory before you join in and they evaluate you based on that primer. That help me a lot and I could understand what they were looking for so that they could guide me to the correct course.
To start with, they gave me a brief overview of microstructures and a couple of statistics, if you want to specialise in options trading or if you want to start with machine learning they have a primer for that as well.
Going through that I understood that the whole course has a lot of perks than just providing skills, but also providing the candidates with an opportunity to specialise in various fields as per their interest. My interest at that particular time was cryptos and I come from an equities background so I had an interest in that as well.
I spoke to the faculty and they were very clear about what was required from me before joining. Programming wasn't an issue for me since I came from a programming background. Although they mentioned that most of the stuff was done in Python and I was not comfortable with it, I was ready to learn it.
One feature of EPAT that you liked the most!
A lot of people joining this course come from various backgrounds such as IT like me, from trading economics and some from non-technical backgrounds. So for them, the Python language would be challenging, as someone who has never done programming.
I was not familiar with the Python language before. The way the QuantInsti team taught Python was just phenomenal. They taught the very basics of Python and if I would have taught someone the Python language, it would be like this. I interacted with a few people who didn't know Python and met them in some extra classes that enabled us to tackle them. I started to understand it a bit more with effort but the direction is important that QuantInsti showed incredibly.
Learning Strategies was also a challenge for me. The first lecture was on writing a VWAP strategy using an Excel sheet. They started from the scrap, starting with the very basics of VWAP, how to implement it and later back test it on historical data and calculate PNL. In same class we were also taught how to tweak certain parameters of strategy to improve PNLs.
The biggest challenge turned out to be statistics because we use heavily use statistics in algorithmic trading. I never studied it deeply and college but I wanted to learn more about it. As the course progressed forward, they helped me in every way possible. The support team is amazing and has always answered my questions. They help you to start and it's up to you where you go from there. After completing the course I have set up a small desk and I am using cryptos for now.
What are your plans for the future?
Technology enables traders what they want to achieve and some specialised traders understand markets and learn how to manipulate trades. A lot of quant traders use algorithms to decide what's the best strategy so that the most efficiency can be achieved. Now trade is best executed by the best algorithms in present market situation and those come from technology. We have to always keep up with the current trends to enable our business.
A year ago, cryptos were reasonably doing well for me, I managed to host hand written algorithms in cloud platform helping me trade cryptos, but the bigger plan is to leave IT and join the Quant side. I would like to set up a reasonable sized desk and depending on my success in this I would like to expand it into equities and not just cryptos and hope to see where it goes. Before that a lot of learning is to be done, things to be sorted and it will take time.
Your message to all the aspiring Algo Traders out there!
My advice is to start with being curious, and if you have the desire to learn and the curiosity to explore something, seize the chance to learn when it presents itself and work to realise your goals. Channel your focus and energy toward what you want to do with the aid of progressive direction, and advancement will follow. You can only succeed with passion, hard work, and patience.
Thanks for your time, Praveen. We’re delighted to have been able to guide and help you in your Algo Trading journey and make your story a success! We wish you continued success and hope you achieve even more.
If you too desire to equip yourself with lifelong skills that will always help you upgrade your trading strategies. With topics such as Statistics & Econometrics, Financial Computing & Technology, and Machine Learning, this algo trading course ensures that you are proficient in every skill required to excel in the field of trading. Check out EPAT now!
Disclaimer: In order to assist individuals who are considering pursuing a career in algorithmic and quantitative trading, this success story has been collated based on the personal experiences of a student or alumni from QuantInsti’s EPAT programme. Success stories are for illustrative purposes only and are not meant to be used for investment purposes. The results achieved post-completion of the EPAT programme may not be uniform for all individuals.
