If you are in a profession different from trading, you might wonder what can be done to learn Algo Trading. If you have the knowledge of trading, you might aspire to get a better understanding of things to align your Career with it.
Here’s how the discussion went.
Hi Anurag, tell us about yourself!
Hi! I’m Anurag Sharma. I’m working at the Bank of America and hold a Masters in Engineering from IIT Bombay and have studied Management from Harvard Business School.
I’m a third-degree blackbelt martial artist in unarmed combat and completed 10 years of training. I like to read technical books and I have been studying a lot about finance.
During the Pandemic, it took time to adapt to the new format of work from home as well as dealing with the lack of interactions. It allowed me to dedicate more time to myself to complete Epat and study more.
What’s your story behind learning Algo Trading after learning Engineering and a career in Finance?
I've done my Master's and Bachelor's (a dual degree) from IIT, Bombay in Computer Science in 2007. Being a part of the Robocon competition is a fond memory from IIT that I cherish. I’ve done 2 internships – with a consultancy firm for developing programs, and another for creating a social graph based on the relation between two entities.
My roommate was working for an educational institution, so I joined along with him and gained a good exposure creating a trading system end to end all by myself. After that, I joined the Bank of America in 2013, developing trading programs to support the applications used by the bank and the global markets.
I was drawn to Algo Trading– it has instant rewards and instant punishments, unlike regular trading where you have to wait for some time to realize the worth of earned or lost.
After a year of working, my manager suggested additional learning that would help in my profession. This got me searching for courses and that was when I found EPAT. From there on my interest started in Algo Trading.
Since I had a computer science background and a decent understanding of mathematics, it seemed like a good challenging opportunity. And, yes, it is more Live in nature.
How did you come to know about EPAT, and why did you choose it?
Since my career is more on the lines of a web developer, I wanted to look at a career in quantitative finance. I was searching online for quantitative finance courses, and that's how I found QuantInsti.
I found the course structure of EPAT to be very complete in nature. It was the perfect starting point since it covered everything right from the markets to the basics of a financial instrument and how the markets operate.
EPAT has the best introduction to algorithmic trading - what it is, how it is done, and how you can trade algorithmically. Obviously, there are a lot of things that a person would need to study even after that, but I think EPAT provides a very good starting point, no doubt on that. One is guided right from starting with the basic strategy, and how to code them, and taking them live.
The applications that we work on are basically used directly by traders, so it is useful for me since now I can understand their needs better and get the perfect overview of the concept laid out at hand.
In short, EPAT helped me get into the psyche of the trader.
Initially, I was very clueless as I would get bits and pieces of information, either from an online search or from my colleagues - it was all broken information. But with EPAT, I was able to put them all together accurately in one piece. This is exactly what I intended to achieve.
What is the best feature of EPAT according to you and what do you like about it?
The first half of the course provides a good base providing a very good idea of the trading, trading strategies, and the infrastructure. Right from the development of a strategy in the excel sheet to Python coding is smooth, seamless, and very well explained.
It builds interest at the beginning of the course. For a person who is new to algo trading, it is very easy to understand.
The second part is, the security derivatives options – it is covered quite well by Dr. Euan Sinclair.
I have a much better understanding of the financial markets now. One lesson was that risk management is a very important aspect. It is not how much risk you take but how many times you are correct.
I’m more aware of the what, how and why of strategies, what to take care of, backtesting, etc.
My Support Manager, Subash, has been extremely helpful. He was very prompt in responding to my queries within mere minutes regardless of the time of the day. Throughout the course, he proactively ensured that the things were going well for me.
Any words that you would like to share for all those aspiring Quants out there?
You can put your emotions to the side and deal with things in a more mathematical, logical fashion.
I’ve read a few books – and a good piece of advice comes from my favourite author Matt Davis (who is rated as one of the good traders around). It is okay even if you’re not right 50% of the time if you're right even 49 times out of 100, you are good trader, importantly, you need to manage your risks well.
I think it is important that you focus on risk management - it differentiates a good trader and a good forecaster.
Thank you for your generous words about EPAT, Anurag. We’re glad that we were able to provide the right guidance and help you achieve your objectives.
It is pretty interesting to see how you went on from learning IT to getting into a fine establishment like Bank of America. Plus, you not only learnt algorithmic trading to add value to your career but also achieve the EPAT Certificate of Excellence. Congratulations!
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.
Disclaimer: In order to assist individuals who are considering pursuing a career in algorithmic and quantitative trading, this case study has been collated based on the personal experiences of a student or alumni from QuantInsti’s EPAT® programme. Case studies 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.