"Is it possible for a Retail Trader to make a shift to Algorithmic Trading?"
This is a question that we are frequently asked.
Today, we bring you the story of EPATian Vilvamoorthy. He has a combined work experience of more than 17 years working in the IT industry, is an Electrical Engineer and is a Certified SCRUM Master.
A retail trader himself, Vilvamoorthy has tremendous experience and knowledge of various programming languages and believes in consistently growing his skills.
He describes himself as:
A competent professional with nearly 14 years of experience in Software Programming, End-to-End Program Delivery, Product Development, Systems Design Engineering & Integration, Strategic Planning, Application Development, Maintenance & Support, and Process Improvement.
We caught up with him over a call to understand his journey and experience in this domain, so that we could share it with you. Here’s how the discussion went.
Hi, tell us about yourself!
I’m Vilvamoorthy Tamildoss, I’m an electrical engineer from Pondicherry. I’ve worked on multiple projects and take on different roles in my career. I’ve worked all the stages of a product life cycle from coding and testing to deploying through my 14 years of experience in the IT industry. I love playing football.
I spent a lot of time developing my technical skills.
Since you’re from the field of Technology, what led to you venturing into Algo Trading?
I was looking for a job in the software industry after graduating from college. But circumstances led me to work in the sales field in Pondicherry. Post that, I moved into the software industry - I was great at mathematics and that’s a required skill for coding. Now, it’s been 14 years and I've been working with different organizations on multiple projects in IT.
I believe that my sales skills have proved just as valuable as my technical skills over the years.
I started looking into the stock markets in 2010. I initially taught myself how to trade and I would consider myself a retail trader. Around 2016, I started digging deeper and discovered that a system called algorithmic trading has evolved.
I have a technology background, was already a C++ developer, well versed in a lot of other programming languages, and I wanted to translate that into the algorithmic trading domain. I did more research and found that my skills are perfectly suited for this area and QuantInsti were the only ones providing quality training in the domain of Algo and Quant Trading.
I’ve worked as a data scientist before and that requires knowledge of Python. My experiences with programming really came in handy when I was learning Algorithmic trading.
I felt like I adequately understood the technical aspects and now, I’m concentrating on building strategies. I’m trading part-time in the crypto and forex markets.
I want to start a proprietary trading firm in the future. That’s the benefit I want to have with all the time and resources I invested in learning algo trading. This is one domain I know a lot about.
I have confidence that with my previous experience in programming and all the skills I picked up in EPAT, I can start a successful trading desk.
After a certain age, I can’t really settle for a job and I want to start something of my own.
What role has EPAT played in your career?
I was looking at resources online and I couldn't find anything that was properly organized. I used to watch videos explaining different concepts but I couldn't get the whole picture until I joined Quantinsti.
With QuantInsti, the information is well organized and excellently delivered. This is rare with other courses - I’ve checked out a couple of them and there are always gaps in their courses.
The EPAT curriculum is very well structured and now I have a good understanding of the entire process, from strategy building to implementation.
Initially, I was sceptical about taking the course because I didn't know if I would get value for the money I'm spending. Looking back after these many years, whatever I invested in the course has proved fully worth it. The access to the latest course material and the support that QuantInsti provides is really good, in fact, I would say it’s excellent and I really appreciate it.
One of my biggest motivations to join QuantInsti was the network that you guys had developed.
I researched the faculty and your management team and saw that most of you are industry practitioners. The support team ensured that I was guided through the algo realm and I say confidentiality now that they delivered.
The EPAT alumni network and especially the lifetime access to classes means a lot. The classes get updated with info from the latest course and I’ll have access to the latest developments in the field.
What do you consider to be the best feature of EPAT?
Thanks to EPAT, I learned the entire infrastructure of the trading systems. Lectures about entry systems, the matching system, and the software the markets are built on - were very valuable to me.
Now when I build strategies, I look at the data and run my strategies through some statistical analysis to see the probability of a preferred result.
As a retail trader, I used to trade without any set process. After learning from EPAT I have a structured approach to trading with proper processes.
What message would you give to the aspiring Algo Traders out there?
The one thing I want to tell people is that whatever knowledge they acquire it is important that they apply it.
Learning doesn’t mean anything if it's not put into practice.
Your desire and compassion towards building yourself and your skills are remarkable, Vilvamoorthy. We’re sure, many retail traders out there would seek inspiration from your story. We wish you the best for your future.
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.
Disclaimer: All data and information provided in this article are for informational purposes only. QuantInsti® makes no representations as to accuracy, completeness, currentness, suitability, or validity of any information in this article and will not be liable for any errors, omissions, or delays in this information or any losses, injuries, or damages arising from its display or use. All information is provided on an as-is basis.