Business Analytics to Quantitative Investing | How Siddhant enhanced his Trading

5 min read

"Patience, persistence, and perspiration make an unbeatable combination for success." This quote by Napoleon Hill reflects Siddhant’s life. Siddhant holds a Masters in Finance from the University of Rochester.

In addition to his enthusiasm, he has acquired countless skills over the years with expertise in factors-based investing, equity trading, financial statement analysis, and quantitative analysis.

We are thrilled to share his journey from working as a Business Analyst job, shifting to US Equities Trader, and now into the domain of Quantitative Investing in digital assets. EPAT empowered Siddhant to gain proficiency in Algo Trading and Python.

Hi Siddhant, tell us about yourself!

Siddhant Vaidya pic

Hi! I am Siddhant Vaidya, and I live in Jersey City, United States. I am currently working with the Product Development team at Galaxy Digital, New York.

Before this, I held roles across Quantitative Research, proprietary trading, and business analytics domains. I love experimenting and challenging myself across different industries.

I am passionate about cryptocurrencies, investing, robotics, aviation, and automobiles. Apart from my interest in trading, my go-to activity is go-karting for relaxation and blowing off steam. I also enjoy watching movies and exploring different cuisines from across the globe.

Could you describe your journey and how Algo Trading came into the picture?

After completing my Graduation in Engineering in 2016, I got my first job in the field of business analytics and consultancy. After a year, I focused my interest in capital markets owing to my personal interest.

I started my career in finance after joining Capstone, where I worked as a US Equities Trader. After getting some exposure to trading, I wanted to leverage my engineering background and learn various technologies to enhance my trading further.

This led me to join QuantInsti in 2018. EPAT brought me great exposure to this industry on another level. I acknowledged what a simple yet powerful programming language like Python could do.

In 2019, I joined a Masters in Finance Program at the University of Rochester, where I got exposure to a lot of aspects of the investment management industry, the quantitative finance industry, especially factor-based research.

Later, I spent a year and a half working with High Probability Advisors, a quantitative advisory firm based in Rochester and worked on multiple quantitative projects as well.

My desire to explore this area of systematic trading and finance is never-ending.

Coming from an Engineering background, did you face any challenges while learning Algo Trading?

One good thing that happened was, that I learned to trade before I studied algorithmic trading. My very first interaction with capital markets happened during the first year of my engineering.

I opened my first trading account, and with the little knowledge that I had, I started basic fundamental research on companies and buying their shares. Fortunately, I started getting good returns. This continued for a couple of years,

My experience in Capstone was a turning point for me. I was trading every day and had started developing good strategies and eventually good results there. The main challenge was that I found dozens of potential tickers, but it was difficult for me to manually trade more than 7-8 tickers at the same time.

Manual trading was just not doing the trick for me. Eventually, I got introduced to algorithmic trading. Because human limitations play a huge factor when it comes to trading. I just wanted to enhance it and scale it. Then I found out about QuantInsti’s Executive Programme in Algorithmic Trading (EPAT).

Which feature of EPAT stood out for you?

Initially, when I sat down with the course, it was quite daunting, because I was attending a 3-hour lecture on the weekend years after completing my studies! So, I had my doubts about whether I’d be committed to it.

But I felt that lectures were structured brilliantly, with the exercise materials and other sources which kept me engaged throughout the course.

I spent a lot of time scripting different kinds of strategies, and programs. One of the most beneficial things that I find was the hands-on project that I did during the last few months of EPAT, under the mentorship and guidance of Varun Divakar. My experience was tremendous and continues to help me even to this day.

Another great thing about EPAT is the diversity and alumni community. You can get a unique perspective on industries and markets from the faculty as well as a pool of fellow learners and alumni from across the globe.

EPAT has an amazing faculty, consisting of very successful, professional traders such as Dr. Ernest P. Chan, who is humble at the same time. I got the liberty to approach such people with every question I had. And they respond with equal enthusiasm every time.

I find QuantInsti pretty agile, adaptive, and up to the market trends.

The Placement cell is one of the biggest jewels of EPAT’s crown because after going through all the hours spent on the course, and practice you'd like to have the opportunity to apply all of your knowledge. It's also quite beneficial for the students to find a job, in this very niche field. They provide multiple job offers for various roles across different companies, and it feels good to have that support.

What’s your advice to the aspiring Algo Traders reading your story?

EPAT is a great resource for, anything related to algorithmic trading.

I come across people who take up courses with a mindset of making profits immediately after completing their courses. But it does not happen overnight.

I’ve come across individuals who have asked me: “What kind of expectations one should have from a course like EPAT?

It is important to understand and manage the expectations about the exact benefits you're going to get, and what is beyond the scope of this course.

My first piece of advice would be, to start trading and get real market exposure. Even with the smallest amount possible for you, there’s immense to learn from the markets.

My second advice would be to learn to program or code. Get a good hand on it. By programming, I mean, you need to understand what type of data is available in the market, how you can analyze them, and what kind of analysis will give you good results.

And lastly, have faith in yourself. Be persistent, keep working at it, and trust the process.

Very well said Siddhant! Your aspirations will indeed drive you on the path to success. Thank you for sharing your incredible and truly inspiring journey with us, Siddhant. As you said, that one can achieve anything if one has the necessary motivation and persistence. We wish you all the best in your future endeavours.

You can watch the complete discussion with Siddhant here:

If you too desire to equip yourself with lifelong skills which will always help you in upgrading 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.

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