IQC Finalist Spotlight:
Vaibhav Gupta

International Quant Champion, Vaibhav Gupta, discusses his experience during the competition.

Where did you grow up?

I was born and raised in Delhi, India.

What did you study at university?

Currently, I am in my third year of undergraduate studies, pursuing a B.Tech major in Chemical Engineering and a B.Tech minor in Computer Science from the Indian Institute of Technology (IIT), Delhi. My keen interest lies in Finance and Mathematics.

How did you get interested in quantitative finance?

I have always believed in the potential of automation, so naturally, trading instruments with algorithms caught my attention. My interest in finance developed during high school when I started reading balance sheets and quarterly results of companies.

How did you hear about the International Quant Championship (IQC)?

Our team’s fascination with quant finance predates our knowledge of the IQC. We first learned about the IQC when the WorldQuant BRAIN Team visited our campus for an introductory session.

How did it feel to be one of the winners?

Being recognized by esteemed individuals, whom I have always aspired to emulate, feels truly special. The praise from leaders in the field, serves as motivation to strive for excellence. Participating in the WorldQuant Global Summit was a humbling experience, allowing me to learn and interact with everyone in attendance.

What do you want to get out of the BRAIN Consultancy Program?

Competing in the IQC for almost 9 months provided structure to my interest in quantitative finance. I gained practical knowledge that would have taken much longer to acquire otherwise. Through the BRAIN Consultancy Program, I aim to delve deeper into this field, experiment, implement, and make contributions to the world of quantitative finance.

What do you like most about the BRAIN platform?

BRAIN, as a platform, encourages us to think beyond code. It reduces the initial resistance that the community may have felt during web-simulations. It empowers us to simulate, test, and appreciate our own ideas. Personally, I appreciate the diverse dataset and data field pool that it offers.

How do you come up with ideas for new alphas?

I start with my own intuition and then validate ideas and results through literature. This helps me create unique, value-adding, and robust signals. I firmly believe in the saying, “alphas are hidden inside data.” By utilizing diverse fields, datasets, and implementing unique ideas, I can seek to generate high-quality signals.

What is the most challenging part about doing quant finance research?

The freedom and power that quantitative finance research provides also bring the responsibility to consistently outperform expectations by adding value through diverse and deep thinking. Building robust signals can be both exciting and challenging, especially in certain market scenarios.

How has your experience working with WorldQuant and the IQC helped shape your career goals?

Through my interactions with various people at WorldQuant, I have maximized my learning opportunities and gained insights that would have taken me many years to have gained. I have learned to stick to the basics and understand the fine line between complexity and unnecessary complication. Participating in the IQC has given me more confidence in the potential of this field and made me realize that we have only scratched the surface.

What advice would you give others considering getting involved with WorldQuant BRAIN and competing in the IQC?

WorldQuant BRAIN opens up new possibilities in the field of quantitative finance. It recognizes the power of quantity along with the importance of unique and diversified signals. The International Quant Championship is a prestigious platform. Deciding to participate in the IQC was one of the best decisions I ever made. It has accelerated my learning, boosted my confidence, and provided an invaluable experience.


* WorldQuant defines “Alphas” as mathematical models that seek to predict the future price movements of various financial instruments.

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