Dhruvi Nishar and Vedant Kabra understand how building a practical know-how is the heart of SP Jain’s learning experience. So, once they completed their Year 1 of the Bachelor of Data Science (BDS) program in Mumbai, both of them decided that it is time to put their newfound skills to test. And what better place to test their skills than at one of the world’s top universities and research centres?
“Vedant and I are currently interning as research students at University of Massachusetts Boston under the guidance of Prof. Lawrence Pohlman and Prof. Debashis Guha,” shares Dhruvi. “We are analysing 20 years’ worth of daily financial series data, including sector ETFs and the individual stocks in SP500. We are using switching models and machine learning techniques to determine investment rotation strategies that outperform buy and hold.”
An internship of this stature right after the first year of an undergraduate program is not a feat achieved by many. So, how did they secure these prestigious roles at such a young age? “Honestly, this internship wouldn’t have been possible without the support and guidance of our Director, Dr. Abhijit Dasgupta,” Vedant explains. “We got constant support from him and the other SP Jain faculty throughout our selection process, and I feel so obliged to them!”
“Throughout the internship, the one aspect that constantly stood out for me was the level at which we were able to apply the knowledge we gained in our SP Jain classrooms to the project,” Dhruvi continues. “I believe that the academic structure of the BDS program has equipped us with everything essential to succeed in this role. Our curriculum focussed a lot on machine learning and data visualization methods, and these are concepts that we could apply to my research first-hand, helping us gain favourable results.”
“The internship has made me go bonkers because of how much I was able to learn every day!” Vedant adds. “The entire project is based on statistical applications and machine learning techniques, and like Dhruvi said, these were areas that we had focussed on in our Year 1 classrooms as well. We are currently working towards finding different machine learning techniques that will help us in predicting the volatility of the coming market, and we couldn’t have done this successfully had it not been for the foundation we built in class.”
When asked about how this internship proved to be beneficial to them, Dhruvi recounts some specific examples. “This internship gave me the privilege to earn insights into the financial domain and develop my interests and skills. I studied about Bayesian Machine Learning, Principal Component Analysis, Markov Regression, and Efficient Frontier Analysis for optimising portfolio returns while minimising volatility using VIX as a signal, all of which are skills that I am assuredly hoping to implement soon.”
Vedant, on the other hand, has a witty retort: “Well, only if I get rich by investing in stocks in the next few years, can I know for sure that the internship has benefitted me, right!?”