Quantitative Research and Analysis
What is Quantitative Research?
Ian Laker (MFE ’17)
Machine Learning Engineer at Apple
Having previously spent 5 years in Quantitative Research with Franklin Templeton, Ian Laker (MFE ’17) shares some insight on his decision to pivot to his new role at Apple.
Why the switch?
"A lot of methods used in both ML and QR are very similar, with the theory based in Math and Stats which is what my undergraduate background is in. The subtle difference coming in what problem you are trying to solve. My time spent in QR was predominantly picking out which assets to invest in based on factors of said assets. Financial markets however do have a lot of noise or idiosyncratic risk that ML methods just cannot account for. Sentiment is particularly hard to model or account for. The data science models typically taught in school translate better to real world problems as opposed to the investment space. This is the major reason I chose to move to the more traditional tech space."
What were some challenges?
"During my time as a quant researcher, I for the most part was not required to have any heavy engineering capabilities and I would primarily work with databases that had been pre-designed. My focus was the modeling and portfolio building aspect of research. Switching to my new role, one thing I realized early is that you need to be conversant with principles like version control, data pipelines and learning about different engineering tools that I had not been exposed to. You need to be part engineer, part data scientist to succeed here."
Francisco Ibáñez (MFE '17)
Quantitative Researcher at Bloomberg LP
New York, New York
Why Quant Research?
"The asset management landscape has undergone a profound transformation in recent decades. What was once an unstructured, qualitative approach has evolved into a disciplined, data-driven, and systematic process. Quantitative research stands at the forefront of this industry shift, serving as the driving force behind the quest for alpha. Engaging in this field demands a curious mind, critical thinking, a solid command of mathematics and programming, and the self-reliance to steer one's research. For me, choosing quantitative research is not just a career path; it's a commitment to navigating the dynamic world of finance, harnessing the power of data and technology, and seeking a competitive advantage in the relentless pursuit of higher excess returns."