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Nicholas S

- Research Program Mentor

MS candidate at University of California Berkeley (UC Berkeley)


The application of data science to investment analysis, financial analysis, trading analysis


My name is Nicholas Schantz, and my academic and professional passions are the application of data science and automation to financial analysis, investment, and portfolio management. I have been programming for 15 years, and working in finance for 6 years. I strive to produce rigorous quantitative analysis to support or disprove existing heuristic approaches to financial analysis and to better explain and provide predictive analytics on factors affecting asset performance. My personal interests and hobbies include application and analytical programming outside the realm of finance and data science. I initially studied piano in my undergraduate career, and so piano and music composition are of deep personal interest as well. I have also spent a considerable amount of time on music production and recording engineering. Recently, I have been learning Broadway musicals.

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Interaction Effects of Stock Characteristics on Common Momentum Signals

In stock trading, momentum is a popular factor to determine probable future performance. However, there are innumerable variations on the momentum factor, and they are not all equally predictive. The predictive nature of momentum may also vary across stock characteristics, e.g. market capitalization percentile relative to an index, price-to-book ratio, earnings growth etc. We seek to better understand the variance in the predictive power of the momentum factor by examining the most common expressions of the momentum and the interaction with commonly examined company characteristics. We will then discuss possible explanations for these effects and their implications on future performance and portfolio management.

Coding skills

python, C/C++, BASH, SQL, NoSQL, Tensorflow, Keras

Teaching experience

After my undergraduate degree, I was a volunteer teacher in Ecuador at The Center for Working Families. I taught a music class for grades k-12. Class sizes were about 20-30 students, with around 200 students total. We focused on getting to know the kids and building rapport with the community. In addition to teaching music during the school day, we also provided Spanish literacy and math instruction to parents in the evenings.


Work experience

Manning & Napier Advisors (2021 - Current)
Research Data Scientist
Manning & Napier Advisors (2018 - 2021)
Quantitative Research Associate
Manning & Napier Advisors (2016 - 2018)
Research Assistant


State University of New York at Buffalo
BA Bachelor of Arts (2014)
University of California Berkeley (UC Berkeley)
MS Master of Science candidate
Data Science

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