Nicholas S
- Research Program Mentor
MS candidate at University of California Berkeley (UC Berkeley)
Expertise
The application of data science to investment analysis, financial analysis, trading analysis
Bio
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
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.