My full name is Charles Sumner Crow IV. I was raised in Princeton, New Jersey and moved to New York City for graduate studies in 2003. I currently live in northern Brooklyn and work in midtown Manhattan.
I have worked on the buy-side as an alternative money manager for the majority of my career. My primary interest is the generation of market-neutral, absolute returns for institutional investors. I generate data-driven investment decisions for long/short, multi-asset class portfolios using modern open source software and machine learning.
I am an advocate for empirically-driven decisions throughout a modern investment firm, spanning the front-, middle- and back-offices (for more details, see my paper “Frontline Data Science: Human + Machine”). I believe the integration of a high impact Data Science team across an organization is non-trivial, but paramount to success.
Even though I am heavily quantitative, I believe both discretionary and systematic alternative strategies play important roles in any robust institutional portfolio (assuming incentive fees are calibrated to pure alpha expectations, and not paid for ‘commoditized’ systematic factor exposures). The thoughtful application of two investment styles will lead to the highest probability of future success in the modern era of capital markets, dominated by (i) interconnected, fast-moving markets and (ii) vast amounts of data, routinely characterized by unstable correlations.
I am a co-founder and member of the steering committee for the Quantitative Research Colloquium (QRC), Sponsored by Morgan Stanley, a monthly discussion forum for Quant and Data Science practitioners to exchange ideas, share best practices, and stay current on new academic developments in the fields of machine learning and quantitative investing.
My undergraduate studies focused on neural networks, agent-based simulations, and traditional computer science fields (e.g., theory of computation, data structures, algorithms, distributed computing, etc.). My graduate studies primarily spanned optimization and stochastic processes with applications in finance.
Mathematics provides a framework for disciplined research, but software is required to obtain empirical results. I view programming languages as tools and select the most appropriate language for a given task.
Currently, I conduct data analysis, visualization and modeling primarily using R within RStudio. I use the Tidyverse suite of packages for data wrangling and Tidymodels for modeling. I am a devoted Linux command line user.
I am a former Treasurer and Trustee of The Oliver Scholars Program, a New York City-based 501(c)(3) nonprofit. I was the Chair of the board’s Finance and Compensation Committees, as well as a mentor through the end of 2015. The program’s mission statement is:
The Oliver Scholars Program identifies and engages extraordinary New York City students of African and Latino descent and prepares them for success at leading independent high schools and prestigious colleges.
Please reach out to me if you’d like to contribute to this program.
Outside of the above activities, I enjoy abstract contemporary art through various mediums, in particular: audio, visual, and architecture.
My favorite artists include (but are not limited to): Christian Fennesz, Mountains, Ryoji Ikeda, Tim Hecker, Alva Noto, Mark McGuire, William Basinski, Jefre Cantu-Ledesma, Stephan Mathieu, John Fahey, Barnett Newman, Agnes Martin, and Robert Ryman.