Experiential Learning Project (ELP): Building Quant Factors and Screening Tools for Fundamental Investment
Client: Smith Investment Fund (SIF) at the University of Maryland
Course Prerequisites:
- Investment or Capital Market (with good academic performance)
- Financial accounting or financial statement analysis (with good academic performance)
- Financial data analytics (such as regression, time series analysis)
- Good skills on programming in R or Python
- Excellent communication skills
Process to Select Students:
- Open to qualified MF and MQF students
- A short cover letter explains your background and motivation in taking this project
- Most recent CV, transcript, and relevant course grades
Project Overview:
Quantamental (fundamental integrated with quantitative) equity investment has become popular in money management industry. Almost all buy-side fund managers (e.g., T. Rowe Price, Fidelity, Capital Group) have extensively used quant techniques in their investment process.
Students taking this ELP will have hands-on experience to build quant factors and especially screening tools for long-only fundamental fund that typically has low turnover and focuses on long investment horizons (such as 6-12 months). These outputs will be routinely (and automatically) updated to help make stock investment decisions by the University of Maryland’s Premier Investment Group. Skills learned in this project are almost the same as what have been used over years in one top-tier mutual fund firm in the U.S. These skills will help students place in asset management industry that requires solid training on integration between quant factors and fundamentals knowledge.
The UMD SIF is supported by the Robert H. Smith School of Business Foundation, Inc. Currently, there are three student investment funds: Mayer Fund, Senbet Fund, and Global Equity Fund. The SIF investment philosophy builds on a top-down strategy to evaluate a company’s securities for potential investment by conducting economic, financial, industry and company analyses. Building systematic quant factors and then deriving a set of scientific screening process from a fundamental investor’s perspective are important for the success and sustainability of the student investment funds.
The focus of this project is to fully expose students with the following factor styles (the so-called existing “alpha” sources that are commercialized): value, growth, size, quality, momentum, low beta and volatility (or low risk), and dividend income. Under the guidance of faculty advisor, students will delve into GICS sectors (and industry groups) and construct sector-specific quant factors that are not present in standard textbooks but are based on domain knowledge from recent years of fund management experience. For example, valuation factors used in semi-conductor industry will be quite different from those used in energy oil E&P industry. Students will also work on a set of factors that typically used for screening purposes (e.g., capex, buyback, leverage etc.) in combination with firm fundamentals. Then, students will build a quant equity model by using various techniques to combine factors both within industries and across industries. Afterwards, we can regularly construct factors, update models, and track their performance over time to understand market conditions and communicate to investors. By the end of project, we should be equipped with a set of industry-standard quant factors, a set of quant models (across the full universe and for specific sectors), and a system of screening scores for stocks within our investment universe (e.g., S&P 500 or Russell 1000).
Skills Learned from this ELP:
- Master the holistic process of equity quant investment in practice from data sources, data inputs of firm-level fundamentals, factor construction, model and screening building.
- Extract, manage and manipulate a large cross-section of equity market data.
- Demonstrate ability to perform data analysis and visualize results with R or Python language.
- Ability to incorporate quant process into fundamental investment. Opportunities to communicate, interpret, and present results clearly to clients (such as portfolio managers, analysts, investment consultants).
Week 1 will be introduction of the equity quant investment process used in industry. For the remaining weeks 2-6, we will assign groups to work on a set of quant factor construction and model building by different factor styles and sectors/industries. Week 7 will be used to develop a screening system that is applicable for fundamental investors. Week 8 (during finals week) will be the presentation to our client (SIF representatives).
This ELP is not like a standard MFin/MQF course where each week a lecture is made, but rather the role of the faculty advisor is to provide guidance to the team and to solve problems that may arise throughout the project. The students “own” the project including project management, making team assignments and adhering to scheduled deliverables. Elevating issues early to the faculty advisor will ensure timely attention to resolving any issues that arise. Students will be expected to speak and interact during our sessions.