Program Learning Objective
The Finance Research Program offers students an opportunity to delve into the fundamentals of finance, emphasizing stock markets and investment strategies. Students will develop a comprehensive understanding of financial instruments, portfolio management techniques, and risk assessment. The curriculum equips students with the skills to analyze market data, assess stock performance, and evaluate the influence of macroeconomic trends on investment decisions.
Feel free to reach out and schedule a complimentary consultation with our counselor. Each mentorship program is tailored to match an individual’s level of expertise and research interests.
Program Outline
Week 1:
The student will explore global financial markets, focusing on stocks and investment strategies. They will identify a research question, gather preliminary market insights, and set up R/RStudio for data analysis.
Week 2:
The student will acquire stock market data from sources like Yahoo Finance, Quandl, or APIs, and clean the data using R. Techniques such as handling missing values, outliers, and standardizing formats will be covered.
Week 3:
The student will perform exploratory data analysis on financial datasets using R, generating visualizations such as time-series plots, histograms, and correlation matrices to uncover trends and patterns.
Week 4:
The student will analyze stock performance using metrics like ROI (Return on Investment), alpha, beta, and Sharpe ratios. They will also use R to calculate and visualize risk measures, such as standard deviation and Value at Risk (VaR). The mentor will complete a mid-point evaluation to be given to the student.
Week 5:
The student will apply portfolio optimization techniques using R, such as the Markowitz Efficient Frontier or Black-Litterman model, and evaluate the performance of hypothetical portfolios.
Week 6:
The student will design an investment strategy based on quantitative analysis, such as momentum investing, value investing, or dividend growth strategies, testing its performance with backtesting in R.
Week 7:
The student will draft their research paper, detailing the methodology, analysis, and key findings. They will use advanced R packages (e.g., ggplot2, shiny) to create visualizations that effectively present their results.
Week 8:
The student will present their research findings in a professional manner, utilizing data-driven insights and visualizations created in R. With guidance and feedback from their mentor, they will refine their research paper for possible submission to academic or financial journals. The mentor will complete a final evaluation to be given to the student.
Economics Mentors
Mentor from MIT
Research interests include risk management, asset selection and portfolio management, financial derivatives pricing, market microstructure, catastrophic Risk Analytics and more...
Mentor from UPenn
Research interests include foreign investment and economic growth, financial crises, emerging markets, market structures and volatility, government fiscal policy, risk management and financial intermediation, and more...
Who Should Sign Up For This Program?
This program is designed for high school and undergraduate students passionate about economics and eager to deepen their understanding of how economic systems function. It is ideal for those considering future studies or careers in economics, finance, business, or public policy.
Next Available Start Date
Please contact us through our application form for more information!
Past Students’ Case Studies
Students’ names have been anonymized to ensure their privacy is protected.
Nirav Subramanian
Residence: Utah, US School: Walton High School Intended major: Business...
Cole Verma
Residence: Utah, US School: American Preparatory Academy Intended major: Business...
Lily Lin
Residence: Florida, US School: University of Florida Intended major: Finance...
Get in touch with us
If you are interested in the Collegiate Mentorship Program, contact us or sign up to start your journey toward a successful future!
