Competition involved analyzing the publicly-traded company, PennyMacFinancial Services Inc., and receiving hands-on training in financial and investment analysis to present a stock pitch to a panel of CFA Charterholders.
Project URL: Project & Recording
Developed a state-level Telehealth Cost Savings Model to assess the financial impact of pre-hospital telehealth programs across 31 U.S. states. Utilizing data from a 2016 Houston-based study, the model integrates healthcare inflation rates, regional price parities, and emergency department (ED) visit statistics. For states with incomplete data, such as Nevada, multivariate forecasting techniques were employed to estimate missing values. The analysis projects potential cost savings ranging from 2.48% to 16.22% of annual health and hospital expenditures, highlighting the significant economic benefits of implementing telehealth interventions.
Project: Telehealth Model
This project builds and analyzes the Heston model, which incorporates stochastic volatility to better reflect real-world market behavior—unlike the constant volatility assumption in Black-Scholes-Merton. Results show that despite added computational complexity, the Heston model delivers more accurate pricing for European call options, particularly over longer horizons with stable volatility.
Project URL: Model Validation
This project develops a valuation model for FedEx Corporation, incorporating its core logistics segments—express and ground delivery. Drawing on financial data, market position, and strategic outlook, the model applies a discounted cash flow approach and supports a strong-buy recommendation based on projected fundamentals.
Model URL: Valuation
Developed a fully automated shipping operations system using Google Workspace and Apps Script. Customers received personalized shipping details immediately upon registration, while invoice uploads were matched to internal package logs with a single click—streamlining operations and significantly reducing manual overhead.
Company Demo Link: https://linktr.ee/shippingdemo
This paper applies the finite difference method to solve the Black-Scholes-Merton equation, using Explicit, Implicit, and Crank-Nicolson schemes to price options. It compares results against the Binomial Cox-Ross-Rubinstein model, concluding that all three finite difference methods closely match Black-Scholes values—while Crank-Nicolson stands out for its faster convergence. The study ultimately favors the finite difference approach for option pricing accuracy and efficiency.
Project URL: Valuation