About My Projects
Every project I build blends finance, data, and creativity. I focus on turning complex information into clear insights through financial modeling, analytics, and AI-driven tools that bring economic ideas to life.
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​I’m passionate about the projects I create and the stories behind them. Each one challenges me to think critically, analyze creatively, and uncover insights hidden within real-world data. Most of my work centers on financial modeling, valuation, and data analytics; exploring the relationships and trends that shape economic behavior and business performance. I also integrate AI tools like Gemini into projects such as my Cobweb Economy simulation, combining finance, data, and artificial intelligence to better understand market dynamics and decision-making.
Project 01: Meta Platforms Inc. Valuation Report (DCF & CCA Analysis)
This project is a detailed equity valuation of Meta Platforms Inc., developed collaboratively through financial analysis and research. It features a Discounted Cash Flow (DCF) model and Comparable Company Analysis (CCA), supported by a macroeconomic outlook, industry trends, Porter’s Five Forces, corporate structure, and governance review. The DCF incorporated declining revenue growth, margin assumptions, and a terminal value to estimate an intrinsic share price of $476.24, compared to a market price of $547.27 as of April 25th 2025. My primary contributions involved building the financial model, conducting the valuation calculations, and developing supporting Excel materials and visuals.
Project 02: Investor Simulator Game
The Investor Simulator Game is a turn-based educational tool that helps players learn core investing concepts by simulating stock market decisions over 20 years. Focused on the video game industry, players buy and sell shares in companies like Nintendo, EA, and Take-Two using real historical data and financial ratios.
With each round, players respond to industry news, analyze company performance, and track their portfolio’s growth. The single-industry focus simplifies comparisons and highlights how financial metrics and market events drive stock prices.
Built with Python and Pygame, the game promotes financial literacy, strategic thinking, and hands-on experience with investment decision-making.
Project 03: Cobweb Economy using AI
In this project I developed a program to simulate a cobweb economy, which is an economy that is dependent on prices in previous periods. This program uses the GEMINI api as 6 farmers that are professional forecasters trying to predict the price of a product of which its price is determined by the previous predictions of the farmers. This project works to simulate how real world price predictions might look like and how the economy would react.
Project 04: Home Purchase Report
This project analyzes housing options for a recent graduate earning $80,000 per year, evaluating the financial feasibility of renting, purchasing with a mortgage, and buying outright with cash. The analysis considers total annual costs, budget allocation, financing implications, and long-term investment potential to determine the most cost-effective and sustainable housing choice.
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Key Analysis Methods & Financial Formulas:​
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Annual Worth (AW) Calculation: AW = PW(A/P,i%,n) – S(A/F, i%,n) to compare lifetime costs.
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Internal Rate of Return (IRR): Used to assess long-term profitability of purchased properties.
​The findings provide an evidence-based recommendation on the most suitable housing choice based on financial feasibility and investment potential.
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Project 05: Political Ads on SnapChat Analysis
This project focuses on analyzing Snapchat political advertisement data to answer key questions about ad performance, demographic targeting, and ROI (Return on Investment). Using Python's pandas and matplotlib libraries, we explore how factors like age, gender, region, and spending impact ad impressions and engagement. The fictional premise and relevance for this type of analysis was deemed to be we were working for a political group that wants to advertise on SnapChat. By analyzing key factors relevant to advertisement success we can better optimize ads to reach their intended audience and viewership goals.
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Project 06: Presidential Polls Analysis
The idea behind this project was to determine whether or not past performance in terms of accuracy of pollsters was determinative of future performance in the 2024 election. It was not, according to the analysis performed. I used live poll data collected from fivethirtyeight.com and created data visualization for the 14-day rolling averages for both candidates, Trump and Harris, along with much more. This analysis provided valuable insight to the 2024 elections.
