Chafic
Charafeddine

My favorite class in my BS in Economics at Texas A&M was econometrics, and since graduating I have learned how markets price risk by taking part in them. Since January 2019 I have managed my own accounts and traded futures, FX and gold, learning technical analysis through in-person courses at Online Trading Academy. While I was taking those courses and trading my own account after A&M, I also worked as a delivery driver. I then went back for formal training: an MS in Finance from the University of St. Thomas (May 2026, GPA 3.8), where graduate work in Mergers & Acquisitions, Financial Modeling and reading financial statements filled in the corporate side of what I knew from trading. I sit for CFA Level I in November 2026.

I taught myself to build analysis tools with Python and SQL. The Rice University FinTech Bootcamp (Jun – Nov 2021) didn't make me a proficient coder on its own, but it gave me the foundation and taught me to learn from library documentation instead of memorizing code. By the time I started my MS in Finance at St. Thomas (Aug 2024 – May 2026), that background made my projects far more interesting. Our capstone assignment was to optimize a single portfolio; I figured it would be more interesting to build an app that could optimize any portfolio. That sent me down the path of extending it one feature at a time, testing each step, until it became a desktop analytics app with DCF valuation, Monte Carlo and 316 automated tests. After applying for a derivatives underwriting role, I built a counterparty credit simulator to learn what the job involves, ending each case in a written approve or decline memo. I have also built an SPX options income strategy, which I backtested, live-tested and paused when live results drifted from the backtest, and a crypto trading terminal with VaR backtests and crash replays. I also manage several financial accounts and recommend strategies for them at my family's medical practice.

I use frontier AI models (current GPT, Claude, Gemini and Grok-class models) every day and know how to use them properly: clear prompts, checking every output against the source data or a test, and building AI-assisted research and coding workflows. My projects were built that way. The AI speeds up the work, and I check what it produces before I rely on it.

For a trading desk, a markets or quant analytics team, or an M&A group, that means someone who learns a new method quickly, builds and checks the model, and explains the conclusion in writing.

Houston, TX · U.S. citizen