First-year at Duke University, Class of 2030, studying Computer Science and Economics.

I got interested in markets before I got interested in code. Trading a DECA portfolio to the top 4% of 5,000 teams taught me that most of an investment thesis is unfalsifiable hand-waving, and that the interesting question is not what do you think but what would prove you wrong. Everything I have built since is an attempt to answer that question with data.

That means equity research where every pitch is timestamped in git and scored against the S&P 500 with no retroactive edits; a Hidden Markov Model that classifies the macro cycle into four regimes off 35 years of FRED data; and an earnings-call model that asks whether a company sounded better or worse than its economic climate would predict. The engineering exists to make the research falsifiable, not the other way around.

Each project starts as a research question and ends as a working pipeline, with the data to back it up.