I'm drawn to the questions investors actually face: when does an implied vol premium disappear? What does a Fed meeting signal about the vol surface across rate regimes? How does options market microstructure translate into risk for an intraday position? I study Accounting and Finance at LSE and run each study from end to end, from institutional data pull through to a concrete published finding.

Outside of finance, you'll find me on a tennis court, behind a guitar, or on a mountain somewhere pretending I know what I'm doing on a snowboard.

Every study on this site starts with a question rather than a conclusion. I run the full backtest across all available data and let the numbers determine the finding. No cherry-picked sample periods, no buried caveats, no results trimmed to look clean.

Unprofitable strategies are reported as unprofitable. If a win rate looks impressive but the sample is small, that is stated clearly. If a strategy only works in one market regime, that is the finding, not a footnote.

The goal is research a professional would trust, not research designed to look impressive.

All data is sourced through Wharton Research Data Services (WRDS), the same infrastructure used by institutional asset managers, quantitative hedge funds, and academic researchers worldwide. Databases vary by study: OptionMetrics IvyDB for implied volatility surfaces, TAQ for intraday trade-and-quote data, CRSP for equity prices, Compustat for fundamentals, IBES for earnings dates, and FRED for macro series.

The full pipeline, from raw data pull to published interactive report, is built and maintained independently. All code is published on GitHub.

Every study is produced end-to-end: institutional data pull, statistical analysis, and interactive published output, without commercial software or third-party platforms.