Economics & Mathematics student at Royal Holloway, University of London, graduating in June 2027. With a 74% Year 2 average, I combine quantitative development, independent research at Waverham Capital and a focused interest in energy markets and commodity trading.
I'm studying BSc Economics and Mathematics at Royal Holloway, University of London, on track for First Class Honours. My Year 2 average is 74%, including 88% in Microeconomics, 84% in Econometrics and 77% in Macroeconomics.
At Syntagma Labs, I work on institutional DeFi transaction data as a Quantitative Development Intern. Through Waverham Capital, my independent research publication, I write most weeks about macroeconomics, energy markets and geopolitical risk. My longer-term interests lie in energy research and commodity trading.
Alongside my studies, I support operations and client relations at Urban Housing, covering more than 100 residential properties and approximately £250,000 in average monthly rent. I also participate in monthly CME futures challenges and completed 12 front-office simulations through the AmplifyME Finance Accelerator.
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Classifying 437,000 institutional DeFi transactions to analyse platform exposure, flows and liquidity. Building Python data pipelines and reporting findings, with attention to records whose economic meaning requires interpretation.
Supporting policy research and drafting. Work includes an internal Gurmat-based case study and research into the UN Working Group's financial-sector work. This proposal remains internal; it has not yet been submitted to a UN body.
UK student financial survival tool built in React Native / Expo. Implements budgeting algorithms and data visualisation to surface actionable spending insights. Developed with budgeting and spending analysis at its centre.
Python, Alpaca API and PostgreSQL infrastructure combining market-news ingestion with mean-reversion research. Backtested over six months of historical data. Runs entirely on paper trading, with no live capital deployed.
Regular participation in monthly futures challenges across commodities, equities and rates, applying volatility-adjusted position sizing and risk management. Placed 25th globally in June 2025.
Hull Tactical S&P 500: Developing ensemble ML models (LightGBM, Ridge) to forecast weekly market direction. NFL Big Data Bowl 2026: LSTM trajectory prediction on player tracking data.
Founded in December 2025. Independent macro and energy research published most weeks on Substack, examining markets, geopolitical risk and commodities. Recent work includes “The Chip Selloff Meets the Hormuz Premium” and “The Price of Peace”.
Hover each card to see my key takeaway. These aren't just titles — they directly shape how I think about markets and risk.
The S&P broke its 200-day MA for the first time since May following tariff renewal. Friday was a record volume day. Here's what the market is telling us and why this week's data calendar is the most consequential we've had in months.
An Israeli operation against Iran sent oil markets into convulsion. The conventional crisis trade failed — buy gold, sell equities. Here's why, and what actually worked for the traders who got it right.
20% of global seaborne oil transits Hormuz daily. With Iran-Israel tensions escalating, the risk premium being priced by futures markets still looks too cheap. Here's the disruption scenario the market isn't modelling.
Graduating in June 2027. Interested in internship, research and early-career opportunities in energy markets, commodity trading and quantitative analysis. Happy to connect with researchers and market practitioners.