currently
- focus on trading options on Asian market indices
previously
- trained ML models to improve overnight exotic option pricing resulting in 10% increase in accuracy
- constructed dashboard to track estimated counterparty PnL per instrument
- analysed options market flows to inform main desk trading decisions
- comprehensive options theory education program: focus on pricing models, Greeks, and risk management
- project: statistical arbitrage strategy for trading futures on Hong Kong indices
- project: developed market-making autotrader for a simulated market with best performance in intern program
- trading: 5 weeks trading HSI index options using live market data in a simulated environment
- created locally-hosted dashboard for tracking performance metrics, saving +$100 per month vs. equivalent subscription service
- conducted pricing and turnover analysis for inventory management
education
Bachelor of Actuarial Studies / Bachelor of Economics
Major: Econometrics & Data Analytics
- competed against 35+ undergraduate and postgraduate teams
- developed a leading model to predict the conversion rate of travel insurance quotes
- identified key factors affecting conversion rate
- created dashboard featuring live data and model predictions, demonstrating real-world business case
- Highest Student Mark: FINS3666 (Trading and Market Making) - T3 2024
- Best Individual Speaker: Charity Pinnacle x I4C Charity Case Competition - T1 2022
projects
- Rust-based data pipeline on remote server handles ingestion, parsing, and cloud storage
- local ZeroMQ server handles real-time data streaming and model outputs
- comprehensive research base covering MFT strategies, realised volatility forecasting, and prediction markets
- Python-based backtesting framework with robust market execution
- automated data scraping from open-meteo.com for daily weather data across key agricultural regions
- performed exploratory analysis on the data to identify key trends and relationships
- created online interactive dashboard using Dash to visualise key findings
- utilised historical data to build models to predict a wide range of outcomes, including match results, goal differences, and player performance
- aim to expand to AFL markets by mid-2026 for mid-game comparison with live Betfair odds
about me
Hi, I'm Tom. I'm a recent graduate from UNSW where I studied Actuarial Studies and Economics,
majoring in Data Analytics and Econometrics. I have a strong background in using data to solve
problems and make data-driven decisions.
I remember being 15 and building a primitive model in Excel
for the ASX 20 which focussed on momentum-related strategies. Ever since then I've been chasing
how I can use math to beat the markets.
I also have a passion for data science and sport, and these intersected when in Year 12 I
created another Excel-based algorithm to predict the outcome of English Premier League matches
and compare my odds vs the betting markets.
I've come a long way since then, using my skills across Python, R, and numerous other languages
to tackle a range of projects and solve a variety of problems.
I'm always up for a chat, so feel free to reach out!
skills
- languages: python, r, sql
- machine learning: gradient boosting, neural networks, transformers
- dashboards: dash, plotly
- experience working with enterprise data platforms (databricks)