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anthony-hn-le/README.md
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Open to Work Denison LSE Portfolio


๐Ÿ‘‹ About Me

I'm an Applied Mathematics & Financial Economics student at Denison University (minoring in Computer Science), currently on a year abroad at the London School of Economics. I like building things that sit at the intersection of rigorous math and live markets โ€” from-scratch pricing engines, matching engines, and forecasting pipelines, not just notebooks.

Most recently: engineered a walk-forward volatility-forecasting pipeline across 18 equities and 11 models (GARCH โ†’ LSTM) as a Denison Economics research fellow, and built a C++ limit order book matching engine compiled to WebAssembly with a differential fuzzer proving correctness across 200k+ operations. A few results along the way: Top 27 in the CME Global University Trading Challenge, Top 200 (US) in IMC Prosperity 4, and 2x National Finalist in Vietnam's Math Olympiad.

I'm currently looking for 2026 quant trading / quant research internships and full-time roles โ€” always happy to talk markets, models, or code.


๐Ÿ› ๏ธ Skills & Tools

Languages

Python C++ R TypeScript SQL LaTeX Stata

Quant & Finance

Black-Scholes Monte Carlo Stochastic Calculus Options Pricing Market Microstructure Portfolio Theory

Frameworks & Libraries

Next.js React NumPy Pandas PyTorch scikit-learn Plotly Streamlit

Tools & Platforms

Git WebAssembly Vercel Supabase Vitest

Math & Statistics

Real Analysis Linear Algebra Time Series Probability Theory Optimization


๐Ÿš€ Current Projects & Focus

  • ๐ŸŽ“ On year abroad at LSE (Fall 2026 โ€“ Spring 2027) โ€” coursework in Financial Statistics, Risk Management & Modelling, and Computational Methods in Financial Mathematics.
  • ๐Ÿ“Š Equity Volatility Forecasting Research โ€” 10-week Denison Economics project testing ML vs. econometric models (GARCH, HAR-RV, XGBoost, LSTM) for equity vol forecasting; pending faculty sign-off on the final manuscript.
  • ๐Ÿ“ˆ Limit Order Book Simulator โ€” a from-scratch C++ matching engine (price-time priority, O(1)-average cancel) compiled to WebAssembly, with a live browser demo and a differential fuzzer for correctness.
  • ๐ŸŽฒ Trader Titan โ€” a market-making trivia game against algorithmic bots, built to explore spread-quoting and inventory risk in a game-design context.
  • ๐ŸŒ‹ Implied Volatility Surface โ€” live options-chain data rendered as an interactive 3D IV surface via Black-Scholes inversion.
  • ๐Ÿงฎ Options Greeks Sandbox โ€” BSM + binomial-tree (Cox-Ross-Rubinstein) calculator comparing European vs. American exercise, with live Greeks.
  • ๐ŸŒ All of the above are showcased and kept up to date on my quant portfolio site.

๐Ÿ“ซ Connect with Me

LinkedIn Email Portfolio

"Markets are the largest distributed computing systems ever built."

Pinned Loading

  1. Implied-Volatility-Surface Implied-Volatility-Surface Public

    A Python-based web app that visualizes the implied volatility surface for equity options using real-time data from Yahoo Finance. The app computes implied volatilities with the Black-Scholes model โ€ฆ

    TypeScript 1

  2. Limit-Order-Book-Simulator Limit-Order-Book-Simulator Public

    A from-scratch C++ limit order book with price-time priority matching, compiled to WebAssembly for a live browser demo.

    TypeScript

  3. VIX-ETF-Returns VIX-ETF-Returns Public

    A fully reproducible econometrics project analyzing how market sentiment, proxied by the VIX, affects returns across major equity ETFs using 20 years of weekly data, fixed-effects panel regressionsโ€ฆ

    TeX 2 1

  4. agricultural-futures-time-series agricultural-futures-time-series Public

    Time series analysis (ARIMA, GARCH, multivariate GARCH) of daily U.S. wheat, corn, and soybean futures prices, 2000-2024

    HTML

  5. Volatility-Research Volatility-Research Public

    Machine learning vs. traditional econometrics for equity volatility forecasting โ€” GARCH family, Random Forest, XGBoost, LSTM, and hybrids evaluated on statistical accuracy and portfolio economic vaโ€ฆ

    Jupyter Notebook