LEE Y.

I help hedge funds, proprietary trading desks, and advanced fintech teams design and build institutional-grade trading and research systems. My focus is not on toy backtests, but on execution-ready, decision-aware infrastructure that operates under real market conditions. I am a senior quantitative developer, algorithmic researcher, and strategy engineer with experience spanning high-frequency trading, systematic alpha research, execution systems, and institutional investment workflows. My work covers the full lifecycle of trading and investment systems, from market microstructure and low-latency execution, to top-down research frameworks that connect macro regimes, sector dynamics, security selection, and portfolio construction. Beyond implementation, I specialize in formalizing how investment teams think. I translate discretionary research and intuition into structured, explainable, and reproducible decision systems suitable for portfolio managers, investment committees, and client reporting. What I Do in Practice ✔️ Design and build execution-ready trading systems including HFT, statistical arbitrage, and market making ✔️ Architect institutional research frameworks linking macro, sector, security, and portfolio layers ✔️ Build strategy-aware infrastructure that enforces risk, explainability, and confidence calibration ✔️ Integrate machine learning and language models as decision support, not black-box signal generators ✔️ Deliver systems intended for live trading, capital deployment, and institutional scrutiny 💡 Core Expertise A. Trading and Execution Systems ✔️ High-Frequency Trading: microstructure modeling, latency optimization, execution efficiency ✔️ Statistical Arbitrage and Market Making: spread modeling, liquidity provisioning ✔️ Smart Order Routing and Trading Aggregators: multi-venue execution, real-time risk and connectivity B. Institutional Research and Decision Architecture ✔️ Top-down investment framework design across macro, sector, security, and portfolio layers ✔️ Research orchestration, dependency tracking, and explainable decision workflows ✔️ Converting discretionary research into auditable, reusable systems used by portfolio managers C. Quantitative Methods and AI ✔️ AI-augmented research systems using language models for structuring, synthesis, and scenario analysis ✔️ Machine learning for predictive modeling, anomaly detection, and regime analysis ✔️ Robust validation including walk-forward testing, stress testing, and stability analysis D. Crypto and Digital Asset Trading ✔️ CEX and DEX arbitrage, perpetuals, options, and AMMs ✔️ DeFi integrations and smart-contract-aware strategies 💻 Platforms & Infrastructure : Traditional Trading: MetaTrader 4/5 (MQL4/MQL5), NinjaTrader, Sierra Chart, TradingView (Pine Script), QuantConnect, Interactive Brokers, ThinkOrSwim Crypto Trading: Binance, Bybit, BitMEX, OKX, Deribit, dYdX, Uniswap, Sushiswap, GMX Low-Latency & HFT Development: C++, C#, Rust, Python, FPGA-based strategies Infrastructure & Pipelines: Kafka, Redis, TimescaleDB, PostgreSQL, Liquibase, Docker, Kubernetes AI & ML Toolkits: TensorFlow, PyTorch, Scikit-learn, OpenAI API, Pandas 💡 My Approach to Machine Learning and AI in Trading Financial markets are non-stationary, adversarial, and regime-driven. Machine learning and AI can add value, but only when applied with discipline and market awareness. I emphasize: - Alpha and economic logic first, machine learning second - Robust validation through walk-forward analysis and stress testing - Execution-aware design rather than theoretical backtests - AI as a tool for structuring reasoning and research, not for mining noise The same discipline applies to research systems. Strong investment outcomes come from clear assumptions, controlled uncertainty, and explainable logic rather than opaque models. 💬 My Philosophy on Pricing & Partnerships Exceptional value lies not just in technical ability, but in deep market understanding and execution precision. I focus on delivering results-driven systems, not just theoretical models. I welcome long-term collaborations with hedge funds, prop desks, and fintech startups who value strategic edge, not just code.