Peiyan Zou
Quant developer and data engineer in London. MSc Computational Finance at King's College London (2026), BSc Computer Science at Nottingham. I build trading systems, market simulations and the data pipelines underneath them.
Selected work
CLMM-Bench: out-of-sample audit of Uniswap v3 LP strategies
MSc thesis. A reproducible backtesting framework over five Uniswap v3 pools showing that walk-forward-selected liquidity-provision configurations don't beat a never-rebalanced position — and that overfitting diagnostics change sign with transaction costs.
Agent-based prediction-market simulation of the BTC spot market
Discrete-time agent-based model of heterogeneous BTC traders reacting to Polymarket belief signals. Stronger herding pushes order imbalance to extremes and flips price dynamics from noisy to persistent one-sided regimes.
StockMARL: multi-agent reinforcement learning for trading
Published BSc research. A multi-agent RL trading system with a DQN agent learning alongside diverse rule-based agents — 12.23% money-weighted annual return and 15.9% cumulative return on unseen S&P 500 data with low trade volatility.