0b8943c926fbc0bb18597aeacee822b85b1fa456
New: strategies/persistence.py Tables: strategies_snap, trade_log, equity_history, fill_tracker Auto-creates on first use, batches inserts per tick Fix: seen_fills loads from PG (not 2000 API fills) Before: every restart loaded all 2000 fills from API into seen_fills, blocking new fills with matching TIDs for ~20min After: only loads last 100 from API + full history from PG. New fills saved to PG immediately - survives restarts. Live node integration: - write_metrics() → save_strategies() every tick - On fill → save_trade() to trade_log - On fill → TID saved to fill_tracker for cross-restart dedup
FTDT Quant Lab — Quantitative Trading Strategies
A collection of quantitative trading strategies running on Hyperliquid Testnet via Nautilus Trader. Built as part of my professional portfolio to demonstrate algorithmic trading, market microstructure, and risk management skills.
What's inside
Five strategies, from simple to advanced:
| # | Strategy | Concept |
|---|---|---|
| 1 | Order Book Imbalance | Trades on L2 bid/ask pressure |
| 2 | Iceberg / TWAP Detection | Follows whale accumulation patterns |
| 3 | Funding Rate Arbitrage | Delta-neutral carry trade |
| 4 | Pairs Trading (BTC/ETH) | Cointegration-based stat arb |
| 5 | Avellaneda-Stoikov Market Making | Stochastic optimal control |
All strategies share a common risk manager and portfolio tracker.
Quick start
# Install dependencies
pip install -r requirements.txt
# Set your Hyperliquid testnet key
export HYPERLIQUID_TESTNET_PK=0x...
# Run live (testnet only)
python live/node.py
Project layout
ftdt-quant-lab/
├── config/ # Per-strategy YAML configuration
├── strategies/ # Strategy implementations
├── common/ # Risk manager, portfolio tracker, metrics
├── backtests/ # Historical backtest runners
├── live/ # Live trading node (Hyperliquid Testnet)
├── docs/ # Documentation and strategy writeups
└── notebooks/ # Analysis notebooks
Strategy details
See docs/STRATEGIES.md for a walkthrough of each strategy.
Risk warning
This is testnet only. These strategies are educational — they are not financial advice and have no alpha guarantee. Never run them on mainnet without thorough backtesting and your own due diligence.
Built by Ramses Echikh · Part of my quant trading portfolio
Description
Quantitative trading lab — Nautilus Trader strategies on Hyperliquid Testnet. Part of my professional portfolio.
Languages
Python
60.7%
TypeScript
19.8%
HTML
18.8%
CSS
0.4%
JavaScript
0.3%