ramseshk
b47948b604
Server: recalc endpoint now checks HISTORICAL_DIR as fallback when file not found in BACKTEST_DIR. Previously historical backtests returned "not found" on recalc. Frontend: renderBTDetail now accepts pnl_net/pnl_net_pct from recalc response (the endpoint returns pnl_net not pnl). Verified: VIP 0 → VIP 6 on OBI historical backtest changes net PnL from 54.31% to 66.57% with fees dropping $18.10 → $5.85.
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