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ramseshk b59dcc3629 Initial project scaffold: five quant strategies for Hyperliquid Testnet

Set up the directory structure and wrote placeholder logic for:

- Order Book Imbalance: trades on L2 bid/ask skew
- Iceberg/TWAP detection: follows whale accumulation patterns
- Funding rate arbitrage: delta-neutral carry on perp funding
- Pairs trading: BTC/ETH spread mean reversion
- Avellaneda-Stoikov market making: optimal bid/ask quoting

Also added shared risk manager, portfolio tracker, and a plain-language strategy walkthrough in docs/.

2026-08-03 11:12:20 +00:00

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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

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