ramseshk
b59dcc3629
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/.
60 lines
1.8 KiB
Markdown
60 lines
1.8 KiB
Markdown
# FTDT Quant Lab — Quantitative Trading Strategies
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A collection of quantitative trading strategies running on
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**Hyperliquid Testnet** via **Nautilus Trader**. Built as part of
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my professional portfolio to demonstrate algorithmic trading,
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market microstructure, and risk management skills.
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## What's inside
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Five strategies, from simple to advanced:
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| # | Strategy | Concept |
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| 1 | Order Book Imbalance | Trades on L2 bid/ask pressure |
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| 2 | Iceberg / TWAP Detection | Follows whale accumulation patterns |
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| 3 | Funding Rate Arbitrage | Delta-neutral carry trade |
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| 4 | Pairs Trading (BTC/ETH) | Cointegration-based stat arb |
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| 5 | Avellaneda-Stoikov Market Making | Stochastic optimal control |
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All strategies share a common risk manager and portfolio tracker.
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## Quick start
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```bash
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# Install dependencies
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pip install -r requirements.txt
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# Set your Hyperliquid testnet key
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export HYPERLIQUID_TESTNET_PK=0x...
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# Run live (testnet only)
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python live/node.py
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```
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## Project layout
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```
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ftdt-quant-lab/
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├── config/ # Per-strategy YAML configuration
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├── strategies/ # Strategy implementations
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├── common/ # Risk manager, portfolio tracker, metrics
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├── backtests/ # Historical backtest runners
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├── live/ # Live trading node (Hyperliquid Testnet)
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├── docs/ # Documentation and strategy writeups
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└── notebooks/ # Analysis notebooks
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```
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## Strategy details
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See `docs/STRATEGIES.md` for a walkthrough of each strategy.
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## Risk warning
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This is **testnet only**. These strategies are educational — they
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are not financial advice and have no alpha guarantee. Never run
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them on mainnet without thorough backtesting and your own due diligence.
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---
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Built by [Ramses Echikh](https://git.ftdt.io/rams) · Part of my quant trading portfolio
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