nkaz001/hftbacktest
Free, open source, a high frequency trading and market making backtesting and trading bot, which accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books(Level-2 and Level-3), with real-world crypto trading examples for Binance and Bybit
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
No releases in the last 90 days; the most recent was 326 days ago, with 22 contributors on GitHub.
Peaked at #41 in the weekly ranking the week of Mar 29, its best in the past year.
Use Cases & Benefits
- Provides a high-frequency trading and market making backtesting and live trading framework using full tick data and order book reconstruction.
- Enables highly accurate simulation by accounting for order queue positions, feed and order latencies, and supports multi-asset and multi-exchange models.
- Use for developing and validating high-frequency trading strategies with realistic order fill and latency modeling in crypto markets.
- Use for prototyping and deploying live trading bots on Binance Futures and Bybit using the same algorithm code as backtesting.
- Use for researching market making algorithms that leverage Level-2 and Level-3 order book data and queue position dynamics.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
- Code of conduct: present
Watch-outs
- No commits in the last six months (last push Dec 2025).
General guidance from repository metadata, not legal advice. How we score
From the README
This framework is designed for developing high frequency trading and market making strategies. It focuses on accounting for both feed and order latencies, as well as the order queue position for order fill simulation. The framework aims to provide more accurate market replay-based backtesting, based on full order book and trade tick feed data.
See
full document here <https://hftbacktest.readthedocs.io/>_.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+684 stars over 83 days across 8 snapshot days; best day +6 on Oct 5.
Forks
955+105
Open issues
23+7
Compared with peers in Automation
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| vercel-labs/agent-desktop | 17.0K | +13.3K | 33 | today |
| D4Vinci/Scrapling | 98.1K | +6.9K | 65 | 1 day ago |
| Panniantong/Agent-Reach | 109.3K | +3.0K | 60 | 4 days ago |
| lexmount/moli | 22.7K | +1.2K | 55 | 2 days ago |
| superplanehq/superplane | 8.8K | +435 | 60 | 7 days ago |
| nkaz001/hftbacktest | 5.0K | — | 25 | 326 days ago |
| Category median | 22.7K | +3.0K | 60 | — |
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