gavindiaz/awesome-quant
1
0
Fork 0
mirror of https://github.com/wilsonfreitas/awesome-quant.git synced 2026-07-27 20:07:50 +00:00
Code Issues Packages Projects Releases Wiki Activity

Add DeepAlpha to Trading & Backtesting section (#366)

Browse Source 
Add DeepAlpha - AI crypto trading bot for Bybit
This commit is contained in:
DeepAlpha
2026-04-25 22:16:18 +02:00
committed by GitHub
parent 8087e9ee38
commit a27e2660fc
1 changed files with 1 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+1
View File
@@ -163,6 +163,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [TradeSight](https://github.com/rmbell09-lang/tradesight) - `Python` - Self-hosted AI trading platform with strategy evolution, technical analysis, backtesting, and paper trading via Alpaca.
- [Orallexa](https://github.com/alex-jb/orallexa-ai-trading-agent) - `Python` - AI trading operating system with 9 ML models (RF, XGBoost, EMAformer, MOIRAI-2, Chronos-2, DDPM, PPO RL, GNN, LR) ranked by Sharpe ratio, Claude AI synthesis with dual-tier routing (~$0.003/analysis), real-time Next.js dashboard, Alpaca paper trading, and 277 automated tests.
- [Vibe-Trading](https://github.com/HKUDS/Vibe-Trading) - `Python` - Natural-language multi-agent finance research agent with 29 swarm presets, 70 skills, and 28 auto-discovered tools; 7 backtest engines covering A-shares/US/Crypto/Futures/Forex/Options plus a cross-market CompositeEngine with shared capital pool; 5-source auto-fallback data layer (tushare/okx/yfinance/akshare/ccxt); 17-tool MCP server; includes trade-journal behavioral diagnostics for 同花顺/东财/富途 exports.
- [DeepAlpha](https://deepalphabot.com) - `Python` - AI crypto trading bot for Bybit with 70.9% walk-forward validated accuracy on out-of-sample data, LightGBM + XGBoost ensemble with 72 ML features. [GitHub](https://github.com/stefanoviana/deepalpha)
- [the0](https://github.com/alexanderwanyoike/the0) - `Python` - Self-hosted execution engine for algorithmic trading bots. Write strategies in Python, TypeScript, Rust, C++, C#, Scala, or Haskell and deploy with one command. Each bot runs in an isolated container with scheduled or streaming execution.
- [Investing algorithm framework](https://github.com/coding-kitties/investing-algorithm-framework) - `Python` - Framework for developing, backtesting, and deploying automated trading algorithms.
- [Lumibot](https://github.com/Lumiwealth/lumibot) - `Python` - Algorithmic trading framework where the same code runs for backtesting and live trading across stocks, options, crypto, futures, and forex with multiple brokers including Alpaca, Interactive Brokers, Tradier, and Schwab.