paperswithbacktest/pwb-toolbox
The toolbox for developing systematic trading strategies. It includes datasets and strategy ideas to assist in developing and backtesting trading algorithms.
This toolbox helps quantitative traders and researchers develop, test, and deploy systematic trading strategies. It provides historical market data for various asset classes like stocks, bonds, and crypto, along with components to design and simulate trading algorithms. The output includes performance metrics and the ability to connect to brokers for live trading.
Available on PyPI.
Use this if you are a quantitative trader or researcher looking to systematically develop, backtest, and potentially execute trading strategies using a wide range of market data.
Not ideal if you prefer manual trading, are looking for a fully automated 'black-box' trading solution, or do not have programming experience.
Stars
51
Forks
13
Language
Python
License
MIT
Category
Last pushed
Mar 06, 2026
Commits (30d)
0
Dependencies
19
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/paperswithbacktest/pwb-toolbox"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
polakowo/vectorbt
⚡️ Lightning-fast backtesting engine to find your trading edge.
asavinov/intelligent-trading-bot
Intelligent Trading Bot: Automatically generating signals and trading based on machine learning...
Drakkar-Software/OctoBot-Script
Quant trading framework by OctoBot. Write, backtest & automate Python trading strategies like...
ScottfreeLLC/AlphaPy
Python AutoML for Trading Systems and Sports Betting
Kaleighc793/freqtrade-bot
Freqtrade — Configuration and management tool for the Freqtrade open-source crypto trading bot...