pyalgotrade
bt
| pyalgotrade | bt | |
|---|---|---|
| 2 | 5 | |
| 4,179 | 2,164 | |
| - | - | |
| 0.0 | 6.8 | |
| 10 months ago | 7 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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pyalgotrade
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Open source backtesting software
https://github.com/gbeced/pyalgotrade (event-driven)
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Best Backtesting Libraries (Python)
pyalgotrade – PyAlgoTrade is an event driven algorithmic trading Python library. Although the initial focus was on backtesting, paper trading is now possible
bt
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Best Backtesting Libraries (Python)
bt – bt is a flexible backtesting framework for Python used to test quantitative trading strategies.
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Are there any ready solutions for backtesting portfolio with daily or more frequent rebalancing?
Here is link number 1 - Previous text "Bt"
- What open source frameworks should i be considering for hobby algo trading?
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How do I run 100 algos live?
A better way would be to create a master strategy that manages 100 other strategies, each with $10 a pop. The bt backtesting framework was designed to support this. That way you can manage your portfolio from one account, but also use multiple strategies. The master strategy just handles fund allocation, and rebalancing if necessary.
What are some alternatives?
backtrader - Python Backtesting library for trading strategies [Moved to: https://github.com/mementum/backtrader]
PyPortfolioOpt - Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
zipline - Zipline, a Pythonic Algorithmic Trading Library
pybacktest - Vectorized backtesting framework in Python / pandas, designed to make your backtesting easier — compact, simple and fast
awesome-quant - A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
PyThalesians - Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians)
algobroker - Algo execution engine
pandas_talib - A Python Pandas implementation of technical analysis indicators