- Trade Engine
- Stock Analysis Engine
- Closing Thoughts
This article describes lesser-known python libraries/scripts that can be used for backtesting. Here is a list of the most popular backtesting libraries that are excluded from the scope of this article.
Bt framework allows you to easily create strategies that mix and match different
Algos. It aims to foster the creation of easily testable, re-usable and flexible blocks of strategy logic to facilitate the rapid development of complex trading strategies.
The goal: to save quants from re-inventing the wheel and let them focus on the important part of the job - strategy development.
To recognise potential of this tool look at the quick example provided by authors The one of the interesting things that this library offers is tree structure of strategies - support for creative combining strategies. The other reading focuses of composing optimal portfolio: Flexible Backtesting with BT. Introducing bt — the open-sourced… | by Richard L | Medium
AutoTrader - A Python-based development platform for automated trading systems - from backtesting to optimization to live-trading. AutoTrader is a Python-based platform intended to help in the development, optimization, and deployment of automated trading systems.
Blueshift is to some extend free but not open source. You can research your ideas, backtest them, and take your strategies live with a broker of your choice on Blueshift. Blueshift helps you turn your ideas in to trading strategies. Research and backtesting on the platform are free. Live strategy deployment is also free for a limited period.
DeepCrypto Rapid Backtesting via Numba Simple & Vectorized trading strategy maker built-in live trading features.
TradingGym is a toolkit for training and backtesting reinforcement learning algorithms. This was inspired by OpenAI Gym and imitated the framework form. Not only trading env but also has backtesting and in the future will implement real-time trading env with Interactive Broker API and so on. This training environment originally designs for tick-data, but also supports for OHLC data format.
vartests is a Python library to perform some statistical tests to evaluate Value at Risk (VaR) Models.
backtesting-for-cryptocurrency-trading - you can use this simple crypto backtesting script to ensure your trading strategy is successful. Minimal setup required and works well with static TP and SL strategies. Trailing Stop Loss could improve profitability if added.
Trade Engine - a library for demo trading or backtest and forward test simulation.
Epymetheus is a multi-asset backtesting framework. It features an intuitive user API that lets analysts try out their trade strategies right away.
TradzQAI - Trading environment for RL agents, backtesting and training.
Stock Analysis Engine
Stock Analysis Engine. Build and tune investment algorithms for use with artificial intelligence (deep neural networks) with a distributed stack for running backtests using live pricing data on publicly traded companies with automated data feeds from: IEX Cloud, Tradier and FinViz (includes: pricing, options, news, dividends, daily, intraday, screeners, statistics, financials, earnings, and more).
BTGym. Scalable event-driven RL-friendly backtesting library. Build on top of Backtrader with OpenAI Gym environment API.
BakTst_Org is a prototype of the backtesting system used for BTC quantitative trading.
Stock-Portfolio-Backtester Efficient way to backtest optimized portfolio allocations for proper hedging techniques.
QSTrader is a free Python-based open-source modular schedule-driven backtesting framework for long-short equities and ETF-based systematic trading strategies.
I would like to look closer at Epymetheus