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Are you looking to enhance your trading strategies with the power of Python and machine learning? Then you need to check out PyBroker! This Python framework is designed for developing algorithmic trading strategies, with a focus on strategies that use machine learning. With PyBroker, you can easily create and fine-tune trading rules, build powerful models, and gain valuable insights into your strategy’s performance.

...It is now faster and much more professional thanks to the use of a C++ layer (used mostly for calculations) over the standard Basic layer (used mostly for the GUI interface). You can use astro indicators and functions from a library for astronomical calculations. You can get real time quotations thanks to Yahoo Finance, Alpha Vantage, Tiingo, Stooq, Finnhub and Twelvedata data sources.

fastquant is a Python library designed to simplify quantitative financial analysis and algorithmic trading strategy development. The project focuses on making backtesting accessible by providing a high-level interface that allows users to test investment strategies with only a few lines of code. It integrates historical market data sources and trading frameworks so that users can quickly build experiments without constructing complex data pipelines. The framework enables users to test common...