Algorithmic Trading in Python with Machine Learning Are you looking to enhance your trading strategies with the power of Python and machine learning? PyBroker is a Python framework 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. Key Features A super-fast backtesting engine built in NumPy and accelerated with Numba. Easy creation of trading rules and models for executing across multiple instruments. Integration of trading signals across multiple time intervals, including daily, weekly, and monthly. Access to historical data from Alpaca, Yahoo Finance, AKShare, or from your own data provider. Model training and backtesting using Walkforward Analysis, which simulates how the strategy would perform during actual trading. Reliable trading metrics that use randomized bootstrapping) to provide more accurate results. Parameter optimization with Optuna to select the best strategy para

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