Showing 3 open source projects for "optimize"

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    JesseAi

    JesseAi

    Advanced AI-Powered Python Crypto Trading Bot 2026 - Free Backtesting

    Jesse Bot: Advanced AI-Powered Python Best Crypto Trading Bot & Framework (2026) Jesse Bot — free open-source Python crypto trading bot & robust framework for cryptocurrency markets. Build, backtest, AI-optimize, and execute precise automated strategies with zero look-ahead bias. Use JesseGPT — built-in AI assistant — to write, debug, and refine strategies effortlessly, even as a beginner. Secure live trading on Binance, Bybit & major exchanges, full risk management, leverage/futures support, and pro analytics. One of the best open-source alternatives to Freqtrade with genuine AI edge: privacy-first self-hosting (no shared API keys), multi-timeframe/symbol backtesting, custom indicators, ML-enhanced signals. ...
    Downloads: 1 This Week
    Last Update:
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  • 2
    Blankly

    Blankly

    Easily build, backtest and deploy your algo in just a few lines

    ​Blankly is a live trading engine, backtest runner and development framework wrapped into one powerful open-source package. Models can be instantly backtested, paper traded, sandbox tested and run live by simply changing a single line. We built blankly for every type of quant including training & running ML models in the same environment, cross-exchange/cross-symbol arbitrage, and even long/short positions on stocks (all with built-in WebSockets). Blankly is the first framework to enable...
    Downloads: 0 This Week
    Last Update:
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  • 3
    Algobot

    Algobot

    Cryptocurrency trading bot with a graphical user interface

    Cryptocurrency trading bot that allows users to create strategies and then backtest, optimize, simulate, or run live bots using them. Telegram integration has been added to support easier and remote trading. Please note that Algobot requires TA-LIB. You can view instructions on how to download TA-LIB. For Windows users, it's best to download the .whl package for your Python install and pip install it. For Linux and MacOS users, there's excellent documentation available.
    Downloads: 2 This Week
    Last Update:
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