Showing 4 open source projects for "model-builder"

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    PowerTrader_AI

    PowerTrader_AI

    Fully automated crypto trading powered by a custom price prediction AI

    PowerTrader_AI is a fully open-source, automated cryptocurrency trading bot that combines a custom price prediction AI with a structured and tiered dollar-cost averaging (DCA) strategy to make real trading decisions on behalf of users. It continuously analyzes market data to forecast high and low price levels across multiple timeframes, using those predictions to determine when to open, scale into, or close positions automatically, which aims to take emotion out of trading and enforce...
    Downloads: 3 This Week
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    Nothing Ever Happens

    Nothing Ever Happens

    Focused async Python bot for Polymarket

    Nothing Ever Happens is an experimental open-source trading bot designed for the Polymarket platform that implements a deliberately simple and unconventional strategy: automatically buying “No” positions across non-sports binary prediction markets. The project is built in Python using asynchronous architecture, allowing it to monitor markets, evaluate opportunities, and execute trades continuously with minimal latency. Its core concept is based on statistical observations that a majority of...
    Downloads: 0 This Week
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  • 3
    Blankly

    Blankly

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

    ...Blankly is the first framework to enable developers to backtest, paper trade, and go live across exchanges without modifying a single line of trading logic on stocks, crypto, and forex. Every model needs to figure out how to buy and sell. We make it super easy for you so you can focus on building better trading algos. Your models can run on any platform, and on any supported exchange. We make that as easy as just changing one line of code.
    Downloads: 0 This Week
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  • 4
    abu

    abu

    Abu quantitative trading system (stocks, options, futures, bitcoin)

    Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. The above system combines hundreds of seed quantitative models, such as financial time series loss model, deep pattern quality assessment model, long and short pattern combination evaluation model, long pattern stop-loss strategy model, short pattern covering strategy model, big data K-line pattern Historical portfolio fitting model, trading position mentality model, dopamine quantification model, inertial residual resistance support model, long-short swap revenge probability model, strong and weak confrontation model, trend angle change rate model, etc.
    Downloads: 0 This Week
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