stock-bot
Unverified ML strategy on Indices by ryantcullen. BotFinder score 18 out of 100.
An open-source Python backtesting engine for designing and evaluating daily stock trading algorithms against real historical market data.
Source: github
BotFinder analysis pending.
stock-bot
StockBot An open-source Python backtesting engine for designing and evaluating daily stock trading algorithms against real historical market data. Features - Fetches up to 10 years of historical price data via the Yahoo Finance API - Computes 10, 50, 100, and 200-day moving averages with derived indicators (slope, concavity, crossover detection) - Position sizing via the Kelly Criterion - Compares algorithm performance against a buy-and-hold baseline - Visualizes results with matplotlib (price chart, moving average overlays, buy/sell markers) Installation Usage Enter any stock ticker (e.g. AAPL, TSLA, IBM) to run the backtest. Type exit or Ctrl+C to quit. Example Output Designing Your Own Algorithm All trading logic lives in the Decide() method of the Portfolio class. To implement your own strategy, modify three parameters based on the moving average data: The method receives four MovingAverage objects (f1 through f4), each with attributes you can use to build your logic: | Attribute | Description | |-----------|-------------| | percentdifference | How far the current price deviates
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How the score has moved
Recalculated at each data collection. Transparency means showing the bad weeks too.
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Alerts on changes: coming soon
Prop-firm compatibility not provided.
Open-source maintainer on GitHub.
Data-completeness & trust index (not a profitability rating)