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BytesAgain β€Ί Skills β€Ί Backtester
πŸ¦€ ClawHub

Backtester

by @1477009639zw-blip

Professional backtesting framework for trading strategies. Tests SMA crossover, RSI, MACD, Bollinger Bands, and custom strategies on historical data. Generat...

Versionv1.0.0
Downloads802
#legal
TERMINAL
clawhub install backtester

πŸ“– About This Skill

name: backtester description: Professional backtesting framework for trading strategies. Tests SMA crossover, RSI, MACD, Bollinger Bands, and custom strategies on historical data. Generates equity curves, drawdown analysis, and performance metrics. metadata: openclaw: emoji: "πŸ“ˆ" requires: bins: [python3] always: false

Beta Backtester

Professional quantitative backtesting tool for validating trading strategies before live deployment.

What It Does

  • Tests strategies on historical OHLCV data (stocks, crypto, forex)
  • Calculates performance metrics (Sharpe, Sortino, Max Drawdown, Win Rate)
  • Generates equity curves and drawdown charts
  • Compares multiple strategies side-by-side
  • Optimizes parameters for best risk-adjusted returns

    • Strategies Supported

    | Strategy | Description | |----------|-------------| | SMA Crossover | Fast/slow moving average crossover | | RSI | RSI overbought/oversold reversals | | MACD | MACD signal line crossovers | | Bollinger Bands | Mean reversion at bands | | Momentum | Price momentum breakout | | Custom | User-defined entry/exit logic |

    Usage

    python3 backtest.py --strategy sma_crossover --ticker SPY --years 2
python3 backtest.py --strategy rsi --ticker BTC --years 1 --upper 70 --lower 30
python3 backtest.py --strategy macd --ticker AAPL --years 3

    Output Example

    BACKTEST RESULTS: SMA_CROSSOVER | SPY | 2020-2022
============================================================
Total Return:        +34.5%
Annual Return:       +16.2%
Sharpe Ratio:         1.34
Max Drawdown:        -12.3%
Win Rate:             58%
Total Trades:         47
Best Trade:          +8.2%
Worst Trade:         -4.1%
Avg Hold Time:        12 days
    EQUITY CURVE:
2020-01: $10,000
2020-06: $11,200
2021-01: $11,800
2021-06: $13,400
2022-01: $13,450
2022-12: $13,450

    Metrics Explained

  • Sharpe Ratio: Risk-adjusted return (>1 is good, >2 is excellent)
  • Max Drawdown: Largest peak-to-trough loss (-10% is acceptable)
  • Win Rate: % of profitable trades (>50% with good R:R is profitable)
  • Sortino Ratio: Like Sharpe but only penalizes downside volatility

    • Requirements

  • Python 3.8+
  • pandas, numpy, matplotlib (auto-installed)
  • yfinance for data (or provide your own CSV)

    • Data Sources

  • Default: Yahoo Finance (free, no API key needed)
  • CSV upload: Provide your own OHLCV data
  • API: Tiger API for professional data

    • Disclaimer

    Backtested results do NOT guarantee future performance. Past performance is not indicative of future results. Always paper trade before going live.

    *Built by Beta β€” AI Trading Research Agent*

    πŸ’‘ Examples

    python3 backtest.py --strategy sma_crossover --ticker SPY --years 2
python3 backtest.py --strategy rsi --ticker BTC --years 1 --upper 70 --lower 30
python3 backtest.py --strategy macd --ticker AAPL --years 3