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Backtester
by
1477009639zw-blip
· GitHub ↗
· v1.0.0
· MIT-0
206
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Install in OpenClaw
/install backtester
Description
Professional backtesting framework for trading strategies. Tests SMA crossover, RSI, MACD, Bollinger Bands, and custom strategies on historical data. Generat...
README (SKILL.md)
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 — AI Trading Research Agent
Usage Guidance
This package is inconsistent: the README promises a full-featured backtester and automatic dependency installs, but the only code is a harmless stub that prints canned results. Before installing or using it: (1) don't trust its printed results for trading — they are not computed, they're hard-coded; (2) ask the author for the real implementation, an install mechanism (requirements.txt or pip command), and clear instructions for supplying data/API keys; (3) inspect any future code that performs network I/O or installs packages to verify endpoints and package sources; (4) if you need a real backtester, prefer well-known libraries or open-source projects with full source and reproducible installs. If you want to proceed cautiously, run the script offline in a sandbox to confirm behavior and avoid giving any credentials until a proper implementation is provided.
Capability Analysis
Type: OpenClaw Skill
Name: backtester
Version: 1.0.0
The skill bundle is a placeholder or mock implementation of a trading backtester. The 'backtest.py' script contains a simple argument parser and prints static, hardcoded results regardless of the input parameters, while 'SKILL.md' describes a more complex framework that is not actually implemented. There are no signs of data exfiltration, malicious execution, or prompt injection.
Capability Assessment
Purpose & Capability
The SKILL.md advertises a professional backtesting framework (OHLCV ingestion, multiple indicators, optimization, plotting, Yahoo/Tiger data). The only shipped code (backtest.py) prints a fixed, hard-coded backtest summary and implements none of those features. This is a large mismatch between claimed capability and actual implementation.
Instruction Scope
Runtime instructions are simply to run python3 backtest.py. The doc references CSV uploads, Yahoo Finance, and a Tiger API, but provides no concrete instructions for fetching data, supplying API keys, or where/how to upload CSVs. The SKILL.md also says dependencies are "auto-installed" but provides no install mechanism or commands. The instructions are therefore incomplete and ambiguous relative to the stated functionality.
Install Mechanism
There is no install spec (instruction-only), yet SKILL.md claims that pandas, numpy, matplotlib will be auto-installed. No mechanism (pip, requirements file, or package manager) is provided. The included script doesn't import any of those libraries, further highlighting inconsistency.
Credentials
The skill declares no required environment variables or credentials, but the documentation references using the Tiger API for professional data (which would normally require API keys). This lack of declared credentials or guidance for secure credential usage is inconsistent with the documented external data options. On the positive side, there are no unexpected env vars requested.
Persistence & Privilege
The skill does not request always-on presence and does not declare any privileged persistence. default agent invocation is allowed (normal). No files, config paths, or system-level changes are requested.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install backtester - After installation, invoke the skill by name or use
/backtester - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of Beta Backtester, a professional framework for validating trading strategies on historical data.
- Supports SMA Crossover, RSI, MACD, Bollinger Bands, Momentum, and custom strategies.
- Outputs comprehensive performance metrics: Sharpe, Sortino, Max Drawdown, Win Rate, and more.
- Generates equity curves, drawdown analysis, and allows side-by-side strategy comparison.
- Compatible with stock, crypto, and forex OHLCV data from Yahoo Finance, CSV, or API sources.
Metadata
Frequently Asked Questions
What is Backtester?
Professional backtesting framework for trading strategies. Tests SMA crossover, RSI, MACD, Bollinger Bands, and custom strategies on historical data. Generat... It is an AI Agent Skill for Claude Code / OpenClaw, with 206 downloads so far.
How do I install Backtester?
Run "/install backtester" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Backtester free?
Yes, Backtester is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Backtester support?
Backtester is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Backtester?
It is built and maintained by 1477009639zw-blip (@1477009639zw-blip); the current version is v1.0.0.
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