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Trading Strategy

Backtest SMA crossover and RSI reversal strategies on historical stock data.

Updated May 19, 2026
Search Tags:#risk assessment#chart generation#performance metrics#backtesting#trading strategy#stock analytics
One-click install
npx skills add https://github.com/sarkcesscrewpay/trading-intelligence-system --skill trading-strategy-sarkcesscrewpay
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Trading Strategy
Source: https://github.com/sarkcesscrewpay/trading-intelligence-system/tree/main/skills/trading_strategy
Command: npx skills add https://github.com/sarkcesscrewpay/trading-intelligence-system --skill trading-strategy-sarkcesscrewpay

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you evaluate whether a trading strategy would have worked on historical stock data, without manually tracking signals and outcomes.

Core Features & Use Cases

  • Backtesting on historical price data: Run predefined strategies over a chosen ticker and time period to simulate buys and sells.
  • Strategy library with common signal logic: Supports sma_crossover (Fast SMA crossing Slow SMA) and rsi_reversal (RSI oversold/overbought turning points).
  • Performance metrics and charting: Computes return-based and risk metrics (including Max Drawdown and Sharpe Ratio) and generates charts with entry/exit markers.

Quick Start

Run a backtest for the last 2 years on AAPL using the SMA crossover strategy and return JSON metrics with a visualization image.

Frequently Asked Questions about Trading Strategy

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I backtest a stock trading strategy on historical data?▼

The Skill evaluates stock trading strategies by applying entry and exit rules to historical price data, generating structured JSON results with performance metrics and trade lists.

What performance metrics can I generate when backtesting trading strategies?▼

Backtesting calculates return-based and risk metrics such as Max Drawdown and Sharpe Ratio to evaluate the historical performance of your chosen trading strategy.

Can I visualize stock entry and exit signals on a chart?▼

The backtesting process produces a generated chart artifact that visualizes historical price data alongside specific entry and exit trade markers.

Does the backtesting tool support RSI reversal and SMA crossover strategies?▼

The strategy library supports both sma_crossover and rsi_reversal signal logic, analyzing Fast SMA crossing Slow SMA and RSI oversold or overbought turning points.

What is the best way to evaluate risk assessment for stock analytics?▼

Evaluating risk assessment for stock analytics involves backtesting trading strategies to compute risk metrics like Max Drawdown and Sharpe Ratio from historical market data.

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