Agent skill

backtest-expert

Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill backtest-expert --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 8 KB
Bundled scripts: none
Path: skills/analysis/backtest-expert/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Backtest Expert Systematic approach to backtesting trading strategies based on professional methodology that prioritizes robustness over optimistic results. ## Core Philosophy **Goal**: Find strategies that "break the least", not strategies that "profit the most" on paper. **Principle**: Add friction, stress test assumptions, and see what survives. If a strategy holds up under pessimistic conditions, it's more likely to work in live trading. ## When to Use This Skill Use this skill when: - Developing or validating systematic trading strategies - Evaluating whether a trading idea is robust enough for live implementation - Troubleshooting why a backtest might be misleading - Learning proper backtesting methodology - Avoiding common pitfalls (curve-fitting, look-ahead bias, survivorship bias) - Assessing parameter sensitivity and regime dependence - Setting realistic expectations for slippage and execution costs ## Backtesting Workflow ### 1. State the Hypothesis Define the edge in one sentence. **Example**: "Stocks that gap up >3% on earnings and pull back to previous day's close within first hour provide mean-reversion opportunity." If you can't articulate the edge clearly, don't

What's inside
Steps it walks through
  1. Core Philosophy
  2. When to Use This Skill
  3. Backtesting Workflow
  4. 1. State the Hypothesis
  5. 2. Codify Rules with Zero Discretion
  6. 3. Run Initial Backtest
  7. 4. Stress Test the Strategy
  8. 5. Out-of-Sample Validation
  9. 6. Evaluate Results
  10. Key Testing Principles
  11. Punish the Strategy
  12. Seek Plateaus, Not Peaks
  13. Test All Cases, Not Cherry-Picked Examples
  14. Separate Idea Generation from Validation
Ships with 1 file
  • metadata.json
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About this skill
What does the backtest-expert skill do?

Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill backtest-expert --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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