Backtesting Analysis
Comprehensive guidance for interpreting backtest results and detecting overfitting (project)
npx skills add majiayu000/claude-skill-registry --skill backtesting-analysis-derekcrosslu-claude-code-explore --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Backtesting Analysis Skill **Purpose**: Interpret backtest results, understand performance metrics, and detect overfitting or unreliable strategies. **Progressive Disclosure**: This primer contains essentials only. Full details available via `docs` command. --- ## When to Use This Skill Load when: - Evaluating backtest results (Phase 3) - Detecting potential overfitting - Understanding strategy-specific performance expectations - Comparing multiple strategies or explaining results --- ## Quick Reference: Key Metrics ### Sharpe Ratio (Primary Metric) **Formula**: `(Return - Risk-Free Rate) / Volatility` | Sharpe | Quality | Action | |--------|---------|--------| | < 0.5 | Poor | Abandon | | 0.5 - 0.7 | Marginal | Consider optimization | | 0.7 - 1.0 | Acceptable | Optimize | | 1.0 - 1.5 | Good | Production-ready | | 1.5 - 2.0 | Very Good | Validate thoroughly | | > 3.0 | **SUSPICIOUS** | **Likely overfitting** | **Key Insight**: QuantConnect reports **annual Sharpe**. Sharpe > 1.0 is production-ready for most strategies. --- ### Maximum Drawdown **Formula**: `(Trough - Peak) / Peak` | Drawdown | Quality | Action | |----------|---------|--------| | < 20% | Excellent | Low risk | | 2
- When to Use This Skill
- Quick Reference: Key Metrics
- Sharpe Ratio (Primary Metric)
- Maximum Drawdown
- Total Trades (Statistical Significance)
- Win Rate
- Profit Factor
- Overfitting Detection (Red Flags)
- Strategy-Type Expectations
- Momentum
- Mean Reversion
- Trend Following
- Breakout
- Example Decisions
python SCRIPTS/backtesting_analysis.py --help
What does the Backtesting Analysis skill do?
Comprehensive guidance for interpreting backtest results and detecting overfitting (project)
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill backtesting-analysis-derekcrosslu-claude-code-explore --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.