backtesting-frameworks — quality + safety report
In the Skillier index (wshobson-agents__backtesting-frameworks) · scanned 2026-06-03 · engine: builtin+triage
✓ Clean — no heuristic safety flags surfaced.
Heuristic flags from the builtin scanner, which is known to over-flag (it trips on legitimate env-reading integrations, security skills, and library .eval calls). This is NOT an authoritative malicious verdict — re-scan with SkillSpector for the authoritative result. Run the authoritative scan →
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Quality notes
No quality issues flagged. ✓
About this skill
Build robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs. Use when developing trading algorithms, validating strategies, or building backtesting infrastructure.
📄 Read the SKILL.md
---
name: backtesting-frameworks
description: Build robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs. Use when developing trading algorithms, validating strategies, or building backtesting infrastructure.
---
# Backtesting Frameworks
Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates.
## When to Use This Skill
- Developing trading strategy backtests
- Building backtesting infrastructure
- Validating strategy performance
- Avoiding common backtesting biases
- Implementing walk-forward analysis
- Comparing strategy alternatives
## Core Concepts
### 1. Backtesting Biases
| Bias | Description | Mitigation |
| ---------------- | ------------------------- | ----------------------- |
| **Look-ahead** | Using future information | Point-in-time data |
| **Survivorship** | Only testing on survivors | Use delisted securities |
| **Overfitting** | Curve-fitting to history | Out-of-sample testing |
| **Selection** | Cherry-picking strategies | Pre-registration |
| **Transaction** | Ignoring trading costs | Realistic cost models |
### 2. Proper Backtest Structure
```
Historical Data
│
▼
┌─────────────────────────────────────────┐
│ Training Set │
│ (Strategy Development & Optimization) │
└─────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────┐
│ Validation Set │
│ (Parameter Selection, No Peeking) │
└─────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────┐
│ Test Set │
│ (Final Performance Evaluation) │
└─────────────────────────────────────────┘
```
### 3. Walk-Forward Analysis
```
Window 1: [Train──────][Test]
Window 2: [Train──────][Test]
Window 3: [Train──────][Test]
Window 4: [Train──────][Test]
─────▶ Time
```
## Detailed worked examples and patterns
Detailed sections (starting with `## Implementation Patterns`) live in `references/details.md`. Read that file when the navigation summary above is insufficient.
## Best Practices
### Do's
- **Use point-in-time data** - Avoid look-ahead bias
- **Include transaction costs** - Realistic estimates
- **Test out-of-sample** - Always reserve data
- **Use walk-forward** - Not just train/test
- **Monte Carlo analysis** - Understand uncertainty
### Don'ts
- **Don't overfit** - Limit parameters
- **Don't ignore survivorship** - Include delisted
- **Don't use adjusted data carelessly** - Understand adjustments
- **Don't optimize on full history** - Reserve test set
- **Don't ignore capacity** - Market impact mattersWant a live grade + an embeddable README badge? Run your skill through the free scanner.
Graded independently by Skillproof — nothing to sell the author. Quality is mechanical + corpus-grounded; safety flags are heuristic (builtin+triage), not a malicious verdict.