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.
View on GitHubccf/claude-code-ccf-marketplace
quantitative-trading
plugins/quantitative-trading/skills/backtesting-frameworks/SKILL.md
January 20, 2026
Select agents to install to:
npx add-skill https://github.com/ccf/claude-code-ccf-marketplace/blob/main/plugins/quantitative-trading/skills/backtesting-frameworks/SKILL.md -a claude-code --skill backtesting-frameworksInstallation paths:
.claude/skills/backtesting-frameworks/# 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
```
## Implementation Patterns
### Pattern 1: Event-Driven Backtester
```python
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
f