Backtesting Trading Strategies

---
name: backtesting-trading-strategies-3eb05e275a65
description: 'Backtest crypto and traditional trading strategies against historical
  data.

  Calculates performance metrics (Sharpe, Sortino, max drawdown), generates equity
  curves,

  and optimizes strategy parameters. Use when user wants to test a trading strategy,

  validate signals, or compare approaches.

  Trigger with phrases like "backtest strategy", "test trading strategy", "historical
  performance",

  "simulate trades", "optimize parameters", or "validate signals".

  '
allowed-tools: Read, Bash(python:*)
version: 1.30.0
author: Jeremy Longshore <jeremy@intentsolutions.io>
license: MIT
tags:
  - crypto
  - testing
  - performance
compatibility: Designed for Claude Code
---

# Backtesting Trading Strategies

## Overview

Simulate trading strategies against historical data. Results describe a historical simulation, not expected future performance. The framework includes 8 built-in strategies, the metrics listed below, and parameter optimization.

**Key Features:**

- 8 pre-built trading strategies (SMA, EMA, RSI, MACD, Bollinger, Breakout, Mean Reversion, Momentum)
- Performance metrics (Sharpe, Sortino, Calmar, VaR, max drawdown)
- Parameter grid search optimization
- Equity curve visualization
- Trade-by-trade analysis

## Prerequisites

Before invoking this skill, the user installs the required dependencies in the
Python environment used for the simulation:

```bash
set -euo pipefail
pip install pandas numpy yfinance matplotlib
```

Optional for advanced features:

```bash
set -euo pipefail
pip install ta-lib scipy scikit-learn
```

## Instructions

1. Fetch historical data (cached to `${CLAUDE_SKILL_DIR}/data/` for reuse):

   ```bash
   python ${CLAUDE_SKILL_DIR}/scripts/fetch_data.py --symbol BTC-USD --period 2y --interval 1d
   ```

2. Run a backtest with default or custom parameters:

   ```bash
   python ${CLAUDE_SKILL_DIR}/scripts/backtest.py --strategy sma_crossover --symbol BTC-USD --period 1y
   python ${CLAUDE_SKILL_DIR}/scripts/backtest.py \
     --strategy rsi_reversal \
     --symbol ETH-USD \
     --period 1y \
     --capital 10000 \
     --params '{"period": 14, "overbought": 70, "oversold": 30}'
   ```

3. Analyze results saved to `${CLAUDE_SKILL_DIR}/reports/` -- includes `*_summary.txt` (performance metrics), `*_trades.csv` (trade log), `*_equity.csv` (equity curve data), and `*_chart.png` (visual equity curve).
4. Optimize parameters via grid search to find the best combination:

   ```bash
   python ${CLAUDE_SKILL_DIR}/scripts/optimize.py \
     --strategy sma_crossover \
     --symbol BTC-USD \
     --period 1y \
     --param-grid '{"fast_period": [10, 20, 30], "slow_period": [50, 100, 200]}'
   ```

## Output

### Performance Metrics

| Metric        | Description                     |
| ------------- | ------------------------------- |
| Total Return  | Overall percentage gain/loss    |
| CAGR          | Compound annual growth rate     |
| Sharpe Ratio  | Historical risk-adjusted return |
| Sortino Ratio | Downside risk-adjusted return   |
| Calmar Ratio  | Return divided by max drawdown  |

### Risk Metrics

| Metric       | Description                     |
| ------------ | ------------------------------- |
| Max Drawdown | Largest peak-to-trough decline  |
| VaR (95%)    | Value at Risk at 95% confidence |
| CVaR (95%)   | Expected loss beyond VaR        |
| Volatility   | Annualized standard deviation   |

### Trade Statistics

| Metric        | Description                                                     |
| ------------- | --------------------------------------------------------------- |
| Total Trades  | Number of round-trip trades                                     |
| Win Rate      | Percentage of profitable trades                                 |
| Profit Factor | Gross profit divided by gross loss; N/A with no observed losses |
| Expectancy    | Expected value per trade                                        |

### Example Output

Figure-free layout; actual values depend on the input series, fees, slippage,
strategy and parameters. Do not present these placeholders as measured returns.

```text
HISTORICAL SIMULATION: [strategy]
[symbol] | [start_date] to [end_date]
Total Return: [computed] | Max Drawdown: [computed]
Sharpe Ratio: [computed] | Win Rate: [computed]
Total Trades: [observed] | Profit Factor: [computed or N/A]
```

Profit factor is unavailable when no losing trades were observed, including a
zero-trade run or a single winning/breakeven trade. A single losing trade yields
zero gross profit divided by its loss; this is not evidence of strategy quality.
Zero/one-trade samples cannot establish performance, and optimization is an
in-sample historical comparison rather than a forecast.

## Supported Strategies

| Strategy          | Description                     | Key Parameters                     |
| ----------------- | ------------------------------- | ---------------------------------- |
| `sma_crossover`   | Simple moving average crossover | `fast_period`, `slow_period`       |
| `ema_crossover`   | Exponential MA crossover        | `fast_period`, `slow_period`       |
| `rsi_reversal`    | RSI overbought/oversold         | `period`, `overbought`, `oversold` |
| `macd`            | MACD signal line crossover      | `fast`, `slow`, `signal`           |
| `bollinger_bands` | Mean reversion on bands         | `period`, `std_dev`                |
| `breakout`        | Price breakout from range       | `lookback`, `threshold`            |
| `mean_reversion`  | Return to moving average        | `period`, `z_threshold`            |
| `momentum`        | Rate of change momentum         | `period`, `threshold`              |

## Configuration

Create `${CLAUDE_SKILL_DIR}/config/settings.yaml`:

```yaml
data:
  provider: yfinance
  cache_dir: ./data

backtest:
  default_capital: 10000 # Starting simulated capital in quote-currency units
  commission: 0.001 # 0.1% per trade
  slippage: 0.0005 # 0.05% slippage

risk:
  max_position_size: 0.95
  stop_loss: null # Optional fixed stop loss
  take_profit: null # Optional fixed take profit
```

## Error Handling

Use Read to inspect [`references/errors.md`](references/errors.md) for common issues and solutions.

## Examples

See [`references/examples.md`](references/examples.md) for detailed usage examples including:

- Multi-asset comparison
- Walk-forward analysis
- Parameter optimization workflows

## Files

| File                    | Purpose                  |
| ----------------------- | ------------------------ |
| `scripts/backtest.py`   | Main backtesting engine  |
| `scripts/fetch_data.py` | Historical data fetcher  |
| `scripts/strategies.py` | Strategy definitions     |
| `scripts/metrics.py`    | Performance calculations |
| `scripts/optimize.py`   | Parameter optimization   |

## Resources

- [yfinance](https://github.com/ranaroussi/yfinance) - Yahoo Finance data
- [TA-Lib](https://ta-lib.org/) - Technical analysis library
- [QuantStats](https://github.com/ranaroussi/quantstats) - Portfolio analytics