Backtesting Trading Strategies
Overview
Validate trading strategies against historical data before risking real capital. This skill provides a complete backtesting framework with 8 built-in strategies, comprehensive performance metrics, and parameter optimization.
Key Features:
- 8 pre-built trading strategies (SMA, EMA, RSI, MACD, Bollinger, Breakout, Mean Reversion, Momentum)
- Full performance metrics (Sharpe, Sortino, Calmar, VaR, max drawdown)
- Parameter grid search optimization
- Equity curve visualization
- Trade-by-trade analysis
Prerequisites
Install required dependencies:
set -euo pipefail
pip install pandas numpy yfinance matplotlib
Optional for advanced features:
set -euo pipefail
pip install ta-lib scipy scikit-learn
Instructions
- Fetch historical data (cached to
${CLAUDE_SKILL_DIR}/data/ for reuse):python ${CLAUDE_SKILL_DIR}/scripts/fetch_data.py --symbol BTC-USD --period 2y --interval 1d
- Run a backtest with default or custom parameters:
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 \ # 10000: 10 seconds in ms
--params '{"period": 14, "overbought": 70, "oversold": 30}'
- 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).
- Optimize parameters via grid search to find the best combination:
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]}' # HTTP 200 OK
Output
Performance Metrics
| Metric |
Description |
| Total Return |
Overall percentage gain/loss |
| CAGR |
Compound annual growth rate |
| Sharpe Ratio |
Risk-adjusted return (target: >1.5) |
| 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 |
| Expectancy |
Expected value per trade |
Example Output
================================================================================
BACKTEST RESULTS: SMA CROSSOVER
BTC-USD | [start_date] to [end_date]
================================================================================
PERFORMANCE | RISK
Total Return: +47.32% | Max Drawdown: -18.45%
CAGR: +47.32% | VaR (95%): -2.34%
Sharpe Ratio: 1.87 | Volatility: 42.1%
Sortino Ratio: 2.41 | Ulcer Index: 8.2
--------------------------------------------------------------------------------
TRADE STATISTICS
Total Trades: 24 | Profit Factor: 2.34
Win Rate: 58.3% | Expectancy: $197.17
Avg Win: $892.45 | Max Consec. Losses: 3
================================================================================
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:
data:
provider: yfinance
cache_dir: ./data
backtest:
default_capital: 10000 # 10000: 10 seconds in ms
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
See ${CLAUDE_SKILL_DIR}/references/errors.md for common issues and solutions.
Examples
See ${CLAUDE_SKILL_DIR}/references/examples.md for detailed usage examples including:
- Multi-asset comparison
- Walk-forward analysis
- Parameter optimization workflows
Files
| File |
Purpose |
scripts/backtest.py |
Main backtesting engine |
scripts/fetch_data.py |
Historical data fetcher |
scripts/strategies.py |
Strategy definitions |
scripts/metrics.py |
Performance calculations |
scripts/optimize.py |
Parameter optimization |
Resources
1---2name: backtesting-trading-strategies3description: Backtest crypto and traditional trading strategies against historical data. Calculates performance metrics (Sharpe, Sortino, max drawdown), generates equity curves, and optimizes strategy parameters. Use when user wants to test a trading strategy, validate signals, or compare approaches. Trigger with phrases like "backtest strategy", "test trading strategy", "historical performance", "simulate trades", "optimize parameters", or "validate signals".4license: MIT5---6# Backtesting Trading Strategies78## Overview910Validate trading strategies against historical data before risking real capital. This skill provides a complete backtesting framework with 8 built-in strategies, comprehensive performance metrics, and parameter optimization.1112**Key Features:**13- 8 pre-built trading strategies (SMA, EMA, RSI, MACD, Bollinger, Breakout, Mean Reversion, Momentum)14- Full performance metrics (Sharpe, Sortino, Calmar, VaR, max drawdown)15- Parameter grid search optimization16- Equity curve visualization17- Trade-by-trade analysis1819## Prerequisites2021Install required dependencies:2223```bash24set -euo pipefail25pip install pandas numpy yfinance matplotlib26```2728Optional for advanced features:29```bash30set -euo pipefail31pip install ta-lib scipy scikit-learn32```3334## Instructions35361. Fetch historical data (cached to `${CLAUDE_SKILL_DIR}/data/` for reuse):37 ```bash38 python ${CLAUDE_SKILL_DIR}/scripts/fetch_data.py --symbol BTC-USD --period 2y --interval 1d39 ```402. Run a backtest with default or custom parameters:41 ```bash42 python ${CLAUDE_SKILL_DIR}/scripts/backtest.py --strategy sma_crossover --symbol BTC-USD --period 1y43 python ${CLAUDE_SKILL_DIR}/scripts/backtest.py \44 --strategy rsi_reversal \45 --symbol ETH-USD \46 --period 1y \47 --capital 10000 \ # 10000: 10 seconds in ms48 --params '{"period": 14, "overbought": 70, "oversold": 30}'49 ```503. Analyze results saved to `${CLAUDE_SKILL_DIR}/reports/` -- includes `*_summary.txt` (performance metrics), `*_trades.csv` (trade log), `*_equity.csv` (equity curve data), and `*_chart.png` (visual equity curve).514. Optimize parameters via grid search to find the best combination:52 ```bash53 python ${CLAUDE_SKILL_DIR}/scripts/optimize.py \54 --strategy sma_crossover \55 --symbol BTC-USD \56 --period 1y \57 --param-grid '{"fast_period": [10, 20, 30], "slow_period": [50, 100, 200]}' # HTTP 200 OK58 ```5960## Output6162### Performance Metrics6364| Metric | Description |65|--------|-------------|66| Total Return | Overall percentage gain/loss |67| CAGR | Compound annual growth rate |68| Sharpe Ratio | Risk-adjusted return (target: >1.5) |69| Sortino Ratio | Downside risk-adjusted return |70| Calmar Ratio | Return divided by max drawdown |7172### Risk Metrics7374| Metric | Description |75|--------|-------------|76| Max Drawdown | Largest peak-to-trough decline |77| VaR (95%) | Value at Risk at 95% confidence |78| CVaR (95%) | Expected loss beyond VaR |79| Volatility | Annualized standard deviation |8081### Trade Statistics8283| Metric | Description |84|--------|-------------|85| Total Trades | Number of round-trip trades |86| Win Rate | Percentage of profitable trades |87| Profit Factor | Gross profit divided by gross loss |88| Expectancy | Expected value per trade |8990### Example Output9192```93================================================================================94 BACKTEST RESULTS: SMA CROSSOVER95 BTC-USD | [start_date] to [end_date]96================================================================================97 PERFORMANCE | RISK98 Total Return: +47.32% | Max Drawdown: -18.45%99 CAGR: +47.32% | VaR (95%): -2.34%100 Sharpe Ratio: 1.87 | Volatility: 42.1%101 Sortino Ratio: 2.41 | Ulcer Index: 8.2102--------------------------------------------------------------------------------103 TRADE STATISTICS104 Total Trades: 24 | Profit Factor: 2.34105 Win Rate: 58.3% | Expectancy: $197.17106 Avg Win: $892.45 | Max Consec. Losses: 3107================================================================================108```109110## Supported Strategies111112| Strategy | Description | Key Parameters |113|----------|-------------|----------------|114| `sma_crossover` | Simple moving average crossover | `fast_period`, `slow_period` |115| `ema_crossover` | Exponential MA crossover | `fast_period`, `slow_period` |116| `rsi_reversal` | RSI overbought/oversold | `period`, `overbought`, `oversold` |117| `macd` | MACD signal line crossover | `fast`, `slow`, `signal` |118| `bollinger_bands` | Mean reversion on bands | `period`, `std_dev` |119| `breakout` | Price breakout from range | `lookback`, `threshold` |120| `mean_reversion` | Return to moving average | `period`, `z_threshold` |121| `momentum` | Rate of change momentum | `period`, `threshold` |122123## Configuration124125Create `${CLAUDE_SKILL_DIR}/config/settings.yaml`:126127```yaml128data:129 provider: yfinance130 cache_dir: ./data131132backtest:133 default_capital: 10000 # 10000: 10 seconds in ms134 commission: 0.001 # 0.1% per trade135 slippage: 0.0005 # 0.05% slippage136137risk:138 max_position_size: 0.95139 stop_loss: null # Optional fixed stop loss140 take_profit: null # Optional fixed take profit141```142143## Error Handling144145See `${CLAUDE_SKILL_DIR}/references/errors.md` for common issues and solutions.146147## Examples148149See `${CLAUDE_SKILL_DIR}/references/examples.md` for detailed usage examples including:150- Multi-asset comparison151- Walk-forward analysis152- Parameter optimization workflows153154## Files155156| File | Purpose |157|------|---------|158| `scripts/backtest.py` | Main backtesting engine |159| `scripts/fetch_data.py` | Historical data fetcher |160| `scripts/strategies.py` | Strategy definitions |161| `scripts/metrics.py` | Performance calculations |162| `scripts/optimize.py` | Parameter optimization |163164## Resources165166- [yfinance](https://github.com/ranaroussi/yfinance) - Yahoo Finance data167- [TA-Lib](https://ta-lib.org/) - Technical analysis library168- [QuantStats](https://github.com/ranaroussi/quantstats) - Portfolio analytics
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