# Backtesting Guide

This guide explains how to use the backtesting feature to evaluate trading strategies on historical data.

## Running a Backtest

1. Navigate to the **Backtesting** page
2. Configure your backtest in the form:
   - **Strategy**: Select a strategy from the dropdown (required)
   - **Symbol**: Trading pair to test (e.g., BTC/USD)
   - **Exchange**: Data source exchange (e.g., coinbase)
   - **Timeframe**: Data timeframe (1m, 5m, 15m, 1h, 4h, 1d) - 1h recommended for most strategies
   - **Start Date**: Beginning of test period (required)
   - **End Date**: End of test period (required)
   - **Initial Capital**: Starting capital in USD (default: $100)
   - **Slippage (%)**: Expected slippage percentage (default: 0.1%)
   - **Fee Rate (%)**: Trading fee percentage (default: 0.1%)
3. Click **Run Backtest**
4. A progress overlay will appear showing the backtest is running
5. An operations panel will show the running backtest with status
6. Wait for completion (you'll receive a success notification)
7. Review results in the **Backtest Results** section below

## Understanding Results

The backtest results include:

- **Total Return**: Overall percentage return
- **Sharpe Ratio**: Risk-adjusted return metric (higher is better)
- **Sortino Ratio**: Downside risk-adjusted return (higher is better)
- **Max Drawdown**: Largest peak-to-trough decline
- **Win Rate**: Percentage of profitable trades
- **Total Trades**: Number of trades executed
- **Final Value**: Portfolio value at end of backtest

## Exporting Results

After a backtest completes, you can export the results:

1. In the backtest results section, find the export buttons
2. **Export CSV**: 
   - Click **Export CSV** button
   - Downloads a CSV file with all trades from the backtest
   - File includes: timestamp, side, price, quantity, value
3. **Export PDF**:
   - Click **Export PDF** button
   - Generates a comprehensive PDF report
   - Includes charts, metrics, and trade analysis

Both exports are automatically named with the current date for easy organization.

## Advanced Backtesting Features

### Walk-Forward Analysis

Walk-forward analysis provides robust parameter optimization by using rolling windows:

1. **Training Period**: Strategy parameters are optimized on training data (e.g., 90 days)
2. **Testing Period**: Optimized parameters are tested on out-of-sample data (e.g., 30 days)
3. **Rolling Window**: Window advances by step size (e.g., 30 days) and process repeats

This method prevents overfitting and provides more realistic performance estimates than single-period optimization.

**Benefits**:
- Prevents overfitting to historical data
- Tests strategy robustness across different market conditions
- Provides confidence intervals for parameter estimates
- Validates strategy performance on unseen data

### Monte Carlo Simulation

Monte Carlo simulation tests strategy robustness by running thousands of random scenarios:

- **Random Parameter Variation**: Tests strategy performance across parameter ranges
- **Statistical Analysis**: Provides distribution of returns, Sharpe ratios, and drawdowns
- **Confidence Intervals**: Shows expected performance ranges (e.g., 95% confidence)
- **Risk Assessment**: Identifies worst-case scenarios and tail risks

Use Monte Carlo simulation to:
- Validate strategy robustness
- Assess parameter sensitivity
- Understand potential downside risks
- Estimate performance under various market conditions

## Parameter Optimization

Parameter optimization allows you to automatically find the best strategy parameters using multiple algorithms:

- **Grid Search**: Exhaustive search across parameter grid (best for small parameter spaces)
- **Bayesian Optimization**: Efficient exploration using Gaussian process (best for expensive evaluations)
- **Genetic Algorithms**: Evolutionary search that finds good solutions efficiently

Optimization metrics include:
- Sharpe Ratio (risk-adjusted returns)
- Total Return
- Maximum Drawdown
- Win Rate

When available via the backend API, you'll be able to:
- Select parameters to optimize
- Set parameter ranges
- Choose optimization method
- View optimization progress
- Compare optimization results

## Interpreting Metrics

- **Sharpe Ratio > 1**: Good risk-adjusted returns
- **Max Drawdown < 20%**: Acceptable risk level
- **Win Rate > 50%**: More winning than losing trades

# Backtesting Guide

Learn how to test your trading strategies on historical data.

## What is Backtesting?

Backtesting is the process of testing a trading strategy on historical data to evaluate its performance before risking real money.

## Running a Backtest

1. Navigate to Backtest view
2. Select a strategy
3. Configure backtest parameters:
   - **Start Date**: Beginning of test period
   - **End Date**: End of test period
   - **Initial Capital**: Starting capital
   - **Symbol**: Trading pair to test
   - **Timeframe**: Data timeframe
4. Click "Run Backtest"
5. Wait for completion
6. Review results

## Backtest Parameters

### Time Period

- **Start Date**: When to begin the backtest
- **End Date**: When to end the backtest
- **Duration**: Length of test period
- Longer periods provide more reliable results

### Capital Settings

- **Initial Capital**: Starting amount (e.g., $10,000)
- **Currency**: Base currency (USD, EUR, etc.)

### Market Settings

- **Symbol**: Trading pair (BTC/USD, ETH/USD, etc.)
- **Timeframe**: Data granularity (1m, 5m, 1h, 1d)
- **Exchange**: Historical data source

## Understanding Results

### Performance Metrics

- **Total Return**: Overall profit/loss percentage
- **Final Capital**: Ending portfolio value
- **Sharpe Ratio**: Risk-adjusted return measure
- **Sortino Ratio**: Downside risk-adjusted return
- **Max Drawdown**: Largest peak-to-trough decline
- **Win Rate**: Percentage of profitable trades

### Trade Analysis

- **Total Trades**: Number of trades executed
- **Winning Trades**: Number of profitable trades
- **Losing Trades**: Number of unprofitable trades
- **Average Win**: Average profit per winning trade
- **Average Loss**: Average loss per losing trade
- **Profit Factor**: Ratio of gross profit to gross loss

### Charts

- **Equity Curve**: Portfolio value over time
- **Drawdown Chart**: Drawdown periods
- **Trade Distribution**: Win/loss distribution
- **Monthly Returns**: Performance by month

## Realistic Backtesting

Crypto Trader includes realistic backtesting features:

### Slippage

Slippage simulates the difference between expected and actual execution prices.

- **Default**: 0.1% for market orders
- **Configurable**: Adjust based on market conditions
- **Market Impact**: Larger orders have more slippage

### Fees

Trading fees are automatically included:

- **Maker Fees**: For limit orders (typically 0.1%)
- **Taker Fees**: For market orders (typically 0.2%)
- **Exchange-Specific**: Fees vary by exchange

### Order Execution

- **Market Orders**: Execute at current price + slippage
- **Limit Orders**: Execute only if price reaches limit
- **Partial Fills**: Large orders may fill partially

## Parameter Optimization

Optimize strategy parameters for better performance:

1. Select strategy
2. Choose parameters to optimize
3. Set parameter ranges
4. Select optimization method:
   - **Grid Search**: Test all combinations
   - **Genetic Algorithm**: Evolutionary optimization
   - **Bayesian Optimization**: Efficient parameter search
5. Run optimization
6. Review results and select best parameters

## Best Practices

1. **Use Sufficient Data**: Test on at least 6-12 months of data
2. **Avoid Overfitting**: Don't optimize too aggressively
3. **Test Multiple Periods**: Verify performance across different market conditions
4. **Consider Fees**: Always include realistic fees
5. **Check Slippage**: Account for execution costs
6. **Validate Results**: Compare with paper trading

## Limitations

Backtesting has limitations:

- **Past Performance**: Doesn't guarantee future results
- **Market Conditions**: Markets change over time
- **Data Quality**: Results depend on data accuracy
- **Execution**: Real trading may differ from simulation

## Exporting Results

Export backtest results for analysis:

1. Click "Export Results"
2. Choose format:
   - **CSV**: For spreadsheet analysis
   - **PDF**: For reports
3. Save file

## Troubleshooting

**No results?**
- Check date range has data
- Verify symbol is correct
- Check strategy parameters

**Unrealistic results?**
- Verify fees are enabled
- Check slippage settings
- Review data quality