feat: Add core trading modules for risk management, backtesting, and execution algorithms, alongside a new ML transparency widget and related frontend dependencies.

docs/user_manual/README.md

@@ -6,14 +6,15 @@ Welcome to the Crypto Trader user manual. This guide will help you get started w
 
 1. [Getting Started](getting_started.md) - Installation and first steps
 2. [Configuration](configuration.md) - Setting up the application
-3. [Trading](trading.md) - How to trade cryptocurrencies
+3. [Trading](trading.md) - How to trade cryptocurrencies with advanced order types
 4. [Strategies](strategies.md) - Creating and managing trading strategies
-5. [Backtesting](backtesting.md) - Testing strategies on historical data
-6. [Portfolio](portfolio.md) - Managing your portfolio
-7. [Alerts](alerts.md) - Setting up price and indicator alerts
-8. [Reporting](reporting.md) - Exporting data and generating reports
-9. [Troubleshooting](troubleshooting.md) - Common issues and solutions
-10. [FAQ](faq.md) - Frequently asked questions
+5. [Backtesting](backtesting.md) - Testing strategies with walk-forward analysis and Monte Carlo simulation
+6. [Portfolio](portfolio.md) - Managing your portfolio with risk analysis and rebalancing
+7. [Trade Journal](trade_journal.md) - Analyzing trade history, filtering, and exporting trade data
+8. [Alerts](alerts.md) - Setting up price and indicator alerts
+9. [Reporting](reporting.md) - Exporting data and generating reports
+10. [Troubleshooting](troubleshooting.md) - Common issues and solutions
+11. [FAQ](faq.md) - Frequently asked questions
 
 ## Quick Links
 

docs/user_manual/backtesting.md

@@ -49,14 +49,57 @@ After a backtest completes, you can export the results:
 
 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. This feature requires backend API support and will be available once the optimization endpoints are implemented.
+Parameter optimization allows you to automatically find the best strategy parameters using multiple algorithms:
 
-The UI includes an information card explaining this feature. When available, you'll be able to:
+- **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 (Grid Search, Genetic Algorithm, Bayesian Optimization)
+- Choose optimization method
 - View optimization progress
 - Compare optimization results
 

docs/user_manual/configuration.md

@@ -190,6 +190,44 @@ Configure risk limits in the Settings page:
 
 Settings are validated before saving and you'll see error messages if values are invalid.
 
+### Advanced Risk Settings
+
+#### Value at Risk (VaR)
+
+VaR configuration is managed through the risk management API. Default settings:
+
+- **Confidence Level**: 95% (typical: 90%, 95%, 99%)
+- **Holding Period**: 1 day (typical: 1 day, 10 days, 30 days)
+- **Lookback Period**: 252 days (1 trading year)
+
+VaR methods available:
+- Historical VaR
+- Parametric (Variance-Covariance) VaR
+- Monte Carlo VaR
+- Conditional VaR (CVaR)
+
+#### Portfolio Correlation Analysis
+
+Correlation analysis settings:
+- **Lookback Period**: 90 days default
+- **Correlation Threshold**: Configurable maximum correlation for position limits
+- **Diversification Scoring**: Automatic calculation
+
+#### Position Sizing
+
+Advanced position sizing methods available:
+- **Volatility-Adjusted**: Adjusts position size based on asset volatility (ATR-based)
+- **Fractional Kelly**: Configurable fraction of Kelly Criterion (default: 0.25)
+- **Regime-Aware**: Adjusts position size based on market regime
+- **Confidence-Based**: ML model confidence-adjusted position sizing
+
+#### Portfolio Rebalancing
+
+Rebalancing configuration:
+- **Threshold**: Deviation threshold to trigger rebalancing (default: 1%)
+- **Rebalance Interval**: Time-based interval in days (optional)
+- **Fee Threshold**: Minimum fee threshold to avoid unnecessary rebalancing
+
 ## Data Storage
 
 Data is stored in `~/.local/share/crypto_trader/`:

docs/user_manual/getting_started.md

@@ -79,12 +79,13 @@ When you first launch Crypto Trader:
 
 3. **Paper Trading**: By default, the application starts in paper trading mode with $100 virtual capital.
 
-4. **UI Overview**: The web interface contains six main pages accessible via the navigation menu:
-   - **Dashboard**: Overview with AutoPilot controls, system health, and real-time market data
+4. **UI Overview**: The web interface contains seven main pages accessible via the navigation menu:
+   - **Dashboard**: Overview with AutoPilot controls, system health, real-time market data, live P&L widgets, ML confidence gauge, and market regime indicators
    - **Strategies**: Create, edit, delete, and manage trading strategies with full parameter configuration
-   - **Trading**: Manual order placement, order management, and position closing
-   - **Portfolio**: View portfolio performance, holdings, allocation charts, and risk metrics
-   - **Backtesting**: Configure and run backtests on historical data with progress tracking
+   - **Trading**: Manual order placement with advanced order types (trailing stop, bracket orders, OCO, iceberg, TWAP/VWAP), order management, and position closing
+   - **Portfolio**: View portfolio performance, holdings, allocation charts, risk metrics, and automated rebalancing
+   - **Backtesting**: Configure and run backtests on historical data with walk-forward analysis, Monte Carlo simulation, and parameter optimization
+   - **Trade Journal**: Comprehensive trade history with filtering, statistics, analysis, and CSV export
    - **Settings**: Manage exchanges, risk settings, alerts, alert history, and application configuration
 
 ## Adding Your First Exchange

docs/user_manual/portfolio.md

@@ -75,6 +75,40 @@ Export functionality for:
 
 The equity curve chart shows portfolio value over time, helping you visualize performance trends.
 
+## Advanced Risk Management
+
+### Value at Risk (VaR)
+
+Crypto Trader provides comprehensive Value at Risk calculations using multiple methods:
+
+- **Historical VaR**: Based on historical portfolio return distribution
+- **Parametric VaR**: Assumes normal distribution (variance-covariance method)
+- **Monte Carlo VaR**: Simulates future returns using estimated parameters
+- **Conditional VaR (CVaR)**: Expected loss given that loss exceeds VaR threshold
+
+VaR helps quantify potential portfolio losses at specified confidence levels (e.g., 95% confidence, 1-day holding period).
+
+### Portfolio Correlation Analysis
+
+Monitor portfolio diversification and correlation risk:
+
+- **Correlation Matrix**: View correlation between all portfolio positions
+- **Diversification Score**: Measure how well-diversified your portfolio is
+- **Concentration Risk**: Identify over-concentration in correlated assets
+- **Correlation-based Limits**: Automatically prevent over-concentration
+
+Lower correlation between positions indicates better diversification and reduced portfolio risk.
+
+## Portfolio Rebalancing
+
+Automated portfolio rebalancing helps maintain your target asset allocation and can be triggered by:
+
+- **Threshold-based**: Rebalance when allocation drifts beyond specified threshold (e.g., 5% deviation)
+- **Time-based**: Rebalance at regular intervals (e.g., daily, weekly, monthly)
+- **Fee-aware**: Considers trading fees when determining if rebalancing is cost-effective
+
+Rebalancing automatically calculates required trades to restore target allocations while minimizing fees and market impact.
+
 ## Understanding Metrics
 
 ### Sharpe Ratio

docs/user_manual/trade_journal.md

@@ -0,0 +1,111 @@
+# Trade Journal Guide
+
+The Trade Journal provides comprehensive analysis of your trading history with advanced filtering, statistics, and export capabilities.
+
+## Overview
+
+The Trade Journal page (`/journal`) allows you to:
+
+- View complete trade history across all symbols and order types
+- Filter trades by status, side, symbol, and date range
+- Analyze trade statistics and performance metrics
+- Export trade data to CSV for external analysis
+- Track fees, volumes, and win rates
+
+## Accessing the Trade Journal
+
+1. Navigate to the **Trade Journal** page from the main navigation menu
+2. The journal displays all trades for the selected trading mode (Paper or Live)
+
+## Trade Statistics
+
+The Trade Journal displays key statistics at the top of the page:
+
+- **Total Trades**: Number of all trades matching current filters
+- **Filled Trades**: Number of successfully executed trades
+- **Total Volume**: Sum of all trade quantities
+- **Total Fees**: Cumulative fees paid across all trades
+
+## Filtering Trades
+
+Use the filter panel to narrow down your trade history:
+
+### Status Filter
+- All
+- Filled
+- Open
+- Pending
+- Cancelled
+- Rejected
+
+### Side Filter
+- All
+- Buy
+- Sell
+
+### Symbol Filter
+- Enter symbol name to search (e.g., "BTC/USD")
+- Partial matching supported
+
+### Date Range Filter
+- **Start Date**: Filter trades from this date onwards
+- **End Date**: Filter trades up to this date
+- Both fields optional; leave empty to show all dates
+
+### Trading Mode Toggle
+- Switch between Paper Trading and Live Trading data
+
+## Trade Table
+
+The trade table displays detailed information for each trade:
+
+- **ID**: Unique order identifier
+- **Symbol**: Trading pair (e.g., BTC/USD)
+- **Side**: Buy or Sell (color-coded chips)
+- **Type**: Order type (Market, Limit, Stop Loss, Trailing Stop, etc.)
+- **Quantity**: Order size
+- **Price**: Limit price (or "Market" for market orders)
+- **Status**: Current order status (color-coded chips)
+- **Filled**: Quantity that has been executed
+- **Fee**: Trading fee for this order
+- **Created At**: Timestamp when order was placed
+
+## Exporting Data
+
+To export trade data:
+
+1. Apply desired filters to narrow down trades
+2. Click the **Export CSV** button
+3. A CSV file will download with all filtered trades
+4. File name includes date: `trade_journal_YYYY-MM-DD.csv`
+
+The CSV includes all columns from the trade table for easy analysis in Excel, Google Sheets, or other tools.
+
+## Use Cases
+
+### Performance Analysis
+- Filter by filled trades to analyze executed strategy performance
+- Use date range to analyze performance over specific periods
+- Compare buy vs sell trade performance
+
+### Fee Tracking
+- View total fees to understand trading costs
+- Filter by symbol to see fees per trading pair
+- Export to calculate tax implications
+
+### Strategy Review
+- Filter by order type to analyze strategy effectiveness
+- Review cancelled/rejected orders to identify issues
+- Track order types used in different market conditions
+
+### Reporting
+- Export data for tax reporting
+- Create custom reports in spreadsheet software
+- Track compliance with trading limits
+
+## Tips
+
+- Use multiple filters together for precise analysis
+- Export data regularly for backup and external analysis
+- Review rejected/cancelled orders to identify systematic issues
+- Compare paper and live trading statistics separately

docs/user_manual/trading.md

@@ -75,6 +75,10 @@ The Autopilot feature provides autonomous trading signal generation with two dis
 - ✅ Optimizes strategy selection
 - ✅ Market condition analysis
 - ✅ Performance tracking and learning
+- ✅ **Online Learning**: Continuously improves from live trading data
+- ✅ **Confidence Calibration**: Accurate confidence scores using Platt scaling/isotonic regression
+- ✅ **Model Explainability**: SHAP values for understanding model decisions
+- ✅ **Advanced Regime Detection**: HMM/GMM-based market regime classification
 
 **Tradeoffs**:
 - ❌ Requires training data (needs historical trades)