portfolio-risk

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# Portfolio Risk

Analyzes portfolio risk and recommends position sizing and diversification.

## Real Code Reference

- `tradinglearn/backtest/backtester.py` — `Backtester._calculate_performance()` computes Sharpe, max drawdown, win rate, total return, CAGR
- `tradinglearn/utils/parameter_optimizer.py` — `plot_optimization_results()` heatmaps: return, Sharpe, drawdown, win rate
- `tradinglearn/pytdx2/backtest.py` — `BacktestEngine` tracks per-trade P&L for risk analysis

## Risk Metrics

- **VaR**: historical simulation, parametric, Monte Carlo
- **CVaR (Expected Shortfall)**: average loss beyond VaR
- **Maximum Drawdown**: peak-to-trough with recovery duration
- **Volatility**: annualized std of returns

## Performance Metrics

- **Sharpe Ratio**: (R - Rf) / sigma
- **Sortino Ratio**: downside-only volatility
- **Calmar Ratio**: annual return / max drawdown
- **Information Ratio**: active return / tracking error

## Portfolio Analysis

- Correlation matrix between holdings
- Beta to market benchmark
- Position concentration (Herfindahl index)
- Risk parity weights

## Usage

```python
from backtest.backtester import Backtester

bt = Backtester(initial_capital=100000.0)
bt.run_backtest(data, MyStrategy, params)
perf = bt.get_performance()
# {'total_return': 0.15, 'annual_return': 0.12, 'sharpe_ratio': 1.2,
#  'max_drawdown': -0.08, 'win_rate': 0.55, 'total_trades': 42}
portfolio = bt.get_portfolio()
# DataFrame with: portfolio_value, position, cash, returns
```

From LisonEvf/finance-skills, MIT.

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