Feature: Add comprehensive risk metrics to simulation results

[ch55secake]

Problem

The trading simulation currently reports only basic metrics: final value, total return, buy-and-hold return, and number of trades. For a system targeting 5-10% ROI, these metrics are insufficient to evaluate whether the returns are worth the risk taken.

Proposed Metrics

Add the following to the simulation results dictionary:

Metric	Description
Sharpe ratio	Annualised risk-adjusted return
Sortino ratio	Sharpe variant penalising only downside volatility
Maximum drawdown	Largest peak-to-trough decline
Max drawdown duration	Longest time to recover from a drawdown
Calmar ratio	Annualised return / max drawdown
Win rate	% of trades that were profitable
Profit factor	Gross profit / gross loss
Average win/loss ratio	Mean winning trade / mean losing trade
Annualised volatility	Std dev of returns, annualised
Value at Risk (VaR)	95th percentile daily loss
Beta to benchmark	Correlation with buy-and-hold

Proposed Location

Create a RiskMetrics dataclass or utility in src/simulation/ that takes the portfolio history DataFrame and computes all metrics. Call it at the end of TradingSimulator.simulate().

Impact

• Proper risk-adjusted evaluation of strategies
• Enables filtering strategies by risk profile, not just return
• Required foundation for factor attribution (Factor model #28)

Files likely affected

• src/simulation/trading_simulator.py
• New: src/simulation/risk_metrics.py