diff --git a/crates/ml/src/trainers/dqn/trainer.rs b/crates/ml/src/trainers/dqn/trainer.rs
index fe85ee2c3..a2dd6d51b 100644
--- a/crates/ml/src/trainers/dqn/trainer.rs
+++ b/crates/ml/src/trainers/dqn/trainer.rs
@@ -3931,8 +3931,14 @@ impl DQNTrainer {
 
             // WAVE 3.11: Calculate and log VaR/CVaR from PnL history
             if self.pnl_history.len() > 20 {
-                let returns: Vec<f64> = self.pnl_history.iter().copied().collect();
-                
+                // Normalize raw dollar PnL to percentage returns relative to initial capital
+                let capital = self.hyperparams.initial_capital as f64;
+                let returns: Vec<f64> = if capital > 0.0 {
+                    self.pnl_history.iter().map(|&pnl| pnl / capital).collect()
+                } else {
+                    self.pnl_history.iter().copied().collect()
+                };
+
                 // Calculate VaR/CVaR at 95% and 99% confidence levels
                 // confidence_level=0.05 means we're looking at the worst 5% of returns (95% VaR)
                 let (var_95, cvar_95) = calculate_var_cvar(&returns, 0.05);
@@ -3942,10 +3948,10 @@ impl DQNTrainer {
                     "Epoch {}/{}: Risk Metrics - VaR(95%)={:.4}%, CVaR(95%)={:.4}%, VaR(99%)={:.4}%, CVaR(99%)={:.4}% (from {} PnL samples)",
                     epoch + 1,
                     self.hyperparams.epochs,
-                    var_95 * 100.0,  // Convert to percentage
-                    cvar_95 * 100.0, // Convert to percentage
-                    var_99 * 100.0,  // Convert to percentage
-                    cvar_99 * 100.0, // Convert to percentage
+                    var_95 * 100.0,
+                    cvar_95 * 100.0,
+                    var_99 * 100.0,
+                    cvar_99 * 100.0,
                     returns.len()
                 );
             }