lint(adaptive-strategy): fix all 11 clippy deny violations

- Replace .unwrap() on partial_cmp with .unwrap_or(Ordering::Equal)
- Replace .unwrap() on Option with .ok_or_else()? for Kelly/PPO sizers
- Convert empty-bracket structs to unit structs (ShortfallTracker, VPINCalculator)
- Use fallback for chrono::Duration and serde_json::Number conversions

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

adaptive-strategy/src/ensemble/weight_optimizer.rs

@@ -279,8 +279,9 @@ impl WeightOptimizer {
         history.push(performance);
 
         // Maintain performance window
-        let cutoff_time =
-            chrono::Utc::now() - chrono::Duration::from_std(self.performance_window).unwrap();
+        let cutoff_time = chrono::Utc::now()
+            - chrono::Duration::from_std(self.performance_window)
+                .unwrap_or_else(|_| chrono::Duration::seconds(3600));
         history.retain(|p| p.timestamp > cutoff_time);
 
         debug!(
@@ -694,7 +695,7 @@ impl WeightOptimizer {
         }
 
         let mut returns: Vec<f64> = history.iter().map(|p| p.return_value).collect();
-        returns.sort_by(|a, b| a.partial_cmp(b).unwrap());
+        returns.sort_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal));
 
         let index = (returns.len() as f64 * 0.05).floor() as usize;
         returns.get(index).copied().unwrap_or(0.0)
@@ -967,7 +968,7 @@ impl MetaOptimizer {
     pub fn get_best_algorithm(&self) -> WeightingAlgorithmType {
         self.algorithm_performance
             .iter()
-            .max_by(|(_, a), (_, b)| a.partial_cmp(b).unwrap())
+            .max_by(|(_, a), (_, b)| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
             .map(|(alg, _)| alg.clone())
             .unwrap_or(WeightingAlgorithmType::BayesianModelAveraging)
     }

adaptive-strategy/src/execution/mod.rs

@@ -184,7 +184,7 @@ pub struct SlippageStatistics {
 
 /// Implementation shortfall tracking
 #[derive(Debug)]
-pub struct ShortfallTracker {}
+pub struct ShortfallTracker;
 
 /// Implementation shortfall measurement
 #[derive(Debug, Clone, Serialize, Deserialize)]
@@ -1000,7 +1000,7 @@ impl Default for ShortfallTracker {
 impl ShortfallTracker {
     /// Create a new shortfall tracker
     pub fn new() -> Self {
-        Self {}
+        Self
     }
 }
 

adaptive-strategy/src/microstructure/mod.rs

@@ -28,7 +28,7 @@ use super::config::MicrostructureConfig;
 /// traders are present in the market. Higher VPIN values indicate higher
 /// probability of adverse selection for market makers.
 #[derive(Debug, Clone)]
-pub struct VPINCalculator {}
+pub struct VPINCalculator;
 
 impl VPINCalculator {
     /// Create a new VPIN calculator with the given configuration
@@ -37,7 +37,7 @@ impl VPINCalculator {
     ///
     /// * `config` - VPIN calculation parameters
     pub fn new(_config: VPINConfig) -> Self {
-        Self {}
+        Self
     }
 
     /// Update VPIN calculation with new market data

adaptive-strategy/src/models/deep_learning.rs

@@ -640,7 +640,9 @@ impl Mamba2Model {
 
             // Use the latest features for single-step prediction
             // In a full implementation, we'd process the entire sequence
-            let latest_features = sequence.last().unwrap();
+            let latest_features = sequence
+                .last()
+                .ok_or_else(|| anyhow::anyhow!("Sequence unexpectedly empty after non-empty check"))?;
 
             // Ensure features match model input dimension
             let input_features = if latest_features.len() != self.mamba_config.d_model {
@@ -868,7 +870,8 @@ impl ModelTrait for Mamba2Model {
         parameters.insert(
             "compression_ratio".to_owned(),
             serde_json::Value::Number(
-                serde_json::Number::from_f64(self.compression_ratio).unwrap(),
+                serde_json::Number::from_f64(self.compression_ratio)
+                    .unwrap_or_else(|| serde_json::Number::from(0)),
             ),
         );
 

adaptive-strategy/src/models/mod.rs

@@ -308,7 +308,10 @@ impl ModelTrait for MockModel {
                 ),
                 (
                     "feature_sum".to_owned(),
-                    serde_json::Value::Number(serde_json::Number::from_f64(feature_sum).unwrap()),
+                    serde_json::Value::Number(
+                        serde_json::Number::from_f64(feature_sum)
+                            .unwrap_or_else(|| serde_json::Number::from(0)),
+                    ),
                 ),
             ])),
         })

adaptive-strategy/src/risk/mod.rs

@@ -542,7 +542,7 @@ impl RiskManager {
         let kelly_recommendation = self
             .kelly_sizer
             .as_mut()
-            .unwrap()
+            .ok_or_else(|| anyhow::anyhow!("Kelly sizer not initialized"))?
             .calculate_position_size(
                 symbol,
                 expected_return,
@@ -631,7 +631,7 @@ impl RiskManager {
             Some(
                 self.kelly_sizer
                     .as_mut()
-                    .unwrap()
+                    .ok_or_else(|| anyhow::anyhow!("Kelly sizer not initialized after is_some check"))?
                     .calculate_position_size(
                         symbol,
                         expected_return,
@@ -648,7 +648,7 @@ impl RiskManager {
         let ppo_recommendation = self
             .ppo_sizer
             .as_mut()
-            .unwrap()
+            .ok_or_else(|| anyhow::anyhow!("PPO sizer not initialized"))?
             .calculate_position_size(
                 symbol,
                 &market_data,