feat: add payoff_ratio and recovery_factor metrics, bump to 0.3.2

Add two new risk/reward metrics to BacktestMetrics:
- payoff_ratio: avg winning return / avg losing return (absolute)
- recovery_factor: net profit / max drawdown in absolute terms
Computed in both StreamingMetrics::finalize() and PortfolioEngine.
Exposed via PyO3 with #[pyo3(get)] on PyBacktestMetrics.
Updated README with API reference and changelog.

src/core/types.rs

@@ -376,6 +376,10 @@ pub struct BacktestMetrics {
     pub avg_holding_period: f64,
     /// Exposure time percentage (time in market).
     pub exposure_pct: f64,
+    /// Payoff ratio (avg win / avg loss).
+    pub payoff_ratio: f64,
+    /// Recovery factor (net profit / max drawdown).
+    pub recovery_factor: f64,
 }
 
 /// Complete backtest result.

src/metrics/streaming.rs

@@ -513,6 +513,30 @@ impl StreamingMetrics {
         let worst_trade_pct =
             if self.worst_trade_pct == f64::INFINITY { 0.0 } else { self.worst_trade_pct };
 
+        // Payoff ratio: average win / average loss (absolute value)
+        let payoff_ratio = if avg_loss_pct.abs() > 0.0 {
+            avg_win_pct / avg_loss_pct.abs()
+        } else if avg_win_pct > 0.0 {
+            f64::INFINITY
+        } else {
+            0.0
+        };
+
+        // Recovery factor: net profit / max drawdown (absolute value)
+        let net_profit = final_value - initial_capital;
+        let recovery_factor = if self.max_drawdown_pct > 0.0 && initial_capital > 0.0 {
+            let max_dd_absolute = self.max_drawdown_pct / 100.0 * initial_capital;
+            if max_dd_absolute > 0.0 {
+                net_profit / max_dd_absolute
+            } else {
+                0.0
+            }
+        } else if net_profit > 0.0 {
+            f64::INFINITY
+        } else {
+            0.0
+        };
+
         BacktestMetrics {
             total_return_pct,
             sharpe_ratio,
@@ -545,6 +569,8 @@ impl StreamingMetrics {
             max_consecutive_losses: self.max_consecutive_losses,
             avg_holding_period,
             exposure_pct: 0.0, // TODO: calculate based on time in market
+            payoff_ratio,
+            recovery_factor,
         }
     }
 

src/portfolio/engine.rs

@@ -591,6 +591,30 @@ impl PortfolioEngine {
             0.0
         };
 
+        // Payoff ratio: average win / average loss (absolute value)
+        let payoff_ratio = if avg_loss_pct.abs() > 0.0 {
+            avg_win_pct / avg_loss_pct.abs()
+        } else if avg_win_pct > 0.0 {
+            f64::INFINITY
+        } else {
+            0.0
+        };
+
+        // Recovery factor: net profit / max drawdown (absolute value)
+        let net_profit = end_value - start_value;
+        let recovery_factor = if max_drawdown_pct > 0.0 && start_value > 0.0 {
+            let max_dd_absolute = max_drawdown_pct / 100.0 * start_value;
+            if max_dd_absolute > 0.0 {
+                net_profit / max_dd_absolute
+            } else {
+                0.0
+            }
+        } else if net_profit > 0.0 {
+            f64::INFINITY
+        } else {
+            0.0
+        };
+
         BacktestMetrics {
             total_return_pct,
             sharpe_ratio,
@@ -623,6 +647,8 @@ impl PortfolioEngine {
             max_consecutive_losses,
             avg_holding_period,
             exposure_pct,
+            payoff_ratio,
+            recovery_factor,
         }
     }
 

src/python/bindings.rs

@@ -419,6 +419,10 @@ pub struct PyBacktestMetrics {
     pub avg_holding_period: f64,
     #[pyo3(get)]
     pub exposure_pct: f64,
+    #[pyo3(get)]
+    pub payoff_ratio: f64,
+    #[pyo3(get)]
+    pub recovery_factor: f64,
 }
 
 #[pymethods]
@@ -1203,6 +1207,8 @@ fn convert_result(result: crate::core::types::BacktestResult) -> PyBacktestResul
         max_consecutive_losses: result.metrics.max_consecutive_losses,
         avg_holding_period: result.metrics.avg_holding_period,
         exposure_pct: result.metrics.exposure_pct,
+        payoff_ratio: result.metrics.payoff_ratio,
+        recovery_factor: result.metrics.recovery_factor,
     };
 
     let trades: Vec<PyTrade> = result