diff --git a/src/pages/analysis/monte_carlo_page.py b/src/pages/analysis/monte_carlo_page.py
index d0fa34d..700bc3b 100644
--- a/src/pages/analysis/monte_carlo_page.py
+++ b/src/pages/analysis/monte_carlo_page.py
@@ -47,6 +47,27 @@ class MonteCarloSimulator:
             
         return price_paths
 
+    def calculate_target_price(self, confidence_level: float = 95) -> float:
+        """
+        Calculate target price based on Monte Carlo simulation and confidence level
+        
+        Args:
+            confidence_level (float): Confidence level for target price (default: 95)
+                
+        Returns:
+            float: Recommended target price
+        """
+        # Run simulation
+        paths = self.run_simulation()
+        
+        # Get the prices at specified timeframe
+        final_prices = paths[-1]
+        
+        # Calculate the price that represents the upside potential
+        target_price = np.percentile(final_prices, confidence_level)
+        
+        return target_price
+
     def calculate_stop_loss(self, risk_percentage: float) -> float:
         """
         Calculate stop loss price based on Monte Carlo simulation and desired risk percentage
diff --git a/src/pages/trading/trading_system_page.py b/src/pages/trading/trading_system_page.py
index 83832c8..a23ed3e 100644
--- a/src/pages/trading/trading_system_page.py
+++ b/src/pages/trading/trading_system_page.py
@@ -57,12 +57,23 @@ def trading_system_page():
                                         max_value=100.0, 
                                         value=1.0, 
                                         step=0.1)
-        use_monte_carlo = st.checkbox("Use Monte Carlo for Stop Loss", value=True)
+        use_monte_carlo = st.checkbox("Use Monte Carlo for Analysis", value=True)
+        if use_monte_carlo:
+            days_out = st.number_input("Days to Project", 
+                                     min_value=1,
+                                     max_value=30,
+                                     value=5,
+                                     help="Number of days to project for target price")
+            confidence_level = st.slider("Confidence Level (%)",
+                                      min_value=80,
+                                      max_value=99,
+                                      value=95)
     
     with col2:
         ticker = st.text_input("Ticker Symbol", value="").upper()
         entry_price = st.number_input("Entry Price ($)", min_value=0.01, step=0.01)
-        target_price = st.number_input("Target Price ($)", min_value=0.01, step=0.01)
+        if not use_monte_carlo:
+            target_price = st.number_input("Target Price ($)", min_value=0.01, step=0.01)
     
     if st.button("Calculate Position"):
         try:
@@ -85,10 +96,12 @@ def trading_system_page():
                         return
                     
                     # Initialize Monte Carlo simulator
-                    simulator = MonteCarloSimulator(df, num_simulations=1000, time_horizon=5)
+                    # Initialize Monte Carlo simulator
+                    simulator = MonteCarloSimulator(df, num_simulations=1000, time_horizon=days_out)
                     
-                    # Calculate stop loss price
+                    # Calculate stop loss and target prices
                     stop_loss_price = simulator.calculate_stop_loss(risk_percentage)
+                    target_price = simulator.calculate_target_price(confidence_level)
                     
                     # Calculate stop loss percentage
                     stop_loss_percentage = abs((stop_loss_price - entry_price) / entry_price * 100)
@@ -150,13 +163,16 @@ def trading_system_page():
             # Add Monte Carlo metrics if used
             if use_monte_carlo:
                 st.subheader("Monte Carlo Analysis")
-                col1, col2 = st.columns(2)
+                col1, col2, col3 = st.columns(3)
                 with col1:
-                    st.metric("Calculated Stop Loss Price", f"${stop_loss_price:.2f}")
-                    st.metric("Stop Loss Percentage", f"{stop_loss_percentage:.2f}%")
+                    st.metric("Stop Loss Price", f"${stop_loss_price:.2f}")
+                    st.metric("Stop Loss %", f"{stop_loss_percentage:.2f}%")
                 with col2:
-                    st.metric("Based on Simulations", "1,000")
-                    st.metric("Simulation Timeframe", "5 days")
+                    st.metric("Target Price", f"${target_price:.2f}")
+                    st.metric("Target %", f"{((target_price - entry_price) / entry_price * 100):.2f}%")
+                with col3:
+                    st.metric("Days Projected", f"{days_out}")
+                    st.metric("Confidence Level", f"{confidence_level}%")
                 
         except Exception as e:
             st.error(f"Error calculating position: {str(e)}")