diff --git a/src/streamlit_app.py b/src/streamlit_app.py
index c46bb20..48e4c31 100644
--- a/src/streamlit_app.py
+++ b/src/streamlit_app.py
@@ -18,6 +18,30 @@ def init_session_state():
     if 'page' not in st.session_state:
         st.session_state.page = 'Trading Journal'
 
+def load_scanner_reports():
+    """Load and return available scanner reports"""
+    import os
+    import pandas as pd
+    from datetime import datetime
+    
+    reports = []
+    reports_dir = "scanner_results"
+    
+    if os.path.exists(reports_dir):
+        for file in os.listdir(reports_dir):
+            if file.endswith(".csv"):
+                file_path = os.path.join(reports_dir, file)
+                # Get file creation time
+                created = datetime.fromtimestamp(os.path.getctime(file_path))
+                reports.append({
+                    'name': file,
+                    'path': file_path,
+                    'created': created
+                })
+    
+    # Sort by creation time, newest first
+    return sorted(reports, key=lambda x: x['created'], reverse=True)
+
 def format_datetime(dt):
     """Format datetime for display"""
     if dt:
@@ -269,41 +293,78 @@ def trading_journal_page():
 def technical_scanner_page():
     st.header("Technical Scanner")
     
-    scanner_type = st.selectbox(
-        "Select Scanner",
-        ["SunnyBands", "ATR-EMA", "ATR-EMA v2"]
-    )
+    # Create tabs for scanner and reports
+    scanner_tab, reports_tab = st.tabs(["Run Scanner", "View Reports"])
     
-    col1, col2 = st.columns(2)
-    with col1:
-        min_price = st.number_input("Minimum Price", value=5.0, step=0.1)
-        max_price = st.number_input("Maximum Price", value=100.0, step=0.1)
+    with scanner_tab:
+        scanner_type = st.selectbox(
+            "Select Scanner",
+            ["SunnyBands", "ATR-EMA", "ATR-EMA v2"]
+        )
+        
+        col1, col2 = st.columns(2)
+        with col1:
+            min_price = st.number_input("Minimum Price", value=5.0, step=0.1)
+            max_price = st.number_input("Maximum Price", value=100.0, step=0.1)
+        
+        with col2:
+            min_volume = st.number_input("Minimum Volume", value=500000, step=100000)
+            portfolio_size = st.number_input("Portfolio Size", value=100000.0, step=1000.0)
+        
+        if st.button("Run Scanner"):
+            with st.spinner("Running scanner..."):
+                try:
+                    signals = run_technical_scanner(scanner_type.lower().replace(" ", "_"))
+                    if signals:
+                        st.success(f"Found {len(signals)} signals")
+                        for signal in signals:
+                            with st.expander(f"{signal['ticker']} - ${signal['entry_price']:.2f}"):
+                                col1, col2 = st.columns(2)
+                                with col1:
+                                    st.metric("Entry Price", f"${signal['entry_price']:.2f}")
+                                    st.metric("Target", f"${signal['target_price']:.2f}")
+                                    st.metric("Stop Loss", f"${signal['stop_loss']:.2f}")
+                                with col2:
+                                    st.metric("Shares", signal['shares'])
+                                    st.metric("Position Size", f"${signal['position_size']:.2f}")
+                                    st.metric("Risk Amount", f"${abs(signal['risk_amount']):.2f}")
+                    else:
+                        st.info("No signals found")
+                except Exception as e:
+                    st.error(f"Error running scanner: {str(e)}")
     
-    with col2:
-        min_volume = st.number_input("Minimum Volume", value=500000, step=100000)
-        portfolio_size = st.number_input("Portfolio Size", value=100000.0, step=1000.0)
-    
-    if st.button("Run Scanner"):
-        with st.spinner("Running scanner..."):
-            try:
-                signals = run_technical_scanner(scanner_type.lower().replace(" ", "_"))
-                if signals:
-                    st.success(f"Found {len(signals)} signals")
-                    for signal in signals:
-                        with st.expander(f"{signal['ticker']} - ${signal['entry_price']:.2f}"):
-                            col1, col2 = st.columns(2)
-                            with col1:
-                                st.metric("Entry Price", f"${signal['entry_price']:.2f}")
-                                st.metric("Target", f"${signal['target_price']:.2f}")
-                                st.metric("Stop Loss", f"${signal['stop_loss']:.2f}")
-                            with col2:
-                                st.metric("Shares", signal['shares'])
-                                st.metric("Position Size", f"${signal['position_size']:.2f}")
-                                st.metric("Risk Amount", f"${abs(signal['risk_amount']):.2f}")
-                else:
-                    st.info("No signals found")
-            except Exception as e:
-                st.error(f"Error running scanner: {str(e)}")
+    with reports_tab:
+        st.subheader("Scanner Reports")
+        
+        reports = load_scanner_reports()
+        if reports:
+            # Create a selectbox to choose the report
+            selected_report = st.selectbox(
+                "Select Report",
+                options=reports,
+                format_func=lambda x: f"{x['name']} ({x['created'].strftime('%Y-%m-%d %H:%M')})"
+            )
+            
+            if selected_report:
+                try:
+                    # Load and display the CSV
+                    df = pd.read_csv(selected_report['path'])
+                    
+                    # Add download button
+                    st.download_button(
+                        label="Download Report",
+                        data=df.to_csv(index=False),
+                        file_name=selected_report['name'],
+                        mime='text/csv'
+                    )
+                    
+                    # Display the dataframe
+                    st.dataframe(df)
+                    
+                except Exception as e:
+                    st.error(f"Error loading report: {str(e)}")
+        else:
+            st.info("No scanner reports found")
 
 def main():
     st.set_page_config(page_title="Trading System", layout="wide")