diff --git a/src/screener/t_candlestick.py b/src/screener/t_candlestick.py
index efe56ba..43e2447 100644
--- a/src/screener/t_candlestick.py
+++ b/src/screener/t_candlestick.py
@@ -35,10 +35,11 @@ CANDLESTICK_PATTERNS = {
 
 def check_entry_signal(df: pd.DataFrame, selected_patterns: list = None) -> list:
     """
-    Check for bullish candlestick patterns
+    Check for bullish candlestick patterns across the entire date range
     
     Args:
         df (pd.DataFrame): DataFrame with OHLCV data
+        selected_patterns (list): List of patterns to scan for
         
     Returns:
         list: List of tuples (signal, date, signal_data) for each signal found
@@ -62,22 +63,22 @@ def check_entry_signal(df: pd.DataFrame, selected_patterns: list = None) -> list
             df['close'].values
         )
     
-    # Look for signals in the last candle
-    i = len(df) - 1
-    found_patterns = []
-    
-    for pattern_name, pattern_values in pattern_signals.items():
-        # Check if we have a bullish signal (value > 0)
-        if pattern_values[i] > 0:
-            found_patterns.append(CANDLESTICK_PATTERNS[pattern_name]['description'])
-    
-    if found_patterns:
-        signal_data = {
-            'price': df.iloc[i]['close'],
-            'patterns': ', '.join(found_patterns),
-            'pattern_count': len(found_patterns)
-        }
-        signals.append((True, df.iloc[i]['date'], signal_data))
+    # Look for signals across all candles
+    for i in range(len(df)):
+        found_patterns = []
+        
+        for pattern_name, pattern_values in pattern_signals.items():
+            # Check if we have a bullish signal (value > 0)
+            if pattern_values[i] > 0:
+                found_patterns.append(CANDLESTICK_PATTERNS[pattern_name]['description'])
+        
+        if found_patterns:
+            signal_data = {
+                'price': df.iloc[i]['close'],
+                'patterns': ', '.join(found_patterns),
+                'pattern_count': len(found_patterns)
+            }
+            signals.append((True, df.iloc[i]['date'], signal_data))
     
     return signals