diff --git a/src/db/db_connection.py b/src/db/db_connection.py
index 395c788..19d34a8 100644
--- a/src/db/db_connection.py
+++ b/src/db/db_connection.py
@@ -9,7 +9,7 @@ from dotenv import load_dotenv
 load_dotenv()
 
 # Configure logging
-logging.basicConfig(level=logging.INFO)
+logging.basicConfig(level=logging.WARNING)
 logger = logging.getLogger(__name__)
 
 def create_client():
diff --git a/src/screener/t_atr_ema.py b/src/screener/t_atr_ema.py
index a4f54c0..58c66c7 100644
--- a/src/screener/t_atr_ema.py
+++ b/src/screener/t_atr_ema.py
@@ -4,7 +4,7 @@ from datetime import datetime, timedelta
 import pandas as pd
 from db.db_connection import create_client
 from trading.position_calculator import PositionCalculator
-from utils.data_utils import get_stock_data
+from utils.data_utils import get_stock_data, validate_signal_date
 from indicators.three_atr_ema import ThreeATREMAIndicator
 
 def check_atr_ema_bullish_signal(df: pd.DataFrame) -> bool:
@@ -65,6 +65,7 @@ def run_atr_ema_scanner(min_price: float, max_price: float, min_volume: int, por
                     max(window_start) as last_update
                 FROM stock_db.stock_prices
                 WHERE window_start BETWEEN {start_ts} AND {end_ts}
+                AND toDateTime(window_start/1000000000) <= now()
                 GROUP BY ticker
                 HAVING last_close BETWEEN {min_price} AND {max_price}
                 AND total_volume >= {min_volume}
diff --git a/src/screener/t_atr_ema_v2.py b/src/screener/t_atr_ema_v2.py
index c879c2f..2d13c5a 100644
--- a/src/screener/t_atr_ema_v2.py
+++ b/src/screener/t_atr_ema_v2.py
@@ -3,7 +3,7 @@ import pandas as pd
 import os
 from db.db_connection import create_client
 from trading.position_calculator import PositionCalculator
-from utils.data_utils import get_stock_data
+from utils.data_utils import get_stock_data, validate_signal_date
 from screener.user_input import get_interval_choice, get_date_range
 from indicators.three_atr_ema import ThreeATREMAIndicator
 
@@ -81,6 +81,7 @@ def run_atr_ema_scanner_v2(min_price: float, max_price: float, min_volume: int,
                     max(window_start) as last_update
                 FROM stock_db.stock_prices
                 WHERE window_start BETWEEN {start_ts} AND {end_ts}
+                AND toDateTime(window_start/1000000000) <= now()
                 GROUP BY ticker
                 HAVING last_close BETWEEN {min_price} AND {max_price}
                 AND total_volume >= {min_volume}
diff --git a/src/screener/t_sunnyband.py b/src/screener/t_sunnyband.py
index a8263fb..28f1b82 100644
--- a/src/screener/t_sunnyband.py
+++ b/src/screener/t_sunnyband.py
@@ -6,7 +6,7 @@ from db.db_connection import create_client
 from indicators.sunny_bands import SunnyBands
 from trading.position_calculator import PositionCalculator
 from screener.user_input import get_interval_choice, get_date_range
-from utils.data_utils import get_stock_data
+from utils.data_utils import get_stock_data, validate_signal_date
 
 
 
@@ -187,6 +187,7 @@ def run_sunny_scanner(min_price: float, max_price: float, min_volume: int, portf
             max(window_start) as last_update
         FROM stock_db.stock_prices
         WHERE window_start BETWEEN {start_ts} AND {end_ts}
+        AND toDateTime(window_start/1000000000) <= now()
         GROUP BY ticker
         HAVING last_close BETWEEN {min_price} AND {max_price}
         AND total_volume >= {min_volume}
@@ -265,7 +266,7 @@ def run_sunny_scanner(min_price: float, max_price: float, min_volume: int, portf
                                 bullish_signals.append(signal_data)
                                 # Update print output format
                                 dollar_risk = position['potential_loss'] * -1
-                                signal_date = df.iloc[-1]['date']  # Get the date of the signal
+                                signal_date = validate_signal_date(df.iloc[-1]['date'])  # Get and validate the date
                                 signal_data['signal_date'] = signal_date  # Add to signal data
                                 print(f"\n🟢 {ticker} @ ${current_price:.2f} on {signal_date.strftime('%Y-%m-%d %H:%M')}")
                                 print(f"   Size: {position['shares']} shares (${position['position_value']:.2f})")
diff --git a/src/utils/data_utils.py b/src/utils/data_utils.py
index 3174d80..a36662e 100644
--- a/src/utils/data_utils.py
+++ b/src/utils/data_utils.py
@@ -2,6 +2,21 @@ import pandas as pd
 from datetime import datetime, timedelta
 from db.db_connection import create_client
 
+def validate_signal_date(signal_date: datetime) -> datetime:
+    """
+    Validate and adjust signal date if needed
+    
+    Args:
+        signal_date (datetime): Signal date to validate
+        
+    Returns:
+        datetime: Valid signal date (not in future)
+    """
+    current_date = datetime.now()
+    if signal_date > current_date:
+        return current_date
+    return signal_date
+
 def get_stock_data(ticker: str, start_date: datetime, end_date: datetime, interval: str) -> pd.DataFrame:
     """
     Fetch stock data from the database with enhanced fallback logic
@@ -41,8 +56,7 @@ def get_stock_data(ticker: str, start_date: datetime, end_date: datetime, interv
             AND window_start BETWEEN 
                 {int(start_date.timestamp() * 1e9)} AND 
                 {int(end_date.timestamp() * 1e9)}
-            AND toYear(toDateTime(window_start/1000000000)) <= toYear(now())
-            AND toYear(toDateTime(window_start/1000000000)) >= (toYear(now()) - 1)
+            AND toDateTime(window_start/1000000000) <= now()
             ORDER BY date ASC
         """