diff --git a/src/screener/t_atr_ema.py b/src/screener/t_atr_ema.py
index 67534fe..ec8a35c 100644
--- a/src/screener/t_atr_ema.py
+++ b/src/screener/t_atr_ema.py
@@ -3,13 +3,16 @@ import os
 from datetime import datetime, timedelta
 import pandas as pd
 from db.db_connection import create_client
+from trading.position_calculator import PositionCalculator
+from screener.t_sunnyband import get_stock_data
 from indicators.three_atr_ema import ThreeATREMAIndicator
 
 def check_atr_ema_bullish_signal(df: pd.DataFrame) -> bool:
     """Check for bullish signal based on ATR EMA indicator"""
     # Get latest values from DataFrame
     last_price = df.iloc[-1]
-    last_bands = results.iloc[-1]  # You need to calculate results first
+    results = indicator.calculate(df)
+    last_bands = results.iloc[-1]
     
     print(f"\nSunnyBands Indicators:")
     print(f"DMA: ${last_bands['dma']:.2f}")
@@ -23,9 +26,12 @@ def check_atr_ema_buy_condition(df: pd.DataFrame) -> bool:
     last_price = df.iloc[-1]
     
     # Check if price is below EMA and has started moving up
+    ema = results['ema'].iloc[-1]
+    lower_band = results['lower_band'].iloc[-1]
+    
     return (
-        last_price['close'] < ema &
-        last_price['close'].shift(1) <= lower_band &
+        last_price['close'] < ema and
+        last_price['close'].shift(1) <= lower_band and
         last_price['close'] > last_price['close'].shift(1)
     )
 
@@ -36,6 +42,8 @@ def run_atr_ema_scanner(min_price: float, max_price: float, min_volume: int, por
     interval = get_interval_choice()
     
     end_date = datetime.now()
+    start_ts = int(start_date.timestamp() * 1000000000)
+    end_ts = int(end_date.timestamp() * 1000000000)
     start_date = end_date - timedelta(days=1)  # Get last trading day
     
     client = create_client()