diff --git a/main.py b/main.py
index 4ad4fd0..14b29b8 100644
--- a/main.py
+++ b/main.py
@@ -74,7 +74,19 @@ def run_ticker_lifecycle(client, yf_ticker, t212_ticker, tz):
     
     if now.hour == 9 and now.minute >= 45:
         logger.info(f"Evaluating opening candle for {yf_ticker}...")
-        if strategy.check_setup():
+        
+        # Retry loop: wait for yfinance to publish the 09:30-09:45 candle (up to 3 minutes)
+        setup_found = False
+        max_retries = 12
+        for attempt in range(max_retries):
+            if strategy.check_setup():
+                setup_found = True
+                break
+            elif attempt < max_retries - 1:
+                logger.debug(f"Data not ready for {yf_ticker} yet, waiting 15s...")
+                time.sleep(15)
+                
+        if setup_found:
             params = strategy.get_trade_params()
             params['ticker'] = t212_ticker
             
diff --git a/src/strategy/scanner.py b/src/strategy/scanner.py
index 0b402e0..e5fc8ca 100644
--- a/src/strategy/scanner.py
+++ b/src/strategy/scanner.py
@@ -40,14 +40,20 @@ def scan_for_candidates(tickers: List[str] = DEFAULT_TICKERS, min_price: float =
                 
             df.ta.atr(length=14, append=True)
             
-            latest = df.iloc[-1]
+            # Safely get the close price, falling back to yesterday if today's is NaN (common at exactly 09:30)
+            close_price = df['Close'].iloc[-1]
+            if pd.isna(close_price) and len(df) > 1:
+                close_price = df['Close'].iloc[-2]
+                
             yesterday_atr = df['ATRr_14'].iloc[-2]
             
-            close_price = latest['Close']
+            # Safely get avg volume
             avg_volume = df['Volume'].tail(14).mean()
+            if pd.isna(avg_volume):
+                avg_volume = 0
             
             # Filters
-            if close_price < min_price or avg_volume < min_volume or pd.isna(yesterday_atr):
+            if pd.isna(close_price) or close_price < min_price or avg_volume < min_volume or pd.isna(yesterday_atr):
                 continue
                 
             atr_percent = (yesterday_atr / close_price) * 100