Use more conservative 1e-6 to prevent division by zero.

model.py

@@ -358,8 +358,8 @@ def calculate_market_conditions(df, lookback_window=180):
     df["Log_Return"] = df["Log_Return"].fillna(method="bfill")
 
     # Recent vs historical volatility ratio
-    recent_vol = max(df["Log_Return"].tail(30).std(), 1e-8)  # Prevent division by zero
+    recent_vol = max(df["Log_Return"].tail(30).std(), 1e-6)  # Prevent division by zero
-    historical_vol = max(df["Log_Return"].tail(lookback_window).std(), 1e-8)
+    historical_vol = max(df["Log_Return"].tail(lookback_window).std(), 1e-6)
     metrics["vol_ratio"] = recent_vol / historical_vol
 
     # Trend strength using log prices