Update stock_analysis.py

stock_analysis.py

@@ -20,8 +20,14 @@ def forecast_series(series, model="ARIMA", forecast_period=FORECAST_PERIOD):
         model = ARIMA(series, order=(5, 1, 0))
         model_fit = model.fit()
         forecast = model_fit.forecast(steps=forecast_period, alpha=(1 - CONFIDENCE_INTERVAL))
-        predictions = forecast.predicted_mean
-        confidence_intervals = forecast.conf_int()
+        
+        # Check if forecast is a numpy array (newer statsmodels) or a ForecastResults object (older statsmodels)
+        if isinstance(forecast, np.ndarray):
+            predictions = forecast
+            confidence_intervals = model_fit.get_forecast(steps=forecast_period).conf_int()
+        else:
+            predictions = forecast.predicted_mean
+            confidence_intervals = forecast.conf_int()
     elif model == "Prophet":
         # Implement Prophet forecasting method
         pass