Update app.py

app.py

@@ -54,8 +54,13 @@ with st.sidebar.expander("Asset Settings", expanded=True):
 # Function to download data
 @st.cache_data
 def get_data(ticker, start, end):
-    data = yf.download(ticker, start=start, end=end)
-    # Squeeze the 'Close' column to ensure a 1D Series (fixes new yfinance behavior)
+    data = yf.download(ticker, start=start, end=end, auto_adjust=False)
+    if isinstance(data.columns, pd.MultiIndex):
+        data.columns = data.columns.get_level_values(0)
+    if data.empty:
+        raise ValueError(f"No data retrieved for {ticker}")
+    if len(data) < 300:  # Ensure enough data for largest trend window (300)
+        raise ValueError(f"Insufficient data points for {ticker}. Need at least 300 days.")
     return data['Close'].squeeze()
 
 # Exponential Moving Average based OU parameters
@@ -155,29 +160,32 @@ def grid_search(data, param_grid):
 run_button = st.sidebar.button("Run Strategy")
 
 if run_button:
-    # Get historical data
-    data = get_data(ticker, start_date, end_date)
-    param_grid = {
-        'base_window': [30, 50, 70, 90],
-        'base_alpha': [0.5, 1.0, 1.5],
-        'beta': [0.05, 0.1, 0.15],
-        'trend_window': [100, 200, 300]
-    }
-    best_params, best_performance, best_positions, best_trend = grid_search(data, param_grid)
-    st.session_state['data'] = data
-    st.session_state['best_params'] = best_params
-    st.session_state['best_positions'] = best_positions
-    st.session_state['best_trend'] = best_trend
-
-    # Display best parameters in JSON format
-    st.json({
-        "Best Parameters": {
-            "Base Window": best_params[0],
-            "Base Alpha": best_params[1],
-            "Beta": best_params[2],
-            "Trend Window": best_params[3]
+    try:
+        # Get historical data
+        data = get_data(ticker, start_date, end_date)
+        param_grid = {
+            'base_window': [30, 50, 70, 90],
+            'base_alpha': [0.5, 1.0, 1.5],
+            'beta': [0.05, 0.1, 0.15],
+            'trend_window': [100, 200, 300]
         }
-    })
+        best_params, best_performance, best_positions, best_trend = grid_search(data, param_grid)
+        st.session_state['data'] = data
+        st.session_state['best_params'] = best_params
+        st.session_state['best_positions'] = best_positions
+        st.session_state['best_trend'] = best_trend
+
+        # Display best parameters in JSON format
+        st.json({
+            "Best Parameters": {
+                "Base Window": best_params[0],
+                "Base Alpha": best_params[1],
+                "Beta": best_params[2],
+                "Trend Window": best_params[3]
+            }
+        })
+    except Exception as e:
+        st.error(f"An error occurred while running the analysis: {e}")
 
 # If the session state has the optimized data, allow updating the signal threshold and other parameters without re-running the optimization
 if 'best_params' in st.session_state:
@@ -257,4 +265,4 @@ hide_streamlit_style = """
 footer {visibility: hidden;}
 </style>
 """
-st.markdown(hide_streamlit_style, unsafe_allow_html=True)
+st.markdown(hide_streamlit_style, unsafe_allow_html=True)