Update app.py

app.py

@@ -9,14 +9,42 @@ def load_data(ticker, start_date, end_date):
     data.reset_index(inplace=True)
     return data
 
-# Function to plot candlestick chart
+# Function to identify buy and sell signals
+def identify_signals(data):
+    # Assume bearish and bullish candles that are significantly larger than usual as signals
+    data['Signal'] = 'None'  # Default no signal
+    avg_body_size = (abs(data['Open'] - data['Close'])).mean()  # Average body size of the candles
+    
+    for i in range(1, len(data)):
+        body_size = abs(data['Open'][i] - data['Close'][i])
+        if body_size > avg_body_size * 1.5:  # Threshold of 150% of average body size
+            if data['Close'][i] < data['Open'][i]:
+                data['Signal'][i] = 'Sell'  # Bearish candle
+            elif data['Close'][i] > data['Open'][i]:
+                data['Signal'][i] = 'Buy'  # Bullish candle
+
+    return data
+
+# Function to plot candlestick chart with signals
 def plot_candlestick_chart(data):
     fig = go.Figure(data=[go.Candlestick(
         x=data['Date'],
         open=data['Open'], high=data['High'],
         low=data['Low'], close=data['Close'],
+        increasing_line_color='green', decreasing_line_color='red',
         name='Candlestick')])
-    fig.update_layout(title='Candlestick Chart', xaxis_rangeslider_visible=False)
+
+    # Add signals to the plot
+    buys = data[data['Signal'] == 'Buy']
+    sells = data[data['Signal'] == 'Sell']
+    for i in buys.index:
+        fig.add_annotation(x=buys['Date'][i], y=buys['High'][i],
+                           text='Buy', showarrow=True, arrowhead=1, arrowcolor='green', arrowsize=3)
+    for i in sells.index:
+        fig.add_annotation(x=sells['Date'][i], y=sells['Low'][i],
+                           text='Sell', showarrow=True, arrowhead=1, arrowcolor='red', arrowsize=3)
+
+    fig.update_layout(title='Candlestick Chart with Buy and Sell Signals', xaxis_rangeslider_visible=False)
     return fig
 
 # Streamlit user interface
@@ -30,12 +58,13 @@ button = st.sidebar.button('Analyze')
 st.title('Fight the Tiger Trading Strategy Visualization')
 st.markdown("""
 This app analyzes and visualizes the "Fight the Tiger" trading strategy using historical stock data fetched from Yahoo Finance.
-Simply enter a stock ticker and select a date range to view the candlestick chart. Look for significant weekly candlesticks that suggest potential buy or sell signals according to the "Fight the Tiger" strategy.
+Enter a stock ticker and select a date range to view the candlestick chart with potential buy and sell signals based on significant candlestick formations.
 """)
 
 if button:
     if start_date < end_date:
         data = load_data(ticker, start_date, end_date)
+        data = identify_signals(data)  # Call to identify signals
         fig = plot_candlestick_chart(data)
         st.plotly_chart(fig, use_container_width=True)
     else: