Create app.py

app.py

@@ -0,0 +1,69 @@
+import streamlit as st
+import yfinance as yf
+import pandas as pd
+import matplotlib.pyplot as plt
+
+def fetch_data(ticker, start_date, end_date):
+    data = yf.download(ticker, start=start_date, end=end_date)
+    return data
+
+def calculate_indicators(data):
+    # High and low for the breakout signals
+    data['20 Day High'] = data['High'].rolling(window=20).max()
+    data['20 Day Low'] = data['Low'].rolling(window=20).min()
+    data['55 Day High'] = data['High'].rolling(window=55).max()
+    data['55 Day Low'] = data['Low'].rolling(window=55).min()
+    
+    return data
+
+def identify_signals(data):
+    # Buy signals are generated when the price exceeds the 20-day high
+    data['Buy Signal'] = (data['Close'] > data['20 Day High'].shift(1))
+    # Sell signals are generated when the price drops below the 20-day low
+    data['Sell Signal'] = (data['Close'] < data['20 Day Low'].shift(1))
+    
+    signals = []
+    for index, row in data.iterrows():
+        if row['Buy Signal']:
+            signals.append({'Date': index, 'Signal Type': 'Buy', 'Price': row['Close']})
+        if row['Sell Signal']:
+            signals.append({'Date': index, 'Signal Type': 'Sell', 'Price': row['Close']})
+    
+    return data, pd.DataFrame(signals)
+
+def plot_data(data):
+    plt.figure(figsize=(12, 6))
+    plt.plot(data['Close'], label='Close Price')
+    
+    buy_signals = data[data['Buy Signal']]
+    sell_signals = data[data['Sell Signal']]
+    plt.scatter(buy_signals.index, buy_signals['Close'], marker='^', color='green', s=100, label='Buy Signal')
+    plt.scatter(sell_signals.index, sell_signals['Close'], marker='v', color='red', s=100, label='Sell Signal')
+    
+    plt.title('Stock Price and Turtle Trading Signals')
+    plt.xlabel('Date')
+    plt.ylabel('Price')
+    plt.legend()
+    plt.grid(True)
+    plt.show()
+
+def main():
+    st.title("Turtle Trading Strategy Visualization")
+    ticker = st.text_input("Enter the ticker symbol, e.g., 'AAPL'")
+    start_date = st.date_input("Select the start date")
+    end_date = st.date_input("Select the end date")
+    
+    if st.button("Analyze"):
+        data = fetch_data(ticker, start_date, end_date)
+        data = calculate_indicators(data)
+        data, signals = identify_signals(data)
+        plot_data(data)
+        st.pyplot(plt)
+        if not signals.empty:
+            st.write("Trading Signals:")
+            st.dataframe(signals)
+        else:
+            st.write("No trading signals found for the selected period.")
+
+if __name__ == "__main__":
+    main()