Create app.py

app.py

@@ -0,0 +1,66 @@
+import streamlit as st
+import yfinance as yf
+import pandas as pd
+import numpy as np
+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):
+    # Bollinger Bands
+    data['Middle Band'] = data['Close'].rolling(window=20).mean()
+    data['Upper Band'] = data['Middle Band'] + 1.96 * data['Close'].rolling(window=20).std()
+    data['Lower Band'] = data['Middle Band'] - 1.96 * data['Close'].rolling(window=20).std()
+    
+    # Moving Averages
+    data['MA5'] = data['Close'].rolling(window=5).mean()
+    data['MA10'] = data['Close'].rolling(window=10).mean()
+    
+    return data
+
+def identify_signals(data):
+    data['Buy Signal'] = ((data['Close'] < data['Lower Band']) & (data['Close'].shift(1) > data['Lower Band'])) | \
+                         ((data['Close'] > data['MA5']) & (data['Close'].shift(1) < data['MA5']))
+    data['Sell Signal'] = ((data['Close'] > data['Upper Band']) & (data['Close'].shift(1) < data['Upper Band'])) | \
+                          ((data['Close'] < data['MA5']) & (data['Close'].shift(1) > data['MA5']))
+    return data
+
+def plot_data(data):
+    plt.figure(figsize=(10, 5))
+    plt.plot(data['Close'], label='Close Price')
+    plt.plot(data['Upper Band'], label='Upper Bollinger Band', linestyle='--')
+    plt.plot(data['Middle Band'], label='Middle Bollinger Band', linestyle='--')
+    plt.plot(data['Lower Band'], label='Lower Bollinger Band', linestyle='--')
+    plt.plot(data['MA5'], label='5-Day MA', color='green', linestyle='-.')
+    plt.plot(data['MA10'], label='10-Day MA', color='red', linestyle='-.')
+    
+    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 Trading Signals')
+    plt.xlabel('Date')
+    plt.ylabel('Price')
+    plt.legend()
+    plt.grid(True)
+    plt.show()
+
+def main():
+    st.title("OMA Ally BBMA 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 = identify_signals(data)
+        plot_data(data)
+        st.pyplot(plt)
+
+if __name__ == "__main__":
+    main()
+