Create app.py

app.py

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+import streamlit as st
+import yfinance as yf
+import pandas as pd
+import plotly.graph_objs as go
+
+def fetch_data(ticker, start_date, end_date):
+    data = yf.download(ticker, start=start_date, end=end_date)
+    return data
+
+def calculate_indicators(data, short_ema, long_ema):
+    # Exponential Moving Averages
+    data['EMA_Short'] = data['Close'].ewm(span=short_ema, adjust=False).mean()
+    data['EMA_Long'] = data['Close'].ewm(span=long_ema, adjust=False).mean()
+    return data
+
+def identify_signals(data):
+    data['Position'] = (data['EMA_Short'] > data['EMA_Long']).astype(int)
+    data['Signal'] = data['Position'].diff()
+    data['Buy Signal'] = data['Signal'] == 1
+    data['Sell Signal'] = data['Signal'] == -1
+    return data
+
+def plot_data(data):
+    fig = go.Figure()
+
+    # Adding Close price trace
+    fig.add_trace(go.Scatter(x=data.index, y=data['Close'], name='Close Price', line=dict(color='blue', width=2)))
+
+    # Adding EMAs
+    fig.add_trace(go.Scatter(x=data.index, y=data['EMA_Short'], name=f'EMA {short_ema}', line=dict(color='green', width=1.5)))
+    fig.add_trace(go.Scatter(x=data.index, y=data['EMA_Long'], name=f'EMA {long_ema}', line=dict(color='red', width=1.5)))
+
+    # Adding Buy and Sell signals
+    buys = data[data['Buy Signal']]
+    sells = data[data['Sell Signal']]
+    fig.add_trace(go.Scatter(x=buys.index, y=buys['Close'], mode='markers', name='Buy Signal', marker=dict(symbol='triangle-up', size=12, color='green')))
+    fig.add_trace(go.Scatter(x=sells.index, y=sells['Close'], mode='markers', name='Sell Signal', marker=dict(symbol='triangle-down', size=12, color='red')))
+
+    # Layout updates
+    fig.update_layout(title='2 EMA Crossover Trading Strategy Visualization', xaxis_title='Date', yaxis_title='Price', template='plotly_dark')
+    fig.update_xaxes(rangeslider_visible=True)
+    
+    return fig
+
+def main():
+    st.sidebar.title("Settings")
+    ticker = st.sidebar.text_input("Enter the ticker symbol, e.g., 'AAPL'", 'AAPL')
+    start_date = st.sidebar.date_input("Select the start date")
+    end_date = st.sidebar.date_input("Select the end date")
+    short_ema = st.sidebar.number_input("Enter the shorter EMA period", min_value=1, value=12)
+    long_ema = st.sidebar.number_input("Enter the longer EMA period", min_value=1, value=26)
+
+    st.title("2 EMA Crossover Trading Strategy")
+    st.markdown("""
+        ## Description
+        This application visualizes a 2 Exponential Moving Average (EMA) Crossover Strategy on historical stock data. 
+        The strategy involves two EMAs: a shorter period EMA and a longer period EMA. 
+        A **buy signal** is generated when the shorter EMA crosses above the longer EMA, and a **sell signal** is generated when the shorter EMA crosses below the longer EMA.
+        """)
+
+    if st.sidebar.button("Analyze"):
+        data = fetch_data(ticker, start_date, end_date)
+        data = calculate_indicators(data, short_ema, long_ema)
+        data = identify_signals(data)
+        fig = plot_data(data)
+        st.plotly_chart(fig, use_container_width=True)
+
+if __name__ == "__main__":
+    main()
+