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import streamlit as st
import yfinance as yf
import pandas as pd
import plotly.graph_objs as go
# Function to calculate EMA
def calculate_ema(data, span):
return data.ewm(span=span, adjust=False).mean()
# Function to get data and calculate EMAs
def get_data_with_ema(ticker, start_date, end_date, short_ema, long_ema):
data = yf.download(ticker, start=start_date, end=end_date)
data['Short_EMA'] = calculate_ema(data['Close'], short_ema)
data['Long_EMA'] = calculate_ema(data['Close'], long_ema)
data['Signal'] = 0
data['Signal'][short_ema:] = \
(data['Short_EMA'][short_ema:] > data['Long_EMA'][short_ema:]).astype(int)
data['Position'] = data['Signal'].diff()
return data
# Streamlit interface
st.sidebar.title("2 EMA Crossover Trading Strategy")
ticker = st.sidebar.text_input("Enter the ticker symbol", "AAPL")
short_ema = st.sidebar.number_input("Short EMA length", min_value=5, max_value=50, value=20)
long_ema = st.sidebar.number_input("Long EMA length", min_value=10, max_value=200, value=50)
start_date = st.sidebar.date_input("Start Date", pd.to_datetime("2020-01-01"))
end_date = st.sidebar.date_input("End Date", pd.to_datetime("today"))
if st.sidebar.button("Analyze"):
data = get_data_with_ema(ticker, start_date, end_date, short_ema, long_ema)
# Plotting
fig = go.Figure()
fig.add_trace(go.Candlestick(x=data.index,
open=data['Open'], high=data['High'],
low=data['Low'], close=data['Close'], name='Candlestick'))
fig.add_trace(go.Scatter(x=data.index, y=data['Short_EMA'], line=dict(color='blue', width=1.5), name='Short EMA'))
fig.add_trace(go.Scatter(x=data.index, y=data['Long_EMA'], line=dict(color='red', width=1.5), name='Long EMA'))
# Buy signals
buys = data[data['Position'] == 1]
sells = data[data['Position'] == -1]
fig.add_trace(go.Scatter(x=buys.index, y=buys['Close'], mode='markers', marker=dict(color='green', size=10), name='Buy Signal'))
fig.add_trace(go.Scatter(x=sells.index, y=sells['Close'], mode='markers', marker=dict(color='red', size=10), name='Sell Signal'))
fig.update_layout(title=f"2 EMA Crossover Trading Analysis for {ticker}",
xaxis_title="Date",
yaxis_title="Price",
xaxis_rangeslider_visible=False)
fig.update_xaxes(type='category')
st.plotly_chart(fig, use_container_width=True)
st.title("2 EMA Crossover Trading Strategy App")
st.markdown("""
This app visualizes the 2 EMA Crossover Trading Strategy for any stock ticker available on Yahoo Finance.
Select the ticker symbol, EMA lengths, start and end date for the analysis in the sidebar and click analyze to see the results.
**Instructions:**
1. Enter the stock ticker symbol (e.g., AAPL, GOOGL).
2. Choose the lengths for the Short and Long EMAs.
3. Set the desired time period for analysis.
4. Click the 'Analyze' button to view the interactive chart with buy and sell signals.
""")
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