Code Editor for app.py

import streamlit as st
import yfinance as yf
import pandas as pd
import numpy as np
import plotly.graph_objects as go
from datetime import datetime, timedelta

st.title('Stock Option Analysis')

# Sidebar inputs
ticker = st.sidebar.text_input('Stock Ticker', 'AAPL').upper()
today = datetime.today()
expiry_dates = pd.date_range(today, today + timedelta(days=365), freq='W-FRI')
expiry = st.sidebar.selectbox('Option Expiry Date', expiry_dates)
analysis_type = st.sidebar.radio('Analysis Type', ['Calls', 'Puts'])

try:
    # Get stock data
    stock = yf.Ticker(ticker)
    current_price = stock.info['regularMarketPrice']
    
    st.write(f"Current {ticker} Price: ${current_price:.2f}")
    
    # Get options chain
    options = stock.option_chain(expiry.strftime('%Y-%m-%d'))
    
    if analysis_type == 'Calls':
        chain = options.calls
        option_type = 'Call'
    else:
        chain = options.puts
        option_type = 'Put'
    
    # Calculate implied volatility and other metrics
    chain['Premium'] = chain['ask'] + chain['bid'] / 2
    chain['IntrinsicValue'] = np.where(
        option_type == 'Call',
        np.maximum(current_price - chain['strike'], 0),
        np.maximum(chain['strike'] - current_price, 0)
    )
    chain['TimeValue'] = chain['Premium'] - chain['IntrinsicValue']
    
    # Display options chain
    st.subheader(f'{ticker} {option_type} Options Chain')
    st.dataframe(chain[['strike', 'Premium', 'IntrinsicValue', 'TimeValue', 'volume', 'openInterest', 'impliedVolatility']])
    
    # Plot payoff diagram
    strikes = chain['strike'].values
    premiums = chain['Premium'].values
    
    fig = go.Figure()
    
    # Generate price range for x-axis
    price_range = np.linspace(current_price * 0.7, current_price * 1.3, 100)
    
    for i, strike in enumerate(strikes):
        premium = premiums[i]
        if option_type == 'Call':
            payoff = np.maximum(price_range - strike, 0) - premium
        else:
            payoff = np.maximum(strike - price_range, 0) - premium
            
        fig.add_trace(go.Scatter(
            x=price_range,
            y=payoff,
            name=f'Strike ${strike:.2f}',
            hovertemplate='Stock Price: $%{x:.2f}<br>Profit/Loss: $%{y:.2f}'
        ))
    
    fig.add_hline(y=0, line_dash="dash", line_color="gray")
    fig.add_vline(x=current_price, line_dash="dash", line_color="red")
    
    fig.update_layout(
        title=f'{ticker} {option_type} Options Payoff Diagram',
        xaxis_title='Stock Price',
        yaxis_title='Profit/Loss',
        showlegend=True
    )
    
    st.plotly_chart(fig)
    
    # Risk analysis
    st.subheader('Risk Analysis')
    max_loss = -premiums.min()
    max_profit = 'Unlimited' if option_type == 'Call' else strikes.min() - premiums.min()
    
    col1, col2 = st.columns(2)
    with col1:
        st.metric('Maximum Loss', f'${max_loss:.2f}')
    with col2:
        st.metric('Maximum Profit', 'Unlimited' if max_profit == 'Unlimited' else f'${max_profit:.2f}')
    
except Exception as e:
    st.error(f'Error: {str(e)}. Please check the ticker symbol and try again.')