app.py

import streamlit as st
import yfinance as yf
import numpy as np
import pandas as pd
from plotly.subplots import make_subplots
import plotly.graph_objects as go

def analyze_and_visualize_straddle(ticker, strike_call, strike_put, premium_call, premium_put):
    """
    This function is used to analyze a given ticker and visualize the payoffs for both long and short straddle strategies.

    Parameters:
    - ticker: Symbol of the underlying asset as is on Yahoo Finance.
    - strike_call: Strike price for the call option.
    - strike_put: Strike price for the put option.
    - premium_call: Premium paid for the call option.
    - premium_put: Premium paid for the put option.
    """

    ## Downloading historical data
    df = yf.download(ticker, multi_level_index=False, auto_adjust=False)

    # Computing returns
    df['Returns'] = df['Adj Close'].pct_change()

    # Computing annualized volatility
    df['Vol'] = df['Returns'].rolling(20).std() * np.sqrt(252)
    df.dropna(axis = 0, inplace = True) # Removing null values

    # Generating array of equally-spaced points representing the quantiles to be calculated (from 0% to 100%)
    quantiles = np.quantile(df['Vol'], np.linspace(0,1,11))

    # Using quantilies to categorize and label the annualized volatility values
    quantile_labels = pd.cut(df['Vol'], bins = quantiles, 
                             labels = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
    
    # Adding categorical labels to the dataframe
    df['Vol_Rank'] = quantile_labels

    # Plotting data
    fig = make_subplots(rows = 3, cols = 1, horizontal_spacing=0.2, row_heights=[.60, .20, .20], shared_xaxes=True)

    # First row --> Closing Price
    fig.add_trace(go.Scatter(
        x = df.index, y = df['Adj Close'], name = 'Closing Price'
    ), row = 1, col = 1)

    # Second row --> Annualized Volatility
    fig.add_trace(go.Scatter(
        x = df.index, y = df['Vol'], name = 'Annualized Volatility'
    ), row = 2, col = 1)

    # Third row --> Volatility rank
    fig.add_trace(go.Scatter(
        x = df.index, y = df['Vol_Rank'], name = 'Volatility Rank'
    ), row = 3, col = 1)

    # Defining subplots layout
    fig.update_layout(title = {'text': f'<b>{ticker} Closing Price & Volatility</b>'},
                      template = 'plotly_white',
                      height = 900, width = 950,
                      showlegend=False,
                      hovermode='x unified')
    
    # Defining layout of y-axes across subplots
    fig.update_yaxes(title_text = 'Closing Price ($)', row = 1)
    fig.update_yaxes(title_text = 'Annualized Volatility', row = 2)
    fig.update_yaxes(title_text = 'Volatility Rank', row = 3)

    # Generating an array of possible prices the underlying asset might fall into
    stock_prices = np.linspace(0.79 * min(strike_put, strike_call), 1.19 * max(strike_put, strike_call), 100).round(2)

    # Computing payoffs
    # Payoffs for holding long call and put options 
    long_call_payoff = np.maximum(stock_prices - strike_call, 0) - premium_call
    long_put_payoff = np.maximum(strike_put - stock_prices, 0) - premium_put

    # Payoffs for holding short positions in call and put options
    short_call_payoff = -long_call_payoff
    short_put_payoff = -long_put_payoff

    # Combined payoffs for both long and short positions
    combined_long_payoff = long_call_payoff + long_put_payoff
    combined_short_payoff = short_call_payoff + short_put_payoff

    # Computing profit and loss for long straddle
    profit_long = np.maximum(combined_long_payoff, 0)
    loss_long = np.minimum(combined_long_payoff, 0)

    # Computing profit and loss for short straddle
    loss_short = np.minimum(combined_short_payoff, 0)
    profit_short = np.maximum(combined_short_payoff, 0)
    
    # Creating subplots
    fig2 = make_subplots(
        rows=2, cols=1,
        horizontal_spacing=0.2,
        row_heights=[0.5, 0.5],
        shared_xaxes=False,
        shared_yaxes=False
    )

    # Adding Long Straddle traces
    fig2.add_trace(
        go.Scatter(x=stock_prices, y=long_call_payoff, mode='lines', line=dict(color='grey', dash='dash'), name='Long Call', hovertemplate='%{y:.2f}'),
        row=1, col=1
    )
    fig2.add_trace(
        go.Scatter(x=stock_prices, y=long_put_payoff, mode='lines', line=dict(color='grey', dash='dash'),  name='Long Put', hovertemplate='%{y:.2f}'),
        row=1, col=1
    )

    # Adding Short Straddle traces
    fig2.add_trace(
        go.Scatter(x=stock_prices, y=short_call_payoff, mode='lines', line=dict(color='grey', dash='dash'),  name='Short Call', hovertemplate='%{y:.2f}'),
        row=2, col=1
    )
    fig2.add_trace(
        go.Scatter(x=stock_prices, y=short_put_payoff, mode='lines', line=dict(color='grey', dash='dash'), name='Short Put', hovertemplate='%{y:.2f}'),
        row=2, col=1
    )
    

    # Adding the payoff lines for Long Straddle
    fig2.add_trace(
        go.Scatter(x=stock_prices, y=profit_long, mode='lines', line=dict(color='black', dash='solid'), name='Profit', hovertemplate='%{y:.2f}',
                    fill='tozeroy', fillcolor='rgba(0, 255, 0, 0.5)'),
        row=1, col=1
    )
    fig2.add_trace(
        go.Scatter(x=stock_prices, y=loss_long, mode='lines', line=dict(color='black', dash='solid'), name='Loss', hovertemplate='%{y:.2f}',
                    fill='tozeroy', fillcolor='rgba(255, 0, 0, 0.5)'),
        row=1, col=1
    )

    # Adding the payoff lines for Long Straddle
    fig2.add_trace(
        go.Scatter(x=stock_prices, y=loss_short, mode='lines', line=dict(color='black', dash='solid'), name = 'Loss', hovertemplate='%{y:.2f}',
                   fill='tozeroy', fillcolor='rgba(255, 0, 0, 0.5)'),
        row=2, col=1
    )
    fig2.add_trace(
        go.Scatter(x=stock_prices, y=profit_short, mode='lines', line=dict(color='black', dash='solid'), name = 'Profit', hovertemplate='%{y:.2f}',
                   fill='tozeroy', fillcolor='rgba(0, 255, 0, 0.5)'),
        row=2, col=1
    )

    
    # Defining layout
    fig2.update_layout(
        title={'text': f'<b>{ticker} Long & Short Straddle</b>'},
        template='plotly_white',
        height=1000, width=750,
        showlegend=False,
        hovermode='x unified')

    # Defining y-axes and x-axes tiles across rows
    fig2.update_yaxes(title_text='Long Payoff ($)', row=1)
    fig2.update_yaxes(title_text='Short Payoff ($)', row=2)
    fig2.update_xaxes(title_text = 'Underlying Asset Price at Expiration', row=1)
    fig2.update_xaxes(title_text = 'Underlying Asset Price at Expiration', row=2)

    # Displaying plots
    return fig, fig2


st.set_page_config(page_title="Long and Short Straddle",
                   page_icon=":chart_with_upwards_trend",
                   layout="wide",
                   initial_sidebar_state="expanded",
                   #theme={"base":"light"}
                   )

title = '<h1 style="font-family:Didot; font-size: 56px; text-align: left"><b>Options Trading: Long & Short Straddle</b></h1>'
st.markdown(title, unsafe_allow_html=True)

st.markdown("""
        This app helps you compute the payoffs for long and short straddles for options trading. It will also plot the historical closing prices for the 
        underlying asset, its annualized volatility, and its volatility rank.""")

st.markdown("""
        Annualized volatility is computed by multiplying the standard deviation of the last 20 trading days by the square root 
        of 252. The volatility rank is computed by breaking down the annualized volatility into ten equally-sized bins, and it 
        ranges from 1 to 10, where 1 represents low volatility, and 10 represents high volatility.""")


st.markdown('For more information about options and straddles, you can see my Kaggle Notebook, [Options Trading: Long & Short Straddle 📈](https://www.kaggle.com/code/lusfernandotorres/options-trading-long-short-straddle), where I describe the process of building this demo app.')

st.write(f"""**Parameters:**""")

st.write(f"""**• Ticker:** The asset symbol as it is on Yahoo Finance.""")
st.write(f"""**• Strike Price (Call):** Strike price for the call option.""")
st.write(f"""**• Strike Price (Put):** Strike price for the put option.""")
st.write(f"""**• Premium (Call):** Premium paid for the call option.""")
st.write(f"""**• Premium (Put):** Premium paid for the put option.""")

ticker = st.text_input("Ticker", placeholder="Enter the symbol for the underlying asset.")
strike_call = st.number_input("Strike Price (Call)", min_value=0.0, format="%f")
strike_put = st.number_input("Strike Price (Put)", min_value=0.0, format="%f")
premium_call = st.number_input("Premium (Call)", min_value=0.0, format="%f")
premium_put = st.number_input("Premium (Put)", min_value=0.0, format="%f")

# Button to trigger the analysis and visualization
if st.button('Analyze and Visualize Straddle'):
    # Check if all required inputs are provided
    if not ticker:
        st.error("Please enter a ticker symbol to proceed.")
    elif strike_call <= 0:
        st.error("Please enter a valid strike price for the call option.")
    elif strike_put <= 0:
        st.error("Please enter a valid strike price for the put option.")
    elif premium_call <= 0:
        st.error("Please enter a valid premium for the call option.")
    elif premium_put <= 0:
        st.error("Please enter a valid premium for the put option.")
    else:
        # All inputs are valid, proceed with the function call
        fig, fig2 = analyze_and_visualize_straddle(ticker, strike_call, strike_put, premium_call, premium_put)
        st.plotly_chart(fig)  # Display the figure in the app
        st.plotly_chart(fig2)  # Display the figure in the app

signature_html = """
<hr style="border: 0; height: 1px; border-top: 0.85px solid #b2b2b2">

<div style="text-align: left; color: #8d8d8d; padding-left: 15px; font-size: 14.25px;">
    Luis Fernando Torres, 2024<br><br>
    Let's connect!🔗<br>
    <a href="https://www.linkedin.com/in/luuisotorres/" target="_blank">LinkedIn</a> • <a href="https://medium.com/@luuisotorres" target="_blank">Medium</a> • <a href="https://www.kaggle.com/lusfernandotorres" target="_blank">Kaggle</a><br><br>
</div>
<div style="text-align: center; margin-top: 50px; color: #8d8d8d; padding-left: 15px; font-size: 14.25px;">
    <b>Like my content? Feel free to <a href="https://www.buymeacoffee.com/luuisotorres" target="_blank">Buy Me a Coffee ☕</a></b>
</div>
<div style="text-align: center; margin-top: 80px; color: #8d8d8d; padding-left: 15px; font-size: 14.25px;">
    <b><a href="https://luuisotorres.github.io/" target="_blank">https://luuisotorres.github.io/</a></b>
</div>
"""

st.markdown(signature_html, unsafe_allow_html=True)