Code Editor for app.py

import streamlit as st
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

st.title("Monte Carlo Option Pricing Model")

# Input parameters
S = st.number_input('Current Stock Price (S)', value=100.0)
K = st.number_input('Strike Price (K)', value=100.0)
T = st.number_input('Time to Maturity in Years (T)', value=1.0)
r = st.number_input('Risk-free Interest Rate (r)', value=0.05)
sigma = st.number_input('Volatility (σ)', value=0.2)
n = st.number_input('Number of Simulations', value=10000)

# Function to calculate option price

def monte_carlo_option_pricing(S, K, T, r, sigma, n):
    # Generate random numbers
    Z = np.random.normal(0, 1, n)
    ST = S * np.exp((r - 0.5 * sigma ** 2) * T + sigma * np.sqrt(T) * Z)
    payoff = np.maximum(ST - K, 0)  # Call option payoff
    option_price = np.exp(-r * T) * np.mean(payoff)
    return option_price

if st.button('Calculate Option Price'):
    option_price = monte_carlo_option_pricing(S, K, T, r, sigma, n)
    st.write(f'The estimated option price is: ${option_price:.2f}')

# Optional: plot histogram
if st.checkbox('Show Histogram of Simulated Prices'):
    Z = np.random.normal(0, 1, n)
    ST = S * np.exp((r - 0.5 * sigma ** 2) * T + sigma * np.sqrt(T) * Z)
    plt.hist(ST, bins=50, alpha=0.7)
    plt.title('Histogram of Simulated Stock Prices at Maturity')
    plt.xlabel('Stock Price')
    plt.ylabel('Frequency')
    st.pyplot(plt)