How to compute the Black Scholes model in Python

The Black-Scholes model is a widely used model for pricing European call and put options. In Python, you can compute the Black-Scholes model by using the following formula:

import math

def black_scholes(S, K, T, r, sigma, option_type):
    d1 = (math.log(S / K) + (r + 0.5 * sigma**2) * T) / (sigma * math.sqrt(T))
    d2 = d1 - sigma * math.sqrt(T)
    if option_type == "call":
        return S * math.norm.cdf(d1) - K * math.exp(-r * T) * math.norm.cdf(d2)
    else:  # option_type == "put"
        return K * math.exp(-r * T) * math.norm.cdf(-d2) - S * math.norm.cdf(-d1)

The black_scholes function takes the following parameters:

• S: the current price of the underlying asset
• K: the strike price of the option
• T: the time to expiration of the option in years
• r: the risk-free interest rate
• sigma: the volatility of the underlying asset
• option_type: the type of option, either "call" or "put"

The function returns the price of the European call or put option based on the Black-Scholes model. The cumulative normal distribution function math.norm.cdf is used to calculate the probabilities associated with the standard normal distribution.