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Black-Scholes pricing

The Black-Scholes formula for a European call option composes log, exp, sqrt, and normal_cdf. All are available in Nautilus without any special imports beyond Nautilus.Distributions.

For a European call with spot price S, strike K, risk-free rate r, volatility sigma, and time to expiry T:

d1 = [ln(S/K) + (r + sigma^2/2) * T] / (sigma * sqrt(T))
d2 = d1 - sigma * sqrt(T)
C = S * N(d1) - K * exp(-rT) * N(d2)

where N(x) is the standard normal CDF.

module Nautilus.BookBlackScholes
import Nautilus.Distributions (normal_cdf)
export (black_scholes_call)
def black_scholes_call(s: f32, k: f32, r: f32, sigma: f32, t: f32) -> f32 = {
sqrt_t = sqrt(t)
d1_num = add(log(div(s, k)), mul(add(r, mul(cast(0.5, f32), mul(sigma, sigma))), t))
d1 = div(d1_num, mul(sigma, sqrt_t))
d2 = sub(d1, mul(sigma, sqrt_t))
nd1 = normal_cdf(d1, cast(0.0, f32), cast(1.0, f32))
nd2 = normal_cdf(d2, cast(0.0, f32), cast(1.0, f32))
discount = exp(neg(mul(r, t)))
sub(mul(s, nd1), mul(mul(k, discount), nd2))
}

normal_cdf takes three arguments (x, mean, std). For the standard normal, pass (x, 0.0, 1.0).

def main() -> f32 = black_scholes_call(
cast(100.0, f32), -- S = 100
cast(100.0, f32), -- K = 100 (at-the-money)
cast(0.05, f32), -- r = 5%
cast(0.2, f32), -- sigma = 20%
cast(1.0, f32) -- T = 1 year
)
-- Expected result: approximately 10.45

The ATM call price of about 10.4506 matches the closed-form f64 value to within f32 precision.

Use grad to calculate first-order sensitivities of this function, as shown in Greeks.

For a European put, use put-call parity rather than re-deriving:

def black_scholes_put(s: f32, k: f32, r: f32, sigma: f32, t: f32) -> f32 = {
call = black_scholes_call(s, k, r, sigma, t)
discount = exp(neg(mul(r, t)))
-- P = C - S + K * exp(-rT)
add(sub(call, s), mul(k, discount))
}