bs_erf_naive.py

# Copyright (C) 2017-2018 Intel Corporation
#
# SPDX-License-Identifier: MIT


import base_bs_erf
from math import log, sqrt, exp, erf
import numpy as np
invsqrt = lambda x: 1.0/sqrt(x)

def black_scholes ( nopt, price, strike, t, rate, vol, call, put ):
    mr = -rate
    sig_sig_two = vol * vol * 2

    for i in range(nopt):
        P = float( price [i] )
        S = strike [i]
        T = t [i]

        a = log(P / S)
        b = T * mr

        z = T * sig_sig_two
        c = 0.25 * z
        y = invsqrt(z)

        w1 = (a - b + c) * y
        w2 = (a - b - c) * y

        d1 = 0.5 + 0.5 * erf(w1)
        d2 = 0.5 + 0.5 * erf(w2)

        Se = exp(b) * S

        call [i] = P * d1 - Se * d2
        put [i] = call [i] - P + Se

base_bs_erf.run("Naive-loop", black_scholes, 4, 8, nparr=False, pass_args=True)