-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathfourier_pricer.py
47 lines (41 loc) · 1.8 KB
/
fourier_pricer.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
import numpy as np
from scipy.fftpack import fft, ifft
def carr_madan_fft_call_pricer(N, d_u, alpha, r, t, S0, q, chf_ln_st):
d_k = 2 * np.pi / (N * d_u)
beta = np.log(S0) - d_k * N / 2
u_arr = np.arange(N) * d_u
k_arr = beta + np.arange(N) * d_k
delta_arr = np.zeros(N)
delta_arr[0] = 1
w_arr = d_u / 3 * (3 + (-1) ** (np.arange(N) + 1) - delta_arr)
call_chf = (np.exp(-r * t) / ((alpha + 1j * u_arr) * (alpha + 1j * u_arr + 1))) * chf_ln_st(
u_arr - (alpha + 1) * 1j,
t, r, q=q, S0=S0)
x_arr = np.exp(-1j * beta * u_arr) * call_chf * w_arr
fft_prices = (fft(x_arr))
call_prices = (np.exp(-alpha * k_arr) / np.pi) * fft_prices.real
return np.exp(k_arr), call_prices
def carr_madan_fraction_fft_call_pricer(N, d_u, d_k, alpha, r, t, S0, q, chf_ln_st):
rou = (d_u * d_k) / (2 * np.pi)
beta = np.log(S0) - d_k * N / 2
u_arr = np.arange(N) * d_u
k_arr = beta + np.arange(N) * d_k
delta_arr = np.zeros(N)
delta_arr[0] = 1
w_arr = d_u / 3 * (3 + (-1) ** (np.arange(N) + 1) - delta_arr)
call_chf = (np.exp(-r * t) / ((alpha + 1j * u_arr) * (alpha + 1j * u_arr + 1))) * chf_ln_st(
u_arr - (alpha + 1) * 1j,
t, r, q=q, S0=S0)
x_arr = np.exp(-1j * beta * u_arr) * call_chf * w_arr
y_arr = np.zeros(2 * N) * 0j
y_arr[:N] = np.exp(-1j * np.pi * rou * np.arange(N) ** 2) * x_arr
z_arr = np.zeros(2 * N) * 0j
z_arr[:N] = np.exp(1j * np.pi * rou * np.arange(N) ** 2)
z_arr[N:] = np.exp(1j * np.pi * rou * np.arange(N - 1, -1, -1) ** 2)
ffty = (fft(y_arr))
fftz = (fft(z_arr))
fftx = ffty * fftz
fftpsi = ifft(fftx)
fft_prices = np.exp(-1j * np.pi * (np.arange(N) ** 2) * rou) * fftpsi[:N]
call_prices = (np.exp(-alpha * k_arr) / np.pi) * fft_prices.real
return np.exp(k_arr), call_prices