It's easy to simulate a path of a brownian motion with the method explained in Wiener process as a limit of random walk:
import numpy as np
import matplotlib.pyplot as plt
X = 2 * np.random.binomial(1, 0.5, 2*1000*1000) - 1
cumsumX = np.cumsum(X)
n = 1000*1000
x = np.linspace(0, 1, num=n)
Y = 1/np.sqrt(n) * np.array([cumsumX[int(n*t)] for t in x])
plt.plot(x,Y)
plt.show()
Is it possible to simulate a fractional brownian motion with such a simple method, based on a random walk? (none of the methods explained in this article seem to be random-walk based)