# -*- coding: utf-8 -*-
"""
Simulations EDS + prix Monte Carlo options
"""
import numpy as np
import matplotlib.pyplot as plt
#simulation Brownien
T=1
N=250
dt=T/N
M=200 #no. realistions
W=np.zeros((N+1,M))
dW=np.sqrt(dt)*np.random.randn(N,M) #increments Browniens
W[1:,:]=np.cumsum(dW,axis=0)
plt.plot(W)

S0=100
mu=0.15
sigma=0.2
K=100
r=0.05
S=np.zeros_like(W)
S[0,:]=S0
for k in range(N):
    S[k+1,:]=None
	
plt.figure('S')    
plt.plot(S)
    
#calcul de la moyenne empirique et histogramme
plt.hist(S[-1,:])
prix_option= None