import numpy as np
np.random.seed(1)

tickers = ['AAPL', 'GOOGL', 'AMZN']
num_portfs = 5
returns = np.array([])

shape = np.genfromtxt('data/AAPL.csv',  delimiter=",")[:,4].shape[0] - 1

pt_change = np.zeros(shape)

for ticker in tickers:
    data = np.genfromtxt('data/%s.csv'%ticker, delimiter=",")
    close = data[:250,4]
    close = close[::-1]
    diff = np.nan_to_num(np.diff(close) / close[:-1])
    returns = np.append(returns, np.sum(diff))
    pt_change = np.c_[pt_change, diff[::-1]]

pt_change = pt_change[:,1:]
cov = np.cov(pt_change.T)

weights = np.random.rand(num_portfs,len(tickers))

weights = (weights.T/weights.sum(axis=1)).T
returns = (weights*returns).sum(axis=1)

std = np.sqrt(weights.T*cov*weights)

print(std)