Constructing an efficient frontier with n stocks

Constructing an efficient frontier is always one of the most difficult tasks for finance instructors since the task involves matrix manipulation and a constrained optimization procedure. One efficient frontier could vividly explain the Markowitz Portfolio theory. The following Python program uses five stocks to construct an efficient frontier:

from matplotlib.finance import quotes_historical_yahoo_ochl as getData
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scipy as sp
from numpy.linalg import inv, pinv

1. Code for input area:

   begYear,endYear = 2001,2013
   stocks=['IBM','WMT','AAPL','C','MSFT']

2. Code for defining two functions:

   def ret_monthly(ticker):  #  function 1
       x = getData(ticker,(begYear,1,1),(endYear,12,31),asobject=True,adjusted=True)
       logret=np.log(x.aclose[1:]/x.aclose[:-1]) 
       date=[]
       d0=x.date
       for i in range(0,np.size(logret)): 
           date...