In [2]:

    

%matplotlib inline


    

In [3]:

    

from pandas_datareader import data


    

In [4]:

    

import datetime as dt


    

In [36]:

    

from math import sqrt


    

In [51]:

    

from numpy import log, exp


    

In [137]:

    

import pandas as pd


    

In [230]:

    

start = dt.datetime(2014,11,28)


    

In [231]:

    

end = dt.datetime(2016,12,9)


    

In [232]:

    

spy = data.DataReader('SPY','yahoo',start,end)['Adj Close']


    

In [237]:

    

p = data.DataReader('MO','yahoo',start,end)['Adj Close']


    

In [238]:

    

df = pd.DataFrame({'SPY':spy,'Stock':p})


    

In [239]:

    

df /= df.iloc[0]


    

In [240]:

    

df.plot();


    

In [221]:

    

r = df.pct_change().dropna()


    

In [222]:

    

r.std()


    

    
Out[222]:





SPY      0.009431
Stock    0.009902
dtype: float64

In [223]:

    

df.iloc[-1]


    

    
Out[223]:





SPY      2.149857
Stock    3.633068
Name: 2016-12-09 00:00:00, dtype: float64

In [224]:

    

n = df.count()


    

In [225]:

    

(((df.iloc[-1]**(1/n))**252) - 1)/(r.std()*sqrt(252))


    

    
Out[225]:





SPY      0.903749
Stock    1.517135
dtype: float64

In [42]:

    

KO = data.DataReader('KO','yahoo',start,end)


    

In [43]:

    

p['KO'] = KO['Adj Close']


    

In [45]:

    

p['KO'] /= p['KO'].iloc[0]


    

In [46]:

    

p['KO'] = log(p['KO'])


    

In [79]:

    

p[['SPY','AAPL']].plot();


    

In [55]:

    

p.head()


    

    
Out[55]:






  

    

      

      
E
      
XOM
      
COP
      
SPY
      
KO
    
    

      
Date
      

      

      

      

      

    
  
  

    

      
1995-12-01
      
0.000000
      
0.000000
      
0.000000
      
0.000000
      
0.000000
    
    

      
1995-12-04
      
-0.022007
      
0.011191
      
-0.007326
      
0.012223
      
0.006167
    
    

      
1995-12-05
      
0.000000
      
0.025398
      
-0.007326
      
0.018783
      
0.020814
    
    

      
1995-12-06
      
0.005108
      
0.034759
      
-0.011009
      
0.021043
      
0.046333
    
    

      
1995-12-07
      
0.005108
      
0.038053
      
-0.018417
      
0.015761
      
0.033655
    
  

In [56]:

    

exp(p).iloc[-1]


    

    
Out[56]:





E      6.718162
XOM    7.757184
COP    7.575459
SPY    5.414596
KO     3.585011
Name: 2016-12-09 00:00:00, dtype: float64

In [67]:

    

AAPL = data.DataReader('AAPL','yahoo',start,end)


    

In [68]:

    

p['AAPL'] = AAPL['Adj Close']


    

In [69]:

    

p['AAPL'] /= p['AAPL'].iloc[0]


    

In [70]:

    

p['AAPL'] = log(p['AAPL'])


    

In [ ]: