Python 如何解释statsmodels coint结果？

我正在使用statsmodels coint，但不确定我的结果告诉了我什么。当我比较一对相似的股票时，我有兴趣了解协整结果。我使用了下面的代码，得到了非常不同的结果。谁能解释一下什么是好的/坏的结果以及为什么？ 我很难理解其中的一些概念，为什么当我运行下面的代码时会得到非常不同的结果？当我使用每日调整收盘价时，与使用调整收盘价的百分比移动相比？我希望他们是一样的

from statsmodels.tsa.stattools import coint
import pandas as pd
import pandas_datareader.data as web
import datetime as dt

start = dt.datetime(2013, 1,1)
end = dt.datetime.today()

intquery1 = web.DataReader(['HEI.DU','HEI.BE'], 'yahoo', start, end) ##<<<<<put start to finish date.
int1 = intquery1['Adj Close']

print('############THIS cointegration on prices#####################')
score, pvalue, _ = coint(int1['HEI.DU'], int1['HEI.BE'])
print ('this is the coint score =',score,'\nthis is the pvalue =', pvalue, 
       '\nthis is the 1% 5% & 10% = ',_)


df_normalize = (int1[:] / int1[:].shift(1) - 1).fillna(0)

print('############THIS cointegration on Daily percetage move#####################')
score, pvalue, _ = coint(df_normalize['HEI.DU'], df_normalize['HEI.BE'])
print ('this is the coint score =',score,'\nthis is the pvalue =', pvalue, 
       '\nthis is the 1% 5% & 10% = ',_)

---

协整应该在价格差异上进行，而不是回报差异上

############THIS cointegration on prices#####################
this is the coint score = 0 
this is the pvalue = 0.985900258026 
this is the 1% 5% & 10% =  [-3.90485841 -3.34081967 -3.04770405]
############THIS cointegration on Daily percetage move#####################
this is the coint score = -7.88182772484 
this is the pvalue = 5.97585656581e-11 
this is the 1% 5% & 10% =  [-3.90485841 -3.34081967 -3.04770405]
/home/ross/anaconda3/lib/python3.6/site-packages/numpy/linalg/linalg.py:1574: RuntimeWarning: invalid value encountered in greater
  return (S > tol).sum(axis=-1)
/home/ross/anaconda3/lib/python3.6/site-packages/statsmodels/tsa/stattools.py:1018: UserWarning: y0 and y1 are perfectly colinear.  Cointegration test is not reliable in this case.
  warnings.warn("y0 and y1 are perfectly colinear.  Cointegration test "