需要关于用Python寻找自然对数收益率和线性回归斜率的反馈吗

Question

我试图获得时间序列价格的自然对数回报，并将其与pythonscipy库一起使用(统计回归)从而得到线性回归线的斜率。这是我第一次尝试这一点，并将非常感谢另一套眼睛和反馈。我认为自然日志返回部分代码有问题。你知道吗

symbols = ["'AAN'"]

# Getting x values (number of days in time series = 90)
xValues = []
x = 1
while x <= 90:
    xValues.append(x)
    x += 1

# print xValues

# The y values used in the stats.linregress method; 
# Currently I am getting them from a database, so I will 
# print out the returned values
yValues = []
for s in symbols:
    data90 = setup.last_90_closes(s)

for each in data90:
    # data90 returns a list of tuples, so I needed to 
    # extract the first element from each tuple
    i = each[0]
    yValues.append(i)

NewYValues = np.log(yValues)
# print NewYValues
# print yValues

slope, intercept, r_value, p_value, std_err = stats.linregress(xValues, NewYValues)


print slope

结果： 原始Y值=

[31.93, 30.26, 29.86, 29.4, 29.37, 29.12, 29.51, 28.88, 29.01, 28.64, 28.63, 28.04, 27.97, 27.47, 26.75, 26.3, 25.71, 26.01, 25.26, 24.84, 24.81, 25.17,
24.71, 24.33, 22.63, 22.95, 23.1, 23.52, 23.23, 23.22, 23.56, 23.42, 22.82, 22.76, 22.77, 22.68, 22.81, 25.62, 25.13, 25.25, 25.17, 24.97, 24.95, 25.42,
24.69, 24.99, 25.14, 24.99, 25.66, 25.59, 25.09, 25.01, 25.01, 24.92, 25.01, 24.71, 24.99, 25.25, 24.73, 25.41, 24.92, 24.17, 24.78, 24.47, 24.36, 24.84,
 25.17, 24.71, 25.04, 25.27, 25.24, 25.23, 25.19, 25.18, 24.83, 24.9, 25.02, 24.76, 24.88, 24.53, 24.56, 24.55, 24.64, 23.94, 23.8, 23.68, 24.08, 23.93,
21.93, 22.88]

新值=

[ 3.46354601  3.40982671  3.39651979  3.38099467  3.37997375  3.37142522
  3.38472919  3.36314931  3.3676406   3.35480434  3.35445512  3.33363206
  3.33113251  3.3130945   3.28653447  3.26956894  3.24688002  3.25848108
  3.22922212  3.21245526  3.2112468   3.22565281  3.20720802  3.19171016
  3.11927646  3.13331794  3.13983262  3.15785112  3.14544455  3.14501398
  3.15955036  3.15359036  3.12763734  3.12500461  3.12544388  3.12148348
  3.12719904  3.2433733   3.22406235  3.22882616  3.22565281  3.2176751
  3.21687382  3.23553627  3.2063983   3.21847574  3.2244602   3.21847574
  3.24493336  3.24220165  3.22246936  3.21927574  3.21927574  3.21567069
  3.21927574  3.20720802  3.21847574  3.22882616  3.20801708  3.2351428
  3.21567069  3.18511219  3.21003688  3.19744788  3.19294244  3.21245526
  3.22565281  3.20720802  3.22047455  3.22961792  3.22843004  3.22803376
  3.22644709  3.22605003  3.2120526   3.2148678   3.21967551  3.20922945
  3.21406427  3.19989686  3.2011191   3.20071185  3.20437114  3.1755507
  3.16968558  3.16463081  3.18138162  3.1751329   3.08785556  3.13026317]

坡度=

-0.00157242772248

我的问题是：结果似乎代表了代码的期望值吗？你知道吗