import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

cqlq=pd.read_csv("cqlq.txt",sep="\s+",encoding="gbk")
dxnt=pd.read_csv("dxnt.txt",sep="\s+",encoding="gbk")
ggdq=pd.read_csv("ggdq.txt",sep="\s+",encoding="gbk")
giyy=pd.read_csv("gjyy.txt",sep="\s+",encoding="gbk")



cqlq.columns = ["date","oppr","hipr","lopr","clpr","TR"]
dxnt.columns = ["date","oppr","hipr","lopr","clpr"]
ggdq.columns = ["date","oppr","hipr","lopr","clpr","TR"]
giyy.columns = ["date","oppr","hipr","lopr","clpr","TR"]

a=cqlq
b=dxnt
c=ggdq
d=giyy

ua=(a["clpr"]-a["clpr"].shift(1))/a["clpr"]
ub=(b["clpr"]-b["clpr"].shift(1))/b["clpr"]
uc=(c["clpr"]-c["clpr"].shift(1))/c["clpr"]
ud=(d["clpr"]-d["clpr"].shift(1))/d["clpr"]

u=pd.concat([ua,ub,uc,ud],axis=1)
u.dropna()
miu=u.mean()+0.005
jz=u.cov()
yi = np.ones(4)

miu= np.mat(miu)
jz = np.mat(jz)
yi = np.mat(yi)
nijz = jz.I

a = miu*nijz*miu.T
b =yi*nijz*miu.T
c = yi*nijz*yi.T
deta=a*c-b**2


stock_y=[i*0.0001 for i in range(100)]
stock_x=[(np.sqrt(( c/deta)*(rp-b/c)**2+1/c)).max() for rp in stock_y]

plt.rcParams['font.sans-serif']=['SimHei']
plt.plot(stock_x,stock_y)
plt.xlabel("方差")
plt.ylabel("期望")
print(miu)
print(jz)

plt.show()

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2020-05-26