# -*- coding: utf-8 -*-
"""
Created on Wed Jun 7 10:22:18 2017
@author: yunjinqi
E-mail:yunjinqi@qq.com
Differentiate yourself in the world from anyone else.
"""
import pandas as pd
import numpy as np
import datetime
import time
import math
import matplotlib.pyplot as plt
import random
#获取数据
df=pd.read_csv('C:/Users/HXWD/Desktop/rb000.csv',encoding='gbk')
df.head()
df.columns=['date','open','high','low','close','volume','amt']
df.head()
###########################原始数据
i=5
j=20
df['ma5']=df['close'].rolling(i).mean()
df['ma20']=df['close'].rolling(j).mean()
df.ix[df['ma5']>df['ma20'],'cross']=1
df.ix[df['ma5']<=df['ma20'],'cross']=-1
#df[['close','ma5','ma20']][-200:].plot()
df['ret']=(df['close']-df['close'].shift(1))/df['close'].shift(1)
df['profit']=df['ret']*df['cross']
#df['profit'].plot()
#target=df['profit'].sum()
target=df['profit'].dropna()
plt.hist(target,bins=100)
######怀特真实检验，自举法
#从里面抽出来ll个数据作为一组，计算平均收益，抽取5000组进行计算
target=df['profit'].dropna()
ll=len(target)
ss=target.mean()
target.sum()
new_target=target-ll*[ss]
new_target=pd.Series(list(new_target))
all_target=[]
j=0
while j<5000:
all_value=[]
i=0
while i<len(new_target):
value=new_target[random.randint(0,len(new_target)-1)]
#print(value)
all_value.append(value)
i=i+1
all_value=pd.Series(all_value)
all_target.append(all_value.sum())
j=j+1
print(j)
plt.hist(all_target)
jianyan_profit=df['profit'].sum()
jianyan_profit
jianyan_profit Out[91]: 4.864976648275746
#基于随机的收益与策略的收益差距非常大，我们有理由相信，策略是具有预测能力的。
#量化投资交流群：226224941，欢迎大家加入。
