new_contents: #-*-coding:utf-8-*-
  #!/usr/bin/python
  # coding: UTF-8
  
  import numpy as np
  import pandas as pd
  import pandas_datareader.data as web
  import math
  
  #从雅虎财经获取DAX指数的数据
  DAX = web.DataReader(name='^GDAXI', data_source='yahoo',start = '2000-1-1')
  
  #查看一下数据的一些信息 上面这一方法返回的是一个pandas dataframe的数据结构
  print (DAX.info())
  
  #绘制收盘价的曲线
  DAX['Close'].plot(figsize=(8,5))
  
  #计算每日的涨跌幅
  DAX['Return'] = np.log(DAX['Close']/DAX['Close'].shift(1))
  
  print (DAX[['Close','Return']].tail())
  
  #将收盘价与每日涨跌幅度放在一张图上
  DAX[['Close','Return']].plot(subplots = True,style = 'b',figsize=(8,5))
  
  #42与252个交易日为窗口取移动平均
  DAX['42d']=pd.rolling_mean(DAX['Close'],window=42)
  
  DAX['252d']=pd.rolling_mean(DAX['Close'],window=252)
  
  #绘制MA与收盘价
  DAX[['Close','42d','252d']].plot(figsize=(8,5))
  
  #计算波动率，然后根据均方根法则进行年化
  DAX['Mov_Vol']=pd.rolling_std(DAX['Return'],window = 252)*math.sqrt(252)
  
  DAX[['Close','Mov_Vol','Return']].plot(subplots = True, style = 'b',figsize = (8,7))
subject: Add demo of DAX analysis and MA