#-*-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))
Add demo of DAX analysis and MA
Add demo of DAX analysis and MA
