python-大智慧-VMACD-量指数平滑移动平均线

# -*- coding: utf-8 -*-"""Created on Wed May 24 15:47:51 2017@author: yunjinqi  E-mail:[e-mail]  Differentiate yourself in the world from anyone else."""import pandas as pd  import numpy as np  import datetime  import time  #获取数据  df=pd.read_csv('C:/Users/HXWD/Desktop/000001.csv',encoding='gbk')  df.columns=['date','code','name','close','high','low','open','preclose',  'change','change_per','volume','amt']  df=df[['date','open','high','low','close','volume','amt']]  df.head()  def get_EMA(df,N):      for i in range(len(df)):          if i==0:              df.ix[i,'ema']=df.ix[i,'volume']          if i>0:              df.ix[i,'ema']=(2*df.ix[i-1,'volume']+(N-1)*df.ix[i,'volume'])/(N+1)      ema=list(df['ema'])      return ema  def get_VMACD(df,short=12,long=26,M=9):      a=get_EMA(df,short)      b=get_EMA(df,long)      df['diff']=pd.Series(a)-pd.Series(b)      #print(df['diff'])      for i in range(len(df)):          if i==0:              df.ix[i,'dea']=df.ix[i,'diff']          if i>0:              df.ix[i,'dea']=(2*df.ix[i-1,'diff']+(M-1)*df.ix[i,'diff'])/(M+1)      df['macd']=2*(df['diff']-df['dea'])      return df  get_VMACD(df,12,26,9)  df.tail() 

 '''    量指数平滑异同平均线原理：    以成交量为权数的MACD指标。算法：DIFF线　成交量的短期(SHORT)、长期(LONG)指数平滑移动平均线间的差。DEA线　 DIFF线的M日指数平滑移动平均线。MACD线　DIFF线与DEA线的差，彩色柱状线。用法：1.DIFF、DEA均为正，DIFF向上突破DEA，买入信号。2.DIFF、DEA均为负，DIFF向下跌破DEA，卖出信号。3.DEA线与K线发生背离，行情反转信号。4.分析MACD柱状线，由正变负，卖出信号；由负变正，买入信号。'''

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