python-优矿-hurst指数与期货33品种的预测

#编写hurst指数
from numpy import std, subtract, polyfit, sqrt, log
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from datetime import timedelta
from statsmodels import regression
from lib.hurst import *
#data=DataAPI.MktIdxdGet(tradeDate=u"",indexID=u"",ticker=u"000300",beginDate=u"",endDate=u"",exchangeCD=u"XSHE,XSHG",field=u"",pandas="1")['closeIndex'][-1500:]
#data=DataAPI.MktEqudGet(tradeDate=u"",secID=u"",ticker=u"000001",beginDate=u"",endDate=u"",isOpen="",field=u"",pandas="1")['closePrice'][-1500:]
def get_hurst(data):
        #data=data[-500:]
        #data.index=range(len(data))
        hhh=[]
        for i in range(len(data)):
             if i>220  :
                    new_data=data[i-220:i]
                    hhh.append(hurst(new_data,5))
        #hhh=pd.Series(hhh)
        #ma1_hhh=hhh.rolling(1).mean()
        #ma5_hhh=hhh.rolling(20).mean()
        #ma20_hhh=hhh.rolling(100).mean()
        #plt.plot(ma1_hhh)
        #plt.plot(ma5_hhh)
        #plt.plot(ma20_hhh)
        #plt.show()
        fig,ax1=plt.subplots()
        data=data[221:]
        data.index=range(len(data))
        data.plot(figsize=(10,4),color='red',linewidth=1)
        plt.grid(True)
        plt.ylabel("Index")
        plt.axis('tight')
        ax2=ax1.twinx()
        hhh=pd.Series(hhh)
        ma1_hhh=hhh.rolling(1).mean()
        ma5_hhh=hhh.rolling(20).mean()
        ma20_hhh=hhh.rolling(100).mean()
        ma1_hhh.plot(figsize=(10,4),color='black',linewidth=1,marker='.')
        ma5_hhh.plot(figsize=(10,4),color='green',linewidth=1,marker='.')
        ma20_hhh.plot(figsize=(10,4),color='blue',linewidth=1,marker='.')
        plt.grid(True)
        plt.ylabel('Hurst Index')
        plt.axis('tight')
        plt.show()
        return hhh
namelist=list_files(path='./期货指数')
for i in namelist:
    filename='./期货指数/'+i
    data=pd.read_csv(filename,encoding='gbk')
    data=data.ix[::,4]
    print i[:2] 
    get_hurst(data)