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期权高频数据准备

发布于 02-20 22:26 字数 8719 浏览 864 评论 0 收藏 0

本notebook根据指定的时间区间整理并保存option_data.csv 文件,请与 期权市场一周纵览 notebook配合使用。

import pandas as pd
import numpy as np
pd.options.display.float_format = '{:,>.4f}'.format
calendar = Calendar('China.SSE')
class _format_checker:

    def __init__(self, calendar):
        self.calendar = calendar

    def _format_check(self, instrumentID):
        contractType = instrumentID[6] + 'O'
        contractYear = int(instrumentID[7:9]) + 2000
        contractMonth = int(instrumentID[9:11])
        contractExp = Date.NthWeekDay(4, Wednesday, contractMonth, contractYear)
        contractExp = self.calendar.adjustDate(contractExp, BizDayConvention.Following)
        contractStrike = float(instrumentID[-4:]) / 1000.0
        return contractType, contractExp, contractStrike

checker = _format_checker(calendar)
tradingDays = calendar.bizDatesList(Date(2015,3,5), Date(2015,3,12))
names, instrumentIDs = (OptionsDataSnapShot().optionId.unique(), OptionsDataSnapShot().instrumentID.unique())
data = pd.DataFrame(names, columns = ['optionId'])
instrumentIDs = pd.Series(instrumentIDs)
data = data.join(pd.DataFrame(list(instrumentIDs.apply(checker._format_check)), columns= ['contractType', 'expDate', 'strikePrice']))
data[:5]
optionIdcontractTypeexpDatestrikePrice
010000001COMarch 25th, 20152.2000
110000002COMarch 25th, 20152.2500
210000003COMarch 25th, 20152.3000
310000004COMarch 25th, 20152.3500
410000005COMarch 25th, 20152.4000
tradingDaysStr = [''.join(date.toISO().split('-')) for date in tradingDays]
tradingDaysStr

['20150305', '20150306', '20150309', '20150310', '20150311']
res = pd.DataFrame()
spotData = []
for day in tradingDaysStr:
    tmp = spotData
    try:
        spotData = DataAPI.MktTicksHistOneDayGet('510050.XSHG', date = day, field = ['dataDate', 'datasTime', 'secOffset', 'lastPrice'])
        spotData = spotData.drop(0)
    except Exception, e:
        print e
        spotData = tmp
    for opt in names:
        try:
            sample = DataAPI.MktOptionTicksHistOneDayGet(optionId = opt,date = day)#field = ['optionId', 'dataDate', 'dataTime' 'secOffset', 'lastPrice'])
            sample = sample.drop_duplicates(['secOffset'])
            spotPrice = np.zeros((len(sample),))
            j = 0
            index = spotData.index
            for i, secOffset in enumerate(sample.secOffset):
                currentSpotSecOffset = spotData.loc[index[j], 'secOffset']*1000
                while currentSpotSecOffset < secOffset and j < len(index)-1:
                    j = j + 1
                    currentSpotSecOffset = spotData.loc[index[j], 'secOffset']*1000
                if j>=1:
                    spotPrice[i] =  spotData.loc[index[j-1], 'lastPrice']
                else:
                    spotPrice[i] = spotData.loc[index[j], 'lastPrice']
            sample['spotPrice'] = spotPrice
            res = res.append(sample)
        except Exception, e:
            print e
    print day + ' finished!'

20150305 finished!
-1:No Data Returned for request: /market/getOptionTicksHistOneDay.csv?field=&optionId=10000030&date=20150306&startSecOffset=&endSecOffset=
-1:No Data Returned for request: /market/getOptionTicksHistOneDay.csv?field=&optionId=10000032&date=20150306&startSecOffset=&endSecOffset=
-1:No Data Returned for request: /market/getOptionTicksHistOneDay.csv?field=&optionId=10000033&date=20150306&startSecOffset=&endSecOffset=
-1:No Data Returned for request: /market/getOptionTicksHistOneDay.csv?field=&optionId=10000035&date=20150306&startSecOffset=&endSecOffset=
-1:No Data Returned for request: /market/getOptionTicksHistOneDay.csv?field=&optionId=10000054&date=20150306&startSecOffset=&endSecOffset=
-1:No Data Returned for request: /market/getOptionTicksHistOneDay.csv?field=&optionId=10000056&date=20150306&startSecOffset=&endSecOffset=
20150306 finished!
20150309 finished!
-1:No Data Returned for request: /market/getOptionTicksHistOneDay.csv?field=&optionId=10000039&date=20150310&startSecOffset=&endSecOffset=
-1:No Data Returned for request: /market/getOptionTicksHistOneDay.csv?field=&optionId=10000056&date=20150310&startSecOffset=&endSecOffset=
-1:No Data Returned for request: /market/getOptionTicksHistOneDay.csv?field=&optionId=10000064&date=20150310&startSecOffset=&endSecOffset=
20150310 finished!
-1:No Data Returned for request: /market/getOptionTicksHistOneDay.csv?field=&optionId=10000039&date=20150311&startSecOffset=&endSecOffset=
-1:No Data Returned for request: /market/getOptionTicksHistOneDay.csv?field=&optionId=10000064&date=20150311&startSecOffset=&endSecOffset=
20150311 finished!
res.optionId = res.optionId.astype('str')

res = res.merge(data, how = 'left', on = 'optionId')

dateData, idData, volumeData = res.dataDate, res.optionId, res['volume']

previous = [dateData[0], idData[0], 0]
newVolume = np.zeros((len(dateData),))
count = 0
for date, ids, volume in zip(dateData, idData, volumeData ):
    if date == previous[0] and ids == previous[1]:
        newVolume[count] = volume - previous[2]
    else:
        newVolume[count] = volume
    previous[0] = date
    previous[1] = ids 
    previous[2] = volume
    count = count + 1

res.volume = newVolume

res['pdDateTime'] = res.expDate.apply(lambda x: x.toDateTime())

optData = pd.DataFrame()
optData['contractType'] = res['contractType']
optData['valuationDate'] = res['dataDate']
optData['expDate'] = res['expDate']
optData['strikePrice'] = res['strikePrice']
optData['lastPrice'] = res['lastPrice']
optData['optionId'] = res['optionId'].astype('str')
optData['Type'] = Option.Call
optData['spotPrice'] = res.spotPrice
optData.loc[optData['contractType'] == 'PO','Type'] = Option.Put

optData['valuationDate'] = [Date(int(date.split('-')[0]),int(date.split('-')[1]),int(date.split('-')[2])) for date in optData['valuationDate']]

dc = DayCounter('Actual/365 (Fixed)')
optData['ttm'] = [dc.yearFraction(date1, date2) for date1, date2 in zip(optData['valuationDate'], optData['expDate'])]

optData['lastPrice(vol)'] = BSMImpliedVolatity(optData['Type'], optData['strikePrice'], optData['spotPrice'], 0.0, 0.0, optData['ttm'], optData['lastPrice'])
optData['bid1(vol)'] = BSMImpliedVolatity(optData['Type'], optData['strikePrice'], optData['spotPrice'], 0.0, 0.0, optData['ttm'], res.bidPrice1)
optData['ask1(vol)'] = BSMImpliedVolatity(optData['Type'], optData['strikePrice'], optData['spotPrice'], 0.0, 0.0, optData['ttm'], res.askPrice1)

res1 = res.merge(optData[[u'spotPrice', u'ttm', u'lastPrice(vol)', u'bid1(vol)', u'ask1(vol)']], left_index=True, right_index=True)

res1 = res1.dropna(how = 'any')

res1['bidAskSpread(bps)'] = (res1.askPrice1 - res1.bidPrice1) * 10000
res1['bidAskSpread(vol bps)'] = (res1['ask1(vol)'] - res1['bid1(vol)']) * 10000

res1.to_csv('option_data.csv')

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