期权高频数据准备 · Python 量化交易教程

# 期权高频数据准备 > 来源：https://uqer.io/community/share/55027e68f9f06c7a9ae9a53b 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。 ```py import pandas as pd import numpy as np pd.options.display.float_format = '{:,>.4f}'.format ``` ```py 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) ``` ```py 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] ``` | | optionId | contractType | expDate | strikePrice | | --- | --- | | 0 | 10000001 | CO | March 25th, 2015 | 2.2000 | | 1 | 10000002 | CO | March 25th, 2015 | 2.2500 | | 2 | 10000003 | CO | March 25th, 2015 | 2.3000 | | 3 | 10000004 | CO | March 25th, 2015 | 2.3500 | | 4 | 10000005 | CO | March 25th, 2015 | 2.4000 | ```py tradingDaysStr = [''.join(date.toISO().split('-')) for date in tradingDays] tradingDaysStr ['20150305', '20150306', '20150309', '20150310', '20150311'] ``` ```py 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! ``` ```py 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') ```