def reverse_singleCode(self, code, startDate, endDate):
days = list(TradedayDataProcess().getTradedays(startDate, endDate))
#factors=['closeStd','index','marketValue','industry']
dailyRepo = dailyFactorsProcess()
dailyFactor = dailyRepo.getSingleStockDailyFactors(
code, startDate, endDate)
dailyKLine = KLineDataProcess('daily')
dailyData = dailyKLine.getDataByDate(code, startDate, endDate)
if dailyData.empty == True:
logger.error(
f'there is no data of {code} from {startDate} to {endDate}')
return pd.DataFrame()
tick = TickDataProcess()
tickfactor = tickFactorsProcess()
mydata = []
position = 0
profit = 0
myStatusList = []
myTradeList = []
myStatus = {}
myTrade = {}
positionYesterday = 0
select1 = []
select2 = []
selectall = []
for today in days:
#logger.info(f'{code} in {today} start!')
todayInfo = dailyFactor[dailyFactor['date'] == today]
if todayInfo.empty == True:
logger.error(
f'there is no factor data of {code} in date {today}')
continue
pass
todayKLine = dailyData[dailyData['date'] == today]
if todayKLine.empty == True:
logger.error(
f'there is no KLine data of {code} in date {today}')
continue
pass
myStatus['date'] = today
myStatus['closeStd20'] = todayInfo['closeStd20'].iloc[0]
myStatus['weight50'] = todayInfo['weight50'].iloc[0]
myStatus['weight300'] = todayInfo['weight300'].iloc[0]
myStatus['weight500'] = todayInfo['weight500'].iloc[0]
myStatus['ts_closeStd20'] = todayInfo['closeStd20'].iloc[0]
myStatus['adjFactor'] = todayKLine['adjFactor'].iloc[0]
myStatus['preClose'] = todayKLine['preClose'].iloc[0]
positionNow = positionYesterday
if (todayInfo.empty
== False) & (todayKLine['status'].iloc[0] != '停牌'):
#tickData=tick.getDataByDateFromLocalFile(code,today)
tickData = tick.getTickShotDataFromInfluxdbServer(code, today)
#factors=tickfactor.getDataByDateFromLocalFile(code,today,'buySellForce')
factors = tickfactor.getFactorsUsedByDateFromLocalFile(
code, today)
all = pd.merge(tickData,
factors,
how='left',
left_index=True,
right_index=True)
all['closeStd20'] = todayInfo['closeStd20'].iloc[0]
all['ts_closeStd20'] = todayInfo['ts_closeStd20'].iloc[0]
all['adjFactor'] = todayKLine['adjFactor'].iloc[0]
all['preClose'] = todayKLine['preClose'].iloc[0]
all['increaseToday'] = all['midPrice'] / all['preClose'] - 1
all['midIncreasePrevious5m'] = all['midPrice'] / all[
'midPrice'].shift(60) - 1
#select0=all[all['increaseToday']>2*all['closeStd20']]
selectall.append(all)
select0 = all[all['midIncreasePrevious5m'] > 0.5 *
all['closeStd20']]
select1.append(select0)
select0 = all[all['midIncreasePrevious5m'] < -0.5 *
all['closeStd20']]
select2.append(select0)
pass
else:
logger.warning(f'There is no data of {code} in {today}')
mycolumns = [
'midIncreaseNext1m', 'midIncreaseNext5m', 'ts_buyForceIncrease',
'ts_sellForceIncrease', 'ts_buySellVolumeRatio5',
'midIncreasePrevious3m', 'differenceHighLow',
'ts_differenceHighLow', 'differenceMidVwap',
'ts_differenceMidVwap', 'midStd60', 'ts_midStd60'
]
select1 = pd.concat(select1)
select2 = pd.concat(select2)
selectall = pd.concat(selectall)
selectall = selectall[mycolumns]
s = select1[(select1['ts_sellForceIncrease'] > 0.6)
& (select1['ts_buySellVolumeRatio5'] > 0.6) &
(select1['increaseToday'] > select1['closeStd20'])]
print(s['midIncreaseNext5m'].mean())
ss = select2[(select2['ts_buySellVolumeRatio5'] > 0.6)
& (select2['increaseToday'] < -select2['closeStd20'])]
print(ss['midIncreaseNext5m'].mean())
return mydata
########################################################################
def dataPrepared(self, stockCodes, startDate, endDate):
warnings.filterwarnings('ignore')
recordFilePath = self.__localFileStrResult
mytradedays = TradedayDataProcess.getTradedays(startDate, endDate)
mylist = stockCodes
myMinute = dkl.KLineDataProcess('minute')
num = 0
dailyFactor = dailyFactorsProcess()
#factors=['closeStd','index','marketValue','industry']
allDailyData = dailyFactor.getMultipleStockDailyFactors(
mylist, startDate, endDate)
#store = pd.HDFStore(self.__factorsAddress,'a')
#allDailyData=store.select(self.__key,where=['date>="%s" and date<="%s"'%(startDate,endDate)])
#store.close()
store = pd.HDFStore(recordFilePath, 'a')
oldKeys = store.keys()
for code in mylist:
num = num + 1
print("{0}({1} of {2}) start!".format(str(code), num, len(mylist)))
#print(datetime.datetime.now())
if ('/' + code) in oldKeys:
continue
pass
m = myMinute.getDataByDate(code, startDate, endDate)
if len(m) == 0:
continue
m = m[m['date'].isin(mytradedays)]
m['vwap'] = m['amount'] / m['volume']
m.loc[(m['date'] == m['date'].shift(5)),
'increase5m'] = (m['open'] / m['open'].shift(5) - 1)
m.loc[(m['date'] == m['date'].shift(1)),
'increase1m'] = (m['open'] / m['open'].shift(1) - 1)
d = allDailyData.xs(code, level='code')
dailyInfo = d.loc[m['date']]
deleteColumns = [
'code', 'date', 'open', 'high', 'low', 'close', 'volume',
'amount', 'change', 'pctChange', 'vwap'
]
mycolumns = [
col for col in dailyInfo.columns if col not in deleteColumns
]
dailyInfo = dailyInfo[mycolumns]
dailyInfo.rename(columns={'preClose': 'yesterdayClose'},
inplace=True)
dailyInfo.index = m.index
m = pd.concat([m, dailyInfo], axis=1)
m['increaseInDay'] = (m['open'] / m['yesterdayClose'] - 1)
m = m[m['status'] != 'N']
m['canBuy'] = 0
m['canSell'] = 0
m['canBuyPrice'] = None
m['canSellPrice'] = None
m.loc[((m['open'] < round(1.097 * m['yesterdayClose'], 2)) &
(m['open'] > 0)), 'canBuy'] = 1
m.loc[((m['open'] > round(0.903 * m['yesterdayClose'], 2)) &
(m['open'] > 0)), 'canSell'] = 1
m.loc[m['canBuy'] == 1, 'canBuyPrice'] = m.loc[m['canBuy'] == 1,
'open']
m.loc[m['canBuy'] == 1, 'canBuyPriceAdj'] = m.loc[m['canBuy'] == 1,
'adjFactor']
m['canBuyPrice'] = m['canBuyPrice'].fillna(method='bfill')
m['canBuyPriceAdj'] = m['canBuyPriceAdj'].fillna(method='bfill')
m.loc[m['canSell'] == 1, 'canSellPrice'] = m.loc[m['canSell'] == 1,
'open']
m.loc[m['canSell'] == 1,
'canSellPriceAdj'] = m.loc[m['canSell'] == 1, 'adjFactor']
m['canSellPrice'] = m['canSellPrice'].fillna(method='bfill')
m['canSellPriceAdj'] = m['canSellPriceAdj'].fillna(method='bfill')
m['timeStamp'] = m['date'] + m['tick']
mselect = m.set_index(['timeStamp', 'code'])
store.append(code, mselect, append=False, format="table")
pass
store.close()
pass
def reverse_singleCode(self,
code,
startDate,
endDate,
parameters=[300, 100000000, 1.5]):
myindex = parameters[0]
totalCash = parameters[1]
std1 = parameters[2]
days = list(TradedayDataProcess().getTradedays(startDate, endDate))
#factors=['closeStd','index','marketValue','industry']
dailyRepo = dailyFactorsProcess()
dailyFactor = dailyRepo.getSingleStockDailyFactors(
code, startDate, endDate)
dailyKLine = KLineDataProcess('daily')
dailyData = dailyKLine.getDataByDate(code, startDate, endDate)
if dailyData.empty == True:
logger.error(
f'there is no data of {code} from {startDate} to {endDate}')
return pd.DataFrame()
tick = TickDataProcess()
mydata = []
position = 0
profit = 0
myStatusList = []
myTradeList = []
myStatus = {}
myTrade = {}
positionYesterday = 0
for today in days:
#logger.info(f'{code} in {today} start!')
todayInfo = dailyFactor[dailyFactor['date'] == today]
if todayInfo.empty == True:
logger.error(
f'there is no factor data of {code} in date {today}')
continue
pass
todayKLine = dailyData[dailyData['date'] == today]
if todayKLine.empty == True:
logger.error(
f'there is no KLine data of {code} in date {today}')
continue
pass
myStatus['date'] = today
myStatus['closeStd20'] = todayInfo['closeStd20'].iloc[0]
myStatus['weight50'] = todayInfo['weight50'].iloc[0]
myStatus['weight300'] = todayInfo['weight300'].iloc[0]
myStatus['weight500'] = todayInfo['weight500'].iloc[0]
myStatus['ts_closeStd20'] = todayInfo['closeStd20'].iloc[0]
myStatus['adjFactor'] = todayKLine['adjFactor'].iloc[0]
myStatus['preClose'] = todayKLine['preClose'].iloc[0]
positionNow = positionYesterday
if (todayInfo.empty
== False) & (todayKLine['status'].iloc[0] != '停牌'):
if myindex == 300:
maxPosition = myStatus[
'weight300'] * totalCash * 0.01 / myStatus['preClose']
elif myindex == 500:
maxPosition = myStatus[
'weight300'] * totalCash * 0.01 / myStatus['preClose']
elif myindex == 50:
maxPosition = myStatus[
'weight50'] * totalCash * 0.01 / myStatus['preClose']
else:
maxPosition = myStatus['totalCash'] * 0.001 / myStatus[
'preClose']
maxPosition = round(maxPosition, -2)
if maxPosition == 0:
continue
tickData = tick.getDataByDateFromLocalFile(code, today)
#['code' ,'date','tick' ,'lastPrice','S1','S2','S3','S4','S5','S6','S7','S8','S9','S10','B1','B2','B3','B4','B5','B6','B7','B8','B9','B10','SV1','SV2','SV3','SV4','SV5','SV6','SV7','SV8','SV9','SV10','BV1','BV2','BV3','BV4','BV5','BV6','BV7','BV8','BV9','BV10','volume' ,'amount','volumeIncrease','amountIncrease']
tickList = tickData.as_matrix()
for i in range(0, len(tickList) - 60):
now = tickList[i]
midPrice = (now[4] + now[14]) / 2
lastPrice = now[3]
tickShot = now[4:43]
upCeiling = False
downCeiling = False
if now[24] == 0:
upCeiling = True
pass
if now[34] == 0:
downCeiling = True
pass
mytime = datetime.datetime.strptime(
now[1] + now[2], '%Y%m%d%H%M%S%f')
increaseToday = tickList[i][3] / myStatus['preClose'] - 1
if (i >= 100) & (tickList[i - 100][3] > 0):
increase5m = tickList[i][3] / tickList[i - 100][3] - 1
else:
increase5m = np.nan
if ((positionNow == 0) & (positionYesterday == 0) &
(i <= 4500) & (i >= 100) &
(increaseToday > std1 * myStatus['closeStd20']) &
(maxPosition > 0) & (downCeiling == False)):
#开空头
[price, deltaPosition,
amount] = TradeUtility.sellByTickShotData(
tickShot, maxPosition, 0.001)
positionNow = -deltaPosition
myTrade['date'] = today
myTrade['opentime'] = mytime
myTrade['position'] = positionNow
myTrade['open'] = price
myTrade['openAdj'] = myStatus['adjFactor']
myTrade['increase5m'] = increase5m
myTrade['increaseToday'] = increaseToday
openIndex = i
maxPosition = maxPosition - deltaPosition
pass
elif ((positionNow == 0) & (positionYesterday == 0) &
(i <= 4500) & (i >= 100) &
(increaseToday < -std1 * myStatus['closeStd20']) &
(maxPosition > 0) & (upCeiling == False)):
#开多头
[price, deltaPosition,
amount] = TradeUtility.buyByTickShotData(
tickShot, maxPosition, 0.001)
positionNow = deltaPosition
myTrade['date'] = today
myTrade['opentime'] = mytime
myTrade['position'] = positionNow
myTrade['open'] = price
myTrade['openAdj'] = myStatus['adjFactor']
myTrade['increase5m'] = increase5m
myTrade['increaseToday'] = increaseToday
maxPosition = maxPosition - deltaPosition
openIndex = i
pass
elif (positionNow > 0):
profit = (lastPrice * myStatus['adjFactor'] -
myTrade['open'] * myTrade['openAdj']) / (
myTrade['open'] * myTrade['openAdj'])
if (((profit < 0) & (i >= openIndex + 400)) |
(i >= 4700) | (i >= openIndex + 1200) |
(positionYesterday != 0)):
if downCeiling == False: #未跌停
#平多头,记录一笔交易
[price, deltaPosition,
amount] = TradeUtility.sellByTickShotData(
tickShot, positionNow, 0.1)
myTrade['closetime'] = mytime
myTrade['close'] = price
myTrade['closeAdj'] = myStatus['adjFactor']
positionNow = 0
positionYesterday = 0
openIndex = 0
tradeCopy = copy.deepcopy(myTrade)
myTradeList.append(tradeCopy)
myTrade = {}
pass
elif (positionNow < 0):
profit = (-lastPrice * myStatus['adjFactor'] +
myTrade['open'] * myTrade['openAdj']) / (
myTrade['open'] * myTrade['openAdj'])
if (((profit < 0) & (i >= openIndex + 400)) |
(i >= 4700) | (i >= openIndex + 1200) |
(positionYesterday != 0)):
if upCeiling == False:
#平空头，记录一笔交易
[price, deltaPosition,
amount] = TradeUtility.buyByTickShotData(
tickShot, -positionNow, 0.1)
myTrade['closetime'] = mytime
myTrade['close'] = price
myTrade['closeAdj'] = myStatus['adjFactor']
positionNow = 0
positionYesterday = 0
openIndex = 0
tradeCopy = copy.deepcopy(myTrade)
myTradeList.append(tradeCopy)
myTrade = {}
pass
if positionNow != 0:
logger.info(
f'{code} of {today} can not close the position!')
positionYesterday = positionNow
pass
else:
logger.warning(f'There is no data of {code} in {today}')
m = pd.DataFrame(data=myTradeList,
columns=[
'date', 'opentime', 'position', 'open', 'openAdj',
'increase5m', 'increaseToday', 'closetime',
'close', 'closeAdj'
])
m['profit'] = m['position'] * (m['close'] * m['closeAdj'] -
m['open'] * m['openAdj']) / m['openAdj']
m['fee'] = m['position'].abs() * m[['open', 'close'
]].max(axis=1) * 0.0012
m['netProfit'] = m['profit'] - m['fee']
m['code'] = code
mycolumns = [
'date', 'closeStd20', 'ts_closeStd20', 'industry', 'industryName'
]
dailyFactor = dailyFactor[mycolumns]
mydata = pd.merge(m,
dailyFactor,
how='left',
left_on='date',
right_on='date')
#mydata=mydata[((mydata['increase5m']>mydata['closeStd20']) & (mydata['position']<0)) |((mydata['increase5m']<-mydata['closeStd20']) & (mydata['position']>0))]
'''
print(mydata)
print(mydata['profit'].sum())
print(mydata['fee'].sum())
print(mydata['netProfit'])
'''
return mydata
########################################################################
def updateDailyFactors(self, codeList, factors=DAILYFACTORSNEEDTOUPDATE):
dailyFactor = dailyFactorsProcess()
dailyFactor.parallelizationUpdateFactorsVersion2(codeList, factors)
pass