def __init__(self):
# 费率和滑点
self.saveDetail = True # 是否保存明细
self.isEmptyUse = False # 是否清空记录
self.codeLists = ['JM', 'SM', 'V', 'I', 'AP', 'J','RB', 'SC', 'MA', 'JD','CU' , 'OI']
self.baseInfo = {}
# k线时间
# self.klineTypeList = ['5m']
self.klineTypeList = ['15m', '30m']
self.widthDeltaLineList = [0.025]
self.widthDeltaLine = 0
self.stopTimeLine = 5
self.widthTimesPeriodList = [3]
self.testDays = 90
# 起始时间
self.startDate = public.getDate(diff=-self.testDays) # 60天数据回测
self.endDate = public.getDate(diff=0)
self.total_tablename = 'train_total_1'
self.detail_tablename = 'train_future_1'
self.totalMethod = 'single'
self.method = 'simTick' if self.isSimTickUse else 'quick'
self.stage = 'single15'
self.uidKey = "%s_%s_%s_%s_%s_" + self.method + "_" + self.stage
self.isAll = 0
def __init__(self):
self.saveDetail = True # 是否保存明细
self.topUse = False
self.isEmptyUse = True # 是否清空记录
self.testDays = 10
self.processCount = 5
self.period = 14
self.bullwidth = 2
self.iniAmount = 50000 # 单边50万
# self.iniAmount = 2000000 * 0.0025 # 单边50万
self.stopLine = 2
self.klineList = ['3m', '5m']
# 起始时间
self.startDate = public.getDate(diff=-self.testDays) # 60天数据回测
self.endDate = public.getDate(diff=1)
self.total_tablename = 'train_total_2'
self.detail_tablename = 'train_future_2'
self.uniform_tablename = 'future_uniform'
self.method = 'hudge2'
self.uidKey = "%s_%s_%s_" + self.method
self.isAll = 0
def __init__(self):
# 费率和滑点
self.saveDetail = False # 是否保存明细
self.isSimTickUse = False # 是否使用1分钟模拟tick测试，否则直接使用kline回测
self.topUse = False
self.isEmptyUse = True # 是否情况记录
self.isKeeping = False
self.baseInfo = {}
self.periodList = [15, 30, 60] # 窗体参数
self.scaleList = [2.0]
self.shiftScale = 0.527 # 滑点模拟系数
self.deltaLine = 0.8
# k线时间
self.klineTypeList = ['5m', '15m', '30m', '60m']
self.scaleDiff2List = [0.8]
self.widthDeltaLineList = [0.1]
self.stopTimeLineList = [0]
self.widthDeltaLine = 0
self.scaleDiffList = [0.2]
# 起始时间
self.startDate = public.getDate(diff=-200) # 60天数据回测
self.endDate = public.getDate()
self.total_tablename = 'train_total_2'
self.detail_tablename = 'train_future_2'
self.method = 'simTick' if self.isSimTickUse else 'quick'
self.stage = 'paird2'
self.uidKey = "%s_%s_%s_%s_%s_" + self.method + "_" + self.stage
def __init__(self):
self.period = '1d'
self.pageCount =50
self.timePeriodsList = [60]
self.timePeriods = 150
self.dropLineList = [1.0, 1.5]
self.dropLine = 0.20
self.sarStartList = [0.02, 0.03, 0.04, 0.05]
self.sarStart = 0.02
self.sarEndList = [0.02, 0.03, 0.04, 0.05]
self.sarEnd = 0.05
self.iniAmount = 250000
self.shift = 0.002
self.ratio = 0.0006
self.atrDropLine = 2
self.saveMongo = True
self.methodName = 'obv'
self.startDate = public.getDate(diff=-200) # 60天数据回测
self.endDate = public.getDate(diff=0)
self.iterCondList = ['timePeriods', 'dropLine', 'sarStart', 'sarEnd']
def __init__(self):
self.codes = ['510050.XSHG']
self.klineType = '30m'
self.klineTypeList = ['15m', '30m']
self.timePeriodsList = [15, 30, 60]
self.timePeriods = 60
self.powlineList = [0.5]
self.powline = 1.0
self.turnlineList = [1.5, 1.75, 2.0]
self.turnline = 1.0
self.paramList = ['powline', 'turnline']
self.scaleDiff2 = 0.8
self.iniAmount = 40000
self.multiplier = 10000
self.ratio = 2
self.scale = 2.0
self.shift = 0.0005
self.index_list = ["MA"]
self.startDate = public.getDate(diff=-360) # 60天数据回测
self.endDate = public.getDate(diff=0)
self.method = 'bull4'
def iniShare(self, codes):
if codes[0] not in self.shareDict:
filename = self.Rice.basePath + '%s_%s.csv' % (codes[0],
public.getDate())
if os.path.exists(filename):
for code in codes:
filename = self.Rice.basePath + '%s_%s.csv' % (
code, public.getDate())
self.shareDict[code] = pd.read_csv(filename,
index_col=0,
encoding='gb2312')
else:
dfs = self.Rice.kline(codes, period=self.period, pre=200)
for code in codes:
if code in dfs:
# 删除前一日文件
filename_1 = self.Rice.basePath + '%s_%s.csv' % (
code, public.getDate(diff=-1))
if os.path.exists(filename_1):
os.remove(filename_1)
# 保存文件
filename = self.Rice.basePath + '%s_%s.csv' % (
code, public.getDate())
dfs[code].to_csv(filename)
self.shareDict[code] = dfs[code]
return self.shareDict
def __init__(self):
self.period = '1d'
self.pageCount = 50
self.timePeriodsList = [150]
self.timePeriods = 150
self.dropLineList = [0.6]
self.dropLine = 0.20
self.sarStartList = [0.02, 0.35, 0.05]
self.sarStart = 0.02
self.sarEndList = [0.02, 0.35, 0.05]
self.sarEnd = 0.05
self.iniAmount = 250000
self.shift = 0.002
self.ratio = 0.0006
self.saveMongo = False
self.methodName = 'filter_5'
self.startDate = public.getDate(diff=-300) # 60天数据回测
self.endDate = public.getDate(diff=0)
self.iterCondList = ['timePeriods', 'dropLine', 'sarStart', 'sarEnd']
def __init__(self):
super().__init__()
# 费率和滑点
self.saveDetail = True # 是否保存明细
self.topUse = False
self.isEmptyUse = True # 是否清空记录
self.testDays = 20
self.processCount = 5
self.iniAmount = 500000 # 单边50万
self.volcLineList = [4, 6]
self.volcLine = 5
self.stopLine = 3
self.maxperiodList = [5, 15, 30]
self.maxperiod = 5
self.indexCodeList = [('IH', '000016.XSHG'), ('IF', '399300.XSHE'),
('IC', '399905.XSHE')]
self.klineList = ['1m', '5m', '10m']
# 起始时间
self.startDate = public.getDate(diff=-self.testDays) # 60天数据回测
self.endDate = public.getDate(diff=0)
self.total_tablename = 'train_total_0'
self.detail_tablename = 'train_future_0'
self.method = 'follow1'
self.uidKey = "%s_%s_%s_%s_%s_" + self.method
def start(self, codes, main, time0, kt):
print("子进程启动:", self.cindex, codes, kt, time.time() - time0)
self.klineType = kt
self.Record = stock_uniform()
# 主力合约
self.Rice = interface_Rice()
# 查询获得配置 - 费率和每手单量
if kt[-1] == 'm':
self.startDate = public.getDate(diff=-200)
else:
self.startDate = public.getDate(diff=-1200)
# 查询获得N分钟K线
dfs = self.Rice.kline(codes,
period=self.klineType,
start=self.startDate,
end=self.endDate,
pre=60)
for rs in list(itertools.combinations(codes, 2)):
if main not in rs: continue
self.codes = rs
doc = self.total(dfs, kt)
if doc is not None:
self.Record.insert(doc)
def __init__(self):
# 费率和滑点
self.isEmptyUse = True # 是否清空记录
self.testDays = 20
self.processCount = 5
self.period = 14
self.bullwidth = 2
self.atrLineList = [2]
self.bullLine = 3.5
self.atrLine = 2
self.bullLine = 3.5
self.iniAmount = 500000 # 单边50万
# self.iniAmount = 2000000 * 0.0025 # 单边50万
self.stopLine = 2
self.indexCodeList = [('IH', '000016.XSHG'), ('IF', '399300.XSHE'),
('IC', '399905.XSHE')]
self.klineList = ['1m']
# 起始时间
self.startDate = public.getDate(diff=-self.testDays) # 60天数据回测
self.endDate = public.getDate(diff=0)
print(self.endDate)
self.total_tablename = 'train_total_2'
self.detail_tablename = 'train_future_2'
self.method = 'fellow'
self.uidKey = "%s_%s_%s_%s_%s_" + self.method
self.isAll = 0
def kline(self,
codes,
period='1m',
start=None,
end=None,
pre=200,
type='future'):
d = {}
# 指数清单
# 提前日期
#start = self.getPreDate(period=period, num=pre, start=start)
preDay = 1 if (pre == 0 or period == 'tick') else self.getPreDays(
period, pre)
# 开始日期
if start is None:
start = public.getDate(diff=-preDay)
else:
start = public.getDate(diff=-preDay, start=start.split(' ')[0])
if end is None:
end = public.getDate(diff=1)
# 查询K线
if period.find('d') > -1 and len(codes) > 1:
# 替换查询线
newCodes = self.alterCode(codes)
res = rq.get_price(newCodes,
frequency=period,
start_date=start,
end_date=end,
adjust_type='pre')
for c in newCodes:
mc = c if not c in self.indexMap else self.indexMap[c]
d[mc] = res.minor_xs(c)
else:
iMap = self.indexMap
for c in codes:
c0 = c1 = c
if type == 'future':
c0 = self.parseCode(c)
c1 = iMap[c0] if c0 in iMap else c
#print(c1)
d[c] = d[c0] = rq.get_price(c1,
frequency=period,
start_date=start,
end_date=end,
adjust_type='pre')
return d
def __init__(self):
# 费率和滑点
super().__init__()
self.saveDetail = True # 是否保存明细
self.savePoint = False
self.isSimTickUse = False # 是否使用1分钟模拟tick测试，否则直接使用kline回测
self.topUse = False
self.isEmptyUse = True
self.baseInfo = {}
#self.codeLists = ['JM', 'SM', 'V', 'I', 'AP', 'J', 'RB', 'SC', 'MA', 'JD', 'CU', 'OI', 'AU']
self.codeLists = ['SC', 'RB', 'FU', 'MA']
# 可变参数
self.periodList = [14] # 窗体参数
self.scaleList = [2]
self.klineTypeList = ['15m']
self.widthTimesPeriodList = [3]
self.superlineList = [2.0]
self.powline = 0.25
self.turnlineList = [2]
self.wdslineList = []
self.turnline = 1.5
self.paramList = ['superline']
self.shiftScale = 0.527 # 滑点模拟系数
self.scaleDiff2 = 0.8
self.scaleDiff = 0
self.processCount = 6
self.testDays = 90
self.adjustDates = []
# testCOun
self.testCount = 300
self.testDays = 100
# 起始时间
self.startDate = public.getDate(diff=-self.testDays) # 60天数据回测
self.endDate = public.getDate(diff=0)
self.total_tablename = 'train_total_1'
self.detail_tablename = 'train_future_1'
self.method = 'simTick' if self.isSimTickUse else 'quick'
self.stage = 'jump'
self.uidKey = "%s_%s_%s_%s_%s_" + self.method + "_" + self.stage
# 切换全部计算
self.isAll = 0
def getAllMain(self, code, start=None):
if start is None:
start = public.getDate(diff=-2)
res = rq.get_dominant_future(code,
start_date=start,
end_date=public.getDate(diff=1))
pre = ''
docs = []
for i in range(len(res)):
if pre != res[i]: docs.append((res.index[i], res[i]))
pre = res[i]
return docs
def getAdjustDate(self, code, diff=120, start=None):
if start is None:
start = public.getDate(diff=-diff)
res = rq.get_dominant_future(code,
start_date=start,
end_date=public.getDate(diff=0))
pre = res[0]
l = []
for i in range(len(res)):
if pre != res[i]:
l.append((res.index[i - 1], res.index[i], pre, res[i]))
pre = res[i]
return l
def __init__(self):
self.Rice = interface_Rice()
self.codes = ['510050.XSHG']
self.period = '30m'
self.timePeriodList = [5, 10, 20, 60]
self.timePeriods = 60
self.iniAmount = 40000
self.multiplier = 10000
self.ratio = 2
self.baisLineList = [0.15, 0.25, 0.35]
self.index_list = ["MA"]
self.startDate = public.getDate(diff=-130) # 60天数据回测
self.endDate = public.getDate(diff=0)
def getMain(self, codes, start=None, end=None):
if start is None:
start = public.getDate(diff=-5)
if end is None:
end = public.getDate()
rs = []
for c in codes:
res = rq.get_dominant_future(c, start_date=start, end_date=end)
if res is not None:
rs.append(res.values[-1])
else:
rs.append(c + '88')
return rs
def switch(self):
# 生成all
if self.isAll == 1:
self.isEmptyUse = True
if self.turnlineList: self.turnlineList = [1.75, 2.5]
if self.superlineList: self.superlineList = [3.25]
self.klineTypeList = ['15m', '30m']
self.total_tablename = 'train_total_dema5'
self.detail_tablename = 'train_future_dema5'
self.testDays = 180
# 起始时间
self.startDate = public.getDate(diff=-self.testDays) # 60天数据回测
self.endDate = public.getDate(diff=0)
self.empty()
def saveStage(self, df2):
self.preNode = []
period = 4
self.records = []
for i in range(period, len(df2)):
sum, date = (df2.ix[i, key] for key in "sum,date".split(","))
isBuy, isRun = 0, False
pN = self.preNode
# 连续5年满足条件
if sum == 5:
isBuy, isRun, mode = 1, True, 1
elif len(pN) > 0 and sum < 5:
isBuy, isRun, mode = -1, True, 1
if isRun:
# print(i, isBuy, pos, vol)
self.order(df2.iloc[i], isBuy, 1)
# 结束时用当前日计算股价
if len(self.preNode) > 0:
last = copy.deepcopy(df2.iloc[-1])
last['date'] = public.getDate()
self.order(last, -1, 1)
# print(self.uid, len(self.records))
# 保存明细
if len(self.records) > 0:
#print('----', len(self.records))
self.Record.insertAll(self.records)
def curMA(self, row, df0):
e = row['datetime']
s = public.str_date(public.getDate(diff=-1, start=e) + ' 21:00:00')
df = df0[(df0['datetime'] >= s) & (df0['datetime'] <= e)]
return (df['close'] * df['volume']
).sum() / df['volume'].sum() if df['volume'].sum() != 0 else 0
def record(self):
# 510050 行情
stock = self.Int.get510050()
stock["datetime"] = public.getDatetime()
self.Owner.insert(stock)
# 期权行情
etfs = self.Int.get_price()
spys = []
self.price_owner = float(stock["price"])
for i in range(0, len(etfs), 2):
# 计算剩余天数
r = public.dayDiff(self.Int.expireMap[etfs[i]["code"]],
public.getDate())
rec0 = self.calc(etfs[i], etfs[i + 1], r, mode=0)
spys.append(rec0)
rec1 = self.calc(etfs[i + 1], etfs[i], r, mode=1)
spys.append(rec1)
# inform 通知
try:
self.inform(spys)
except:
logger.error("ws disconnect")
# 写入数据库
self.sPrice.insertAll(etfs)
self.Spy.insertAll(spys)
def main():
cmdKeys = "w:"
fw = public.getCmdParam(cmdKeys, ("-w", 2))
FT = fytuObject()
# 每10分钟检查一次窝轮行情
if fw == 1:
valid = FT.isTradeDate('HK')
if valid:
obj = warModel()
obj.online()
# 每15分钟检查一次基金申购:
if fw == 2:
if FT.isTradeDate('SH'):
obj = etf4_compare()
d, t = public.getDate(), public.getDatetime()
# 大于2点45分，则每15秒运行一次直到结束
if t > d + " 14:45:00" and t < d + " 15:00:00":
while True:
t = public.getDatetime()
if not (t > d + " 14:45:00" and t < d + " 15:00:00"): break
obj.create(1)
time.sleep(15)
else:
# 小于2点45分，则每15分钟运行一次
obj.create(0)
def getDf(self, codes, period='1d'):
Rice = interface_Rice()
Rice.setIndexList(self.indexCodeList)
Base = future_baseInfo()
BI = BaseInfo([])
if len(codes) == 0:
codes = Base.getUsedMap(hasIndex=True)
mCodes = Rice.getMain(codes)
dfs = Rice.kline(mCodes,
period=period,
start=public.getDate(diff=-10),
pre=200)
i = 0
for mcode in mCodes:
c = codes[i]
last = BI.att(c, 'nightEnd')[0:6].replace(':', '')
file = Rice.basePath + 'future_%s_%s_%s.csv' % (
mcode, last, public.getDatetime(style='%Y%m%d_%H%M%S'))
print(mcode, last)
df = dfs[mcode]
df['datetime'] = df.index
df0 = df[df['datetime'] > '2019-01-17 13:47:40.000']
print(df0.index, len(df0))
#df.to_csv(file, index=0)
i += 1
break
def getWave(self, market='HK', stock_type="STOCK", autype='qfq'):
date = public.getDate(diff=0)
CSV = csvFile(folder="/data/csv",
filename="rate_%s_%s_%s.csv" % (market, autype, date),
headers=["code", "name", "count", "avg", "rate"])
df = self.getStockInfo(market, stock_type)
i = 0
for index, row in df.iterrows():
_c, _m, _s = self.getHistory(row["code"], autype)
doc = {
"code": row["code"],
"name": row["name"],
"count": _c,
"avg": _m,
"rate": _s
}
#print(doc)
#break
if i % 100 == 0:
print(i, doc)
i += 1
CSV.writeLine(doc)
CSV.close()
def get_fundamentals(self, codes, start_date=None, years=10, type='y'):
"""
q = query(fds.eod_derivative_indicator.pe_ratio,
fds.balance_sheet.total_assets,
fds.balance_sheet.total_liabilities,
fds.balance_sheet.total_equity_and_liabilities
).filter(fds.stockcode.in_(codes))
"""
q = query(
fds.financial_indicator.adjusted_return_on_equity_diluted).filter(
fds.stockcode.in_(codes))
if start_date is None:
start_date = public.getDate()
print('-----', start_date)
Y = str(years * 4) + 'q'
res = rq.get_fundamentals(q,
start_date,
interval=Y,
report_quarter=True)
d = {}
for c in codes:
try:
d[c] = res.minor_xs(c)
except:
continue
return d
def start(self, codes, time0, kt):
print("子进程启动:", self.cindex, codes, kt, time.time() - time0)
self.klineType = kt
# 主力合约
self.codes = codes
self.mCodes = mCodes = [n + '88' for n in codes]
self.baseInfo = {}
self.Rice = interface_Rice()
# 查询获得配置 - 费率和每手单量
self.Base = future_baseInfo()
for doc in self.Base.getInfo(codes):
self.baseInfo[doc["code"] + '88'] = doc
cs0, cs1 = self.baseInfo[mCodes[0]], self.baseInfo[mCodes[1]]
# 子进程共享类
self.Rice.setTimeArea(cs0["nightEnd"])
self.Total = stock_uniform()
self.Total.tablename = self.total_tablename
if kt[-1]=='m':
self.startDate = public.getDate(diff=-200)
# 查询获得N分钟K线
dfs = self.Rice.kline(mCodes, period=self.klineType, start=self.startDate, end=self.endDate, pre=60)
doc = self.total(dfs, kt)
if doc is not None :
self.Total.insert(doc)
def getOwnerMap(self, owners=None):
owners_map = {}
res = self.Wave.getLastWave()
# 存储对象
# 查询获得正股波动率
oDf = pd.DataFrame(
[doc for doc in res if (owners is None or doc['code'] in owners)])
# 正股列表
lists = ('HK.' + oDf['code']).tolist()
# 查询获得正股当前股价
closes, volumes, rates = [], [], []
for ls in public.eachPage(lists, pc=200):
df = self.Futu.getSnap(ls)
#print(df)
if not df.empty:
closes += df['last_price'].tolist()
volumes += df['volume'].tolist()
rates += df['turnover_rate'].tolist()
time.sleep(5)
#添加正股收盘价
oDf['sclose'] = closes
oDf['volume'] = volumes
oDf['turnover_rate'] = rates
oDf['sdate'] = public.getDate()
docs = oDf.to_dict(orient='records')
for doc in docs:
owners_map[doc['code']] = doc
return owners_map
def stat_pe(self, codes, n):
print(n)
self.Rice = interface_Rice()
self.Record = stock_PE_year()
df = self.Rice.get_factor(codes,
start='2000-01-01',
end=public.getDate())
df['date'] = df.index
#df['date'] = df['date'].apply(lambda x: str(x))
df['year'] = df['date'].apply(lambda x: str(x)[:4])
docs = []
for y in range(2000, 2020):
df0 = df[df['year'] == str(y)]
for c in codes:
doc = {
"code": c,
'year': y,
'pe_ratio': round(df0[c].mean(), 2)
}
#print(doc)
docs.append(doc)
if len(docs) > 0:
self.Record.insertAll(docs)
def __init__(self):
# 费率和滑点
self.saveDetail = True # 是否保存明细
self.topUse = False
self.isEmptyUse = True # 是否清空记录
self.testDays = 1200
self.bullwidth = 2
self.periodwidth = 14
self.processCount = 5
self.preDaysList = [10]
self.preDays = 5
self.dissLineList = [0.05]
self.dissLine = 0.5
self.iniAmount = 500000 # 单边50万
# self.iniAmount = 2000000 * 0.0025 # 单边50万
self.stopLine = 2
self.indexCodeList = [('IH', '000016.XSHG'), ('IF', '399300.XSHE'), ('IC', '399905.XSHE')]
self.klineList = ['1d']
# 起始时间
self.startDate = '2013-01-01'
self.endDate = public.getDate(diff=0)
print(self.endDate)
self.total_tablename = 'train_total_4'
self.detail_tablename = 'train_future_4'
self.method = 'jump'
self.uidKey = "%s_%s_%s_%s_%s_" + self.method
self.isAll = 0
def adjustOrder(self, n0, date, dd):
preCode = ''
for c in self.adjustDates:
if c[1] == date:
preCode = c[2]
break
s = str(date).split(" ")[0]
df1 = self.Rice.kline([preCode], period=self.klineType, start=public.getDate(diff=-2, start= s), end=s, pre=0)
oldP = df1[preCode].loc[dd, 'close']
newP = n0['close']
# 调仓卖出
doc = copy.deepcopy(self.preNode[0])
sign = np.sign(self.preNode[0]['mode'])
pp = self.preNode[0]['price']
doc['price'] = oldP
doc['isopen'] = 0
doc['mode'] = -doc['mode']
doc['isstop'] = 6
doc['createdate'] = date
doc['income'] = sign * (oldP - pp) * doc["vol"] - doc["fee"]
doc1 = copy.deepcopy(self.preNode[0])
doc1['createdate'] = date
doc1['mode'] = int(6 * sign)
doc1['price'] = newP
doc1['isopen'] = 1
doc1['batchid'] = self.batchId = uuid.uuid1()
#self.records.append(doc1)
self.preNode = [doc1]
return [doc, doc1]
def order(self, n0, isBuy, mode):
vol, fee, amount, income, p0 = 0, 0, 0, 0, 0
code = n0['code']
d = public.getDate(diff=1, start=str(n0["date"]))
vd = self.getVday(d)
d1, price = self.Rice.getOpen(code, vd, type='stock')
#print(vd, d1)
if price is None:
print(code, vd, 'None')
return
if isBuy > 0:
if len(self.preNode) == 0:
self.batchid = uuid.uuid1()
p0 = price * (1 + self.shift)
vol = int(self.iniAmount / p0 / 100) * 100
amount = vol * p0
fee = vol * p0 * self.ratio
income = -fee
elif isBuy < 0:
p0 = price * (1 - self.shift)
vol, amount, fee, income = 0, 0, 0, 0
if len(self.preNode) > 0:
for pN in self.preNode:
vol += pN['vol']
amount += pN['vol'] * p0
fee += pN['vol'] * p0 * self.ratio
# 计算总的Income
income += pN['vol'] * p0 - pN[
'amount'] - pN['vol'] * p0 * self.ratio
doc = {
"code": n0['code'],
"name": self.dict[n0['code']],
"createdate": vd,
'reportdate': d1,
"price": p0,
"vol": vol,
"mode": int(mode),
"isBuy": int(isBuy),
"fee": fee,
"amount": amount,
"income": income,
"method": self.methodName,
"batchid": self.batchid,
"uid": self.uid
}
self.records.append(doc)
# 设置上一个记录
if isBuy > 0:
self.preNode.append(doc)
else:
self.preNode = []
return True
