增加回测非标准套利合约的方法。

This commit is contained in:
msincenselee 2017-04-16 10:58:50 +08:00
parent a56b0524e9
commit d19a5d721e

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@ -25,6 +25,7 @@ from vtGateway import VtOrderData, VtTradeData
from vtFunction import loadMongoSetting
import logging
import copy
import pandas as pd
########################################################################
class BacktestingEngine(object):
@ -90,6 +91,10 @@ class BacktestingEngine(object):
self.workingLimitOrderDict = OrderedDict() # 活动限价单字典,用于进行撮合用
self.limitOrderCount = 0 # 限价单编号
# 持仓缓存字典
# key为vtSymbolvalue为PositionBuffer对象
self.posBufferDict = {}
self.tradeCount = 0 # 成交编号
self.tradeDict = OrderedDict() # 成交字典
@ -420,9 +425,8 @@ class BacktestingEngine(object):
def __dataToTick(self, data):
"""
数据库查询返回的data结构转换为tick对象
added by IncenseLee
"""
tick = CtaTickData()
added by IncenseLee """
tick = CtaTickData()
symbol = data['InstrumentID']
tick.symbol = symbol
@ -775,6 +779,349 @@ class BacktestingEngine(object):
cache.close()
return True
def runBackTestingWithNonStrArbTickFile(self, leg1MainPath, leg2MainPath, leg1Symbol,leg2Symbol):
"""运行套利回测使用本地tickcsv数据)
参数
leg1MainPath leg1合约所在的市场路径
leg2MainPath leg2合约所在的市场路径
leg1Symbol leg1合约
Leg2Symbolleg2合约
added by IncenseLee
原始的tick分别存放在白天目录1和夜盘目录2中每天都有各个合约的数据
Z:\ticks\SHFE\201606\RB\0601\
RB1610.txt
RB1701.txt
....
Z:\ticks\SHFE_night\201606\RB\0601
RB1610.txt
RB1701.txt
....
夜盘目录为自然日不是交易日
按照回测的开始日期到结束日期循环每一天
每天优先读取日盘数据再读取夜盘数据
读取eg1如RB1610读取Leg2如RB701根据两者tick的时间优先顺序逐一tick灌输到策略的onTick中
"""
self.capital = self.initCapital # 更新设置期初资金
if not self.dataStartDate:
self.writeCtaLog(u'回测开始日期未设置。')
return
# RB
if len(self.symbol)<1:
self.writeCtaLog(u'回测对象未设置。')
return
if not self.dataEndDate:
self.dataEndDate = datetime.today()
#首先根据回测模式,确认要使用的数据类
if self.mode == self.BAR_MODE:
self.writeCtaLog(u'本回测仅支持tick模式')
return
testdays = (self.dataEndDate - self.dataStartDate).days
if testdays < 1:
self.writeCtaLog(u'回测时间不足')
return
for i in range(0, testdays):
testday = self.dataStartDate + timedelta(days = i)
self.output(u'回测日期:{0}'.format(testday))
# 加载运行白天数据
self.__loadNotStdArbTicks(leg1MainPath, leg2MainPath, testday, leg1Symbol,leg2Symbol)
# 加载运行夜盘数据
self.__loadNotStdArbTicks(leg1MainPath+'_night', leg2MainPath+'_night', testday, leg1Symbol, leg2Symbol)
def __loadTicksFromFile(self, filepath, tickDate, vtSymbol):
"""从文件中读取tick"""
# 先读取数据到Dict以日期时间为key
ticks = OrderedDict()
if not os.path.isfile(filepath):
self.writeCtaLog(u'{0}文件不存在'.format(filepath))
return ticks
dt = None
csvReadFile = file(filepath, 'rb')
reader = csv.DictReader(csvReadFile, delimiter=",")
self.writeCtaLog(u'加载{0}'.format(filepath))
for row in reader:
tick = CtaTickData()
tick.vtSymbol = vtSymbol
tick.symbol = vtSymbol
tick.date = tickDate.strftime('%Y%m%d')
tick.tradingDay = tick.date
tick.time = row['Time']
try:
tick.datetime = datetime.strptime(tick.date + ' ' + tick.time, '%Y%m%d %H:%M:%S.%f')
except Exception as ex:
self.writeCtaError(u'日期转换错误:{0},{1}:{2}'.format(tick.date + ' ' + tick.time, Exception, ex))
continue
# 修正毫秒
if tick.datetime.replace(microsecond=0) == dt:
# 与上一个tick的时间去除毫秒后相同,修改为500毫秒
tick.datetime = tick.datetime.replace(microsecond=500)
tick.time = tick.datetime.strftime('%H:%M:%S.%f')
else:
tick.datetime = tick.datetime.replace(microsecond=0)
tick.time = tick.datetime.strftime('%H:%M:%S.%f')
dt = tick.datetime
tick.lastPrice = float(row['LastPrice'])
tick.volume = int(float(row['LVolume']))
tick.bidPrice1 = float(row['BidPrice']) # 叫买价(价格低)
tick.bidVolume1 = int(float(row['BidVolume']))
tick.askPrice1 = float(row['AskPrice']) # 叫卖价(价格高)
tick.askVolume1 = int(float(row['AskVolume']))
# 排除涨停/跌停的数据
if (tick.bidPrice1 == float('1.79769E308') and tick.bidVolume1 == 0) \
or (tick.askPrice1 == float('1.79769E308') and tick.askVolume1 == 0):
continue
dtStr = tick.date + ' ' + tick.time
if dtStr in ticks:
self.writeCtaError(u'日内数据重复,异常,数据时间为:{0}'.format(dtStr))
else:
ticks[dtStr] = tick
return ticks
def __loadNotStdArbTicks(self, leg1MainPath,leg2MainPath, testday, leg1Symbol, leg2Symbol):
self.writeCtaLog(u'加载回测日期:{0}的价差tick'.format( testday))
leg1File = u'z:\\ticks\\{0}\\{1}\\{2}\\{3}\\{4}.txt' \
.format(leg1MainPath, testday.strftime('%Y%m'), self.symbol, testday.strftime('%m%d'), leg1Symbol)
if not os.path.isfile(leg1File):
self.writeCtaLog(u'{0}文件不存在'.format(leg1File))
return
leg2File = u'z:\\ticks\\{0}\\{1}\\{2}\\{3}\\{4}.txt' \
.format(leg2MainPath, testday.strftime('%Y%m'), self.symbol, testday.strftime('%m%d'), leg2Symbol)
if not os.path.isfile(leg2File):
self.writeCtaLog(u'{0}文件不存在'.format(leg2File))
return
leg1Ticks = self.__loadTicksFromFile(filepath=leg1File,tickDate= testday, vtSymbol=leg1Symbol)
if len(leg1Ticks) == 0:
self.writeCtaLog(u'{0}读取tick数为空'.format(leg1File))
return
leg2Ticks = self.__loadTicksFromFile(filepath=leg2File, tickDate=testday, vtSymbol=leg2Symbol)
if len(leg2Ticks) == 0:
self.writeCtaLog(u'{0}读取tick数为空'.format(leg1File))
return
leg1_tick = None
leg2_tick = None
while not (len(leg1Ticks) == 0 or len(leg2Ticks) == 0):
if leg1_tick is None and len(leg1Ticks) > 0:
leg1_tick = leg1Ticks.popitem(last=False)
if leg2_tick is None and len(leg2Ticks) > 0:
leg2_tick = leg2Ticks.popitem(last=False)
if leg1_tick is None and leg2_tick is not None:
self.newTick(leg2_tick[1])
leg2_tick = None
elif leg1_tick is not None and leg2_tick is None:
self.newTick(leg1_tick[1])
leg1_tick = None
elif leg1_tick is not None and leg2_tick is not None:
leg1 = leg1_tick[1]
leg2 = leg2_tick[1]
if leg1.datetime <= leg2.datetime:
self.newTick(leg1)
leg1_tick = None
else:
self.newTick(leg2)
leg2_tick = None
def runBackTestingWithNonStrArbTickFile2(self, leg1MainPath, leg2MainPath, leg1Symbol, leg2Symbol):
"""运行套利回测使用本地tickcsv数据数据从taobao标普购买)
参数
leg1MainPath leg1合约所在的市场路径
leg2MainPath leg2合约所在的市场路径
leg1Symbol leg1合约
Leg2Symbolleg2合约
added by IncenseLee
原始的tick存放在相应市场下每天的目录中目录包含市场各个合约的数据
E:\ticks\SQ\201606\20160601\
RB10.csv
RB01.csv
....
目录为交易日
按照回测的开始日期到结束日期循环每一天
读取eg1如RB1610读取Leg2如RB701根据两者tick的时间优先顺序逐一tick灌输到策略的onTick中
"""
self.capital = self.initCapital # 更新设置期初资金
if not self.dataStartDate:
self.writeCtaLog(u'回测开始日期未设置。')
return
# RB
if len(self.symbol) < 1:
self.writeCtaLog(u'回测对象未设置。')
return
if not self.dataEndDate:
self.dataEndDate = datetime.today()
# 首先根据回测模式,确认要使用的数据类
if self.mode == self.BAR_MODE:
self.writeCtaLog(u'本回测仅支持tick模式')
return
testdays = (self.dataEndDate - self.dataStartDate).days
if testdays < 1:
self.writeCtaLog(u'回测时间不足')
return
for i in range(0, testdays):
testday = self.dataStartDate + timedelta(days=i)
self.output(u'回测日期:{0}'.format(testday))
# 加载运行每天数据
self.__loadNotStdArbTicks2(leg1MainPath, leg2MainPath, testday, leg1Symbol, leg2Symbol)
def __loadTicksFromFile2(self, filepath, tickDate, vtSymbol):
"""从csv文件中UnicodeDictReader读取tick"""
# 先读取数据到Dict以日期时间为key
ticks = OrderedDict()
if not os.path.isfile(filepath):
self.writeCtaLog(u'{0}文件不存在'.format(filepath))
return ticks
dt = None
csvReadFile = file(filepath, 'rb')
df = pd.read_csv(filepath, encoding='gbk')
df.columns = ['date', 'time', 'lastPrice', 'lastVolume', 'totalInterest', 'position',
'bidPrice1', 'bidVolume1', 'bidPrice2', 'bidVolume2', 'bidPrice3', 'bidVolume3',
'askPrice1', 'askVolume1', 'askPrice2', 'askVolume2', 'askPrice3', 'askVolume3','BS']
self.writeCtaLog(u'加载{0}'.format(filepath))
for i in range(0,len(df)):
#日期, 时间, 成交价, 成交量, 总量, 属性(持仓增减), B1价, B1量, B2价, B2量, B3价, B3量, S1价, S1量, S2价, S2量, S3价, S3量, BS
# 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
row = df.iloc[i].to_dict()
tick = CtaTickData()
tick.vtSymbol = vtSymbol
tick.symbol = vtSymbol
tick.date = row['date']
tick.tradingDay = tickDate.strftime('%Y%m%d')
tick.time = row['time']
try:
tick.datetime = datetime.strptime(tick.date + ' ' + tick.time, '%Y-%m-%d %H:%M:%S')
except Exception as ex:
self.writeCtaError(u'日期转换错误:{0},{1}:{2}'.format(tick.date + ' ' + tick.time, Exception, ex))
continue
tick.date = tick.datetime.strftime('%Y%m%d')
# 修正毫秒
if tick.datetime.replace(microsecond=0) == dt:
# 与上一个tick的时间去除毫秒后相同,修改为500毫秒
tick.datetime = tick.datetime.replace(microsecond=500)
tick.time = tick.datetime.strftime('%H:%M:%S.%f')
else:
tick.datetime = tick.datetime.replace(microsecond=0)
tick.time = tick.datetime.strftime('%H:%M:%S.%f')
dt = tick.datetime
tick.lastPrice = float(row['lastPrice'])
tick.volume = int(float(row['lastVolume']))
tick.bidPrice1 = float(row['bidPrice1']) # 叫买价(价格低)
tick.bidVolume1 = int(float(row['bidVolume1']))
tick.askPrice1 = float(row['askPrice1']) # 叫卖价(价格高)
tick.askVolume1 = int(float(row['askVolume1']))
# 排除涨停/跌停的数据
if (tick.bidPrice1 == float('1.79769E308') and tick.bidVolume1 == 0) \
or (tick.askPrice1 == float('1.79769E308') and tick.askVolume1 == 0):
continue
dtStr = tick.date + ' ' + tick.time
if dtStr in ticks:
self.writeCtaError(u'日内数据重复,异常,数据时间为:{0}'.format(dtStr))
else:
ticks[dtStr] = tick
return ticks
def __loadNotStdArbTicks2(self, leg1MainPath, leg2MainPath, testday, leg1Symbol, leg2Symbol):
self.writeCtaLog(u'加载回测日期:{0}的价差tick'.format(testday))
# E:\Ticks\SQ\2014\201401\20140102\ag01_20140102.csv
leg1File = u'e:\\ticks\\{0}\\{1}\\{2}\\{3}\\{4}{5}_{3}.csv' \
.format(leg1MainPath, testday.strftime('%Y'), testday.strftime('%Y%m'), testday.strftime('%Y%m%d'), self.symbol, leg1Symbol[-2:])
if not os.path.isfile(leg1File):
self.writeCtaLog(u'{0}文件不存在'.format(leg1File))
return
leg2File = u'e:\\ticks\\{0}\\{1}\\{2}\\{3}\\{4}{5}_{3}.csv' \
.format(leg2MainPath,testday.strftime('%Y'), testday.strftime('%Y%m'), testday.strftime('%Y%m%d'), self.symbol, leg2Symbol[-2:])
if not os.path.isfile(leg2File):
self.writeCtaLog(u'{0}文件不存在'.format(leg2File))
return
leg1Ticks = self.__loadTicksFromFile2(filepath=leg1File, tickDate=testday, vtSymbol=leg1Symbol)
if len(leg1Ticks) == 0:
self.writeCtaLog(u'{0}读取tick数为空'.format(leg1File))
return
leg2Ticks = self.__loadTicksFromFile2(filepath=leg2File, tickDate=testday, vtSymbol=leg2Symbol)
if len(leg2Ticks) == 0:
self.writeCtaLog(u'{0}读取tick数为空'.format(leg1File))
return
leg1_tick = None
leg2_tick = None
while not (len(leg1Ticks) == 0 or len(leg2Ticks) == 0):
if leg1_tick is None and len(leg1Ticks) > 0:
leg1_tick = leg1Ticks.popitem(last=False)
if leg2_tick is None and len(leg2Ticks) > 0:
leg2_tick = leg2Ticks.popitem(last=False)
if leg1_tick is None and leg2_tick is not None:
self.newTick(leg2_tick[1])
leg2_tick = None
elif leg1_tick is not None and leg2_tick is None:
self.newTick(leg1_tick[1])
leg1_tick = None
elif leg1_tick is not None and leg2_tick is not None:
leg1 = leg1_tick[1]
leg2 = leg2_tick[1]
if leg1.datetime <= leg2.datetime:
self.newTick(leg1)
leg1_tick = None
else:
self.newTick(leg2)
leg2_tick = None
#----------------------------------------------------------------------
def runBackTestingWithBarFile(self, filename):
"""运行回测使用本地csv数据)
@ -831,6 +1178,9 @@ class BacktestingEngine(object):
try:
bar = CtaBarData()
bar.symbol = self.symbol
bar.vtSymbol = self.symbol
# 从tb导出的csv文件
#bar.open = float(row['Open'])
#bar.high = float(row['High'])
@ -1130,17 +1480,19 @@ class BacktestingEngine(object):
sellCrossPrice = self.bar.high # 若卖出方向限价单价格低于该价格,则会成交
buyBestCrossPrice = self.bar.open # 在当前时间点前发出的买入委托可能的最优成交价
sellBestCrossPrice = self.bar.open # 在当前时间点前发出的卖出委托可能的最优成交价
vtSymbol = self.bar.vtSymbol
else:
buyCrossPrice = self.tick.askPrice1
sellCrossPrice = self.tick.bidPrice1
buyBestCrossPrice = self.tick.askPrice1
sellBestCrossPrice = self.tick.bidPrice1
vtSymbol = self.tick.vtSymbol
# 遍历限价单字典中的所有限价单
for orderID, order in self.workingLimitOrderDict.items():
# 判断是否会成交
buyCross = order.direction==DIRECTION_LONG and order.price >= buyCrossPrice
sellCross = order.direction==DIRECTION_SHORT and order.price <= sellCrossPrice
buyCross = order.direction == DIRECTION_LONG and order.price >= buyCrossPrice and vtSymbol == order.vtSymbol
sellCross = order.direction == DIRECTION_SHORT and order.price <= sellCrossPrice and vtSymbol == order.vtSymbol
# 如果发生了成交
if buyCross or sellCross:
@ -1200,16 +1552,18 @@ class BacktestingEngine(object):
buyCrossPrice = self.bar.high # 若买入方向停止单价格低于该价格,则会成交
sellCrossPrice = self.bar.low # 若卖出方向限价单价格高于该价格,则会成交
bestCrossPrice = self.bar.open # 最优成交价,买入停止单不能低于,卖出停止单不能高于
vtSymbol = self.bar.vtSymbol
else:
buyCrossPrice = self.tick.lastPrice
sellCrossPrice = self.tick.lastPrice
bestCrossPrice = self.tick.lastPrice
vtSymbol = self.tick.vtSymbol
# 遍历停止单字典中的所有停止单
for stopOrderID, so in self.workingStopOrderDict.items():
# 判断是否会成交
buyCross = so.direction==DIRECTION_LONG and so.price <= buyCrossPrice
sellCross = so.direction==DIRECTION_SHORT and so.price >= sellCrossPrice
buyCross = so.direction == DIRECTION_LONG and so.price <= buyCrossPrice and vtSymbol == so.vtSymbol
sellCross = so.direction == DIRECTION_SHORT and so.price >= sellCrossPrice and vtSymbol == so.vtSymbol
# 如果发生了成交
if buyCross or sellCross:
@ -1334,9 +1688,13 @@ class BacktestingEngine(object):
if len(shortTrade)==0:
self.writeCtaError(u'异常,没有开空仓的数据')
break
pop_indexs = [i for i, val in enumerate(shortTrade) if val.vtSymbol == trade.vtSymbol]
if len(pop_indexs) < 1:
self.writeCtaLog(u'没有对应的symbol:{0}开空仓数据'.format(trade.vtSymbol))
break
pop_index = pop_indexs[0]
# 从未平仓的空头交易
entryTrade = shortTrade.pop(0)
entryTrade = shortTrade.pop(pop_index)
# 开空volume不大于平仓volume
if coverVolume >= entryTrade.volume:
@ -1347,6 +1705,7 @@ class BacktestingEngine(object):
groupId=gId, fixcommission=self.fixCommission)
t = {}
t['vtSymbol'] = entryTrade.vtSymbol
t['OpenTime'] = entryTrade.tradeTime
t['OpenPrice'] = entryTrade.price
t['Direction'] = u'Short'
@ -1406,6 +1765,7 @@ class BacktestingEngine(object):
groupId=gId, fixcommission=self.fixCommission)
t = {}
t['vtSymbol'] = entryTrade.vtSymbol
t['OpenTime'] = entryTrade.tradeTime
t['OpenPrice'] = entryTrade.price
t['Direction'] = u'Short'
@ -1467,7 +1827,14 @@ class BacktestingEngine(object):
self.writeCtaError(u'异常,没有开多单')
break
entryTrade = longTrade.pop(0)
pop_indexs = [i for i, val in enumerate(longTrade) if val.vtSymbol == trade.vtSymbol]
if len(pop_indexs) < 1:
self.writeCtaLog(u'没有对应的symbol{0}开多仓数据'.format(trade.vtSymbol))
break
pop_index = pop_indexs[0]
entryTrade = longTrade.pop(pop_index)
# 开多volume不大于平仓volume
if sellVolume >= entryTrade.volume:
@ -1479,6 +1846,7 @@ class BacktestingEngine(object):
groupId=gId, fixcommission=self.fixCommission)
t = {}
t['vtSymbol'] = entryTrade.vtSymbol
t['OpenTime'] = entryTrade.tradeTime
t['OpenPrice'] = entryTrade.price
t['Direction'] = u'Long'
@ -1534,6 +1902,7 @@ class BacktestingEngine(object):
groupId=gId, fixcommission=self.fixCommission)
t = {}
t['vtSymbol'] = entryTrade.vtSymbol
t['OpenTime'] = entryTrade.tradeTime
t['OpenPrice'] = entryTrade.price
t['Direction'] = u'Long'
@ -1866,7 +2235,7 @@ class BacktestingEngine(object):
import csv
csvWriteFile = file(csvOutputFile, 'wb')
fieldnames = ['OpenTime', 'OpenPrice', 'Direction', 'CloseTime', 'ClosePrice', 'Volume', 'Profit']
fieldnames = ['vtSymbol','OpenTime', 'OpenPrice', 'Direction', 'CloseTime', 'ClosePrice', 'Volume', 'Profit']
writer = csv.DictWriter(f=csvWriteFile, fieldnames=fieldnames, dialect='excel')
writer.writeheader()