class SingleMA(strategy.BacktestingStrategy):
def __init__(self, feed, instrument, n, initialCash=1000000):
strategy.BacktestingStrategy.__init__(self, feed, initialCash)
self.__instrument = instrument
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__position = None
self.__prices = feed[instrument].getPriceDataSeries()
self.__malength = int(n)
self.__ma = ma.SMA(self.__prices, self.__malength)
self.__pos = SequenceDataSeries() # record signal
def getPrice(self):
return self.__prices
def getMA(self):
return self.__ma
def testCon(self):
if self.__position is not None:
self.__pos.append(1)
elif self.__position is None:
self.__pos.append(0)
def getPos(self):
return self.__pos
def onEnterCanceled(self, position):
self.__position = None
def onEnterOk(self, position):
execInfo = position.getEntryOrder().getExecutionInfo()
instrumentInfo = position.getInstrument()
self.info("BUY %s at $%.2f" % (instrumentInfo, execInfo.getPrice()))
def onExitOk(self, position):
execInfo = position.getExitOrder().getExecutionInfo()
instrumentInfo = position.getInstrument()
self.info("SELL %s at $%.2f" % (instrumentInfo, execInfo.getPrice()))
self.__position = None
def onExitCancelled(self, position):
self.__position.exitMarket()
def onBars(self, bars):
closePrice = bars[self.__instrument].getPrice()
if self.__ma[-1] is None:
return
self.testCon()
if self.__position is not None:
if not self.__position.exitActive() and closePrice < self.__ma[-1]:
self.__position.exitMarket()
if self.__position is None:
if closePrice > self.__ma[-1]:
shares = int(self.getBroker().getEquity() * 0.9 / closePrice)
self.__position = self.enterLong(self.__instrument, shares)
def __init__(self, feed, instrument, n, initialCash=1000000):
strategy.BacktestingStrategy.__init__(self, feed, initialCash)
self.__instrument = instrument
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__position = None
self.__prices = feed[instrument].getPriceDataSeries()
self.__malength = int(n)
self.__ma = ma.SMA(self.__prices, self.__malength)
self.__pos = SequenceDataSeries() # record signal
def __init__(self, feed, instrument, mall, mals, masl, mass):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__instrument = instrument
self.__close = feed[instrument].getCloseDataSeries()
self.__longPos = None
self.__shortPos = None
self.__mall = ma.SMA(self.__close, int(mall))
self.__mals = ma.SMA(self.__close, int(mals))
self.__masl = ma.SMA(self.__close, int(masl))
self.__mass = ma.SMA(self.__close, int(mass))
self.__position = SequenceDataSeries()
def __init__(self, feed, instrument, n, initialCash = 1000000):
strategy.BacktestingStrategy.__init__(self, feed, initialCash)
self.__instrument = instrument
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__position = None
self.__prices = feed[instrument].getPriceDataSeries()
self.__malength = int(n)
self.__ma = ma.SMA(self.__prices, self.__malength)
self.__pos = SequenceDataSeries() # record signal
def __init__(self, feed, instrument, fast, slow, signal, up_cum):
strategy.BacktestingStrategy.__init__(self, feed)
self.__instrument = instrument
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.0008))
self.__longPos = None
self.__shortPos = None
self.__prices = feed[instrument].getPriceDataSeries()
self.__macd=macd.MACD(self.__prices,fast,slow,signal)
self.__range=0
self.__circ = int(up_cum)
self.__position = SequenceDataSeries()
def __init__(self,
instrument,
dataSeries,
fastEMA,
slowEMA,
signalEMA,
maxLen=None):
assert (fastEMA > 0)
assert (slowEMA > 0)
assert (fastEMA < slowEMA)
assert (signalEMA > 0)
super(Macd, self).__init__(maxLen)
self.__instrument = instrument
self.__skipNum = max(fastEMA, slowEMA, signalEMA)
self.__fastEMAWindow = EMAEventWindow(fastEMA)
self.__slowEMAWindow = EMAEventWindow(slowEMA)
self.__signalEMAWindow = EMAEventWindow(signalEMA)
self.__signal = SequenceDataSeries(maxLen) #dea
self.__histogram = SequenceDataSeries(maxLen) #macd
self.__cross = SequenceDataSeries(
maxLen) #dead cross signals and gold cross signals
self.__close_prices = dataSeries.getPriceDataSeries()
self.top_divergences = list()
self.double_top_divergences = list()
self.bottom_divergences = list()
self.double_bottom_divergences = list()
self.cross_detect = CrossDetect()
self.max_limit_detect = MaxLimitDetect
self.min_limit_detect = MinLimitDetect
self.top_divergence_detect = TopDivergenceDetect()
self.bottom_divergence_detect = BottomDivergenceDetect()
self.__close_prices.getNewValueEvent().subscribe(self.__onNewValue)
def __init__(self, feed, instrument, mall, mals, masl, mass):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__instrument = instrument
self.__close = feed[instrument].getCloseDataSeries()
self.__longPos = None
self.__shortPos = None
self.__mall = ma.SMA(self.__close, int(mall))
self.__mals = ma.SMA(self.__close, int(mals))
self.__masl = ma.SMA(self.__close, int(masl))
self.__mass = ma.SMA(self.__close, int(mass))
self.__position = SequenceDataSeries()
def __init__(self, feed, instrument, bollingerlength, numStdDev):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0))
self.__instrument = instrument
self.__bollingerlength = int(bollingerlength)
self.__close = feed[instrument].getPriceDataSeries()
numStdDev = float(numStdDev) / 10
self.__longPos = []
self.__macd=macd.MACD(self.__close,50,150,10)
self.__bollinger = bollinger.BollingerBands(self.__macd, self.__bollingerlength, int(numStdDev))
self.__UpperBand = self.__bollinger.getUpperBand()
self.__LowerBand = self.__bollinger.getLowerBand()
self.__position = SequenceDataSeries()
self.__circ=5
def __init__(self, feed, instrument,longline,shortline,bollingerlength, numStdDev):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__instrument = instrument
self.__bollingerlength = int(bollingerlength)
self.__close = feed[instrument].getMatchDataSeries()
numStdDev = float(numStdDev) / 10
self.__longPos = []
self.__shortPos = []
self.__macd=macd.MACD(self.__close,shortline,longline,10)
self.__bollinger = bollinger.BollingerBands(self.__macd, self.__bollingerlength, int(numStdDev))
self.__UpperBand = self.__bollinger.getUpperBand()
self.__LowerBand = self.__bollinger.getLowerBand()
self.__position = SequenceDataSeries()
self.__circ=5
self.__lastLongPos=None
self.__lastShortPos=None
self.__barNum=0
self.__macdMin=[]
self.__macdMax=[]
def __init__(self, feed, instrument,preclose,prehigh,prelow,p1,p2,p3,p4):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__instrument = instrument
self.__longPos = []
self.__shortPos = []
self.__position = SequenceDataSeries()
self.__prices= feed[instrument].getPriceDataSeries()
self.__circ=5
self.__lastLongPos=None
self.__lastShortPos=None
self.__barNum=0
self.__ssetup=prehigh-p1*(preclose-prelow)
self.__senter=((1+p2)/2)*(prehigh+preclose)-p2*prelow
self.__benter=((1+p2)/2)*(prelow+preclose)-p2*prehigh
self.__bsetup=prelow+p1*(prehigh-preclose)
self.__bbreak=self.__ssetup+p3*(self.__ssetup-self.__bsetup)
self.__sbreak=self.__bsetup-p3*(self.__ssetup-self.__bsetup)
self.__moreSsetup=False
self.__lessBsetup=False
self.__couldsbreak=True
self.__couldbbreak=True
self.__p4=p4
def __init__(self, feed = None, instrument = '',shortPeriod = 0,longPeriod = 0,money = None,longAllowed=True,shortAllowed=True): strategy.BacktestingStrategy.__init__(self, feed) self.position_cost = 0 #mid init position value mid_DEFAULT_MAX_LEN = 10 * DEFAULT_MAX_LEN self.__instrument = instrument self.__longPosition = None self.__shortPosition = None self.__position_volume = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量 self.__position_cost = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本 self.__position_pnl = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值 self.__portfolio_value = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) self.__buy = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) self.__sell = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) self.__buySignal = False self.__sellSignal = False self.money = money self.longAllowed = True self.shortAllowed = True #mid 计算ma将使用当天的收盘价格计算 #mid 1) dataSeries = feed[instrument] dataSeries.setMaxLen(mid_DEFAULT_MAX_LEN) closeSeries = dataSeries.getCloseDataSeries() #mid 2) prices = closeSeries prices.setMaxLen(mid_DEFAULT_MAX_LEN) #mid 3) self.__sma = ma.SMA(prices, shortPeriod,maxLen=mid_DEFAULT_MAX_LEN) self.__lma = ma.SMA(prices,longPeriod,maxLen=mid_DEFAULT_MAX_LEN) self.i = 0
class Bollinger_Bandit(strategy.BacktestingStrategy):
def __init__(self, feed, instrument, bollingerlength, numStdDev,
closelength, ccMAlength, malength, space):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.002))
self.__instrument = instrument
self.__bollingerlength = int(bollingerlength)
numStdDev = float(numStdDev) / 10
self.__closelength = int(closelength)
self.__ccMAlength = int(ccMAlength)
self.__malength = int(malength)
self.__longPos = None
self.__shortPos = None
self.__close = feed[instrument].getCloseDataSeries()
self.__open = feed[instrument].getOpenDataSeries()
self.__high = feed[instrument].getHighDataSeries()
self.__low = feed[instrument].getLowDataSeries()
self.__datetime = feed[instrument].getDateTimes()
self.__bollinger = bollinger.BollingerBands(self.__close,
self.__bollingerlength,
int(numStdDev))
self.__UpperBand = self.__bollinger.getUpperBand()
self.__LowerBand = self.__bollinger.getLowerBand()
self.__MA = SequenceDataSeries()
self.__space = int(space)
self.__enter = 0
self.__enterLong1 = 0
self.__enterLong2 = 0
self.__enterShort1 = 0
self.__enterShort2 = 0
self.__exitLong1 = 0
self.__exitLong2 = 0
self.__exitShort1 = 0
self.__exitShort1 = 0
#for test
#########################################################################
self.__p = SequenceDataSeries()
self.__filterCon = SequenceDataSeries()
self.__ccMACon1 = SequenceDataSeries()
self.__ccMACon2 = SequenceDataSeries()
self.__enterCon = SequenceDataSeries()
self.__enterLongCon1 = SequenceDataSeries()
self.__enterLongCon2 = SequenceDataSeries()
self.__enterShortCon1 = SequenceDataSeries()
self.__enterShortCon2 = SequenceDataSeries()
self.__exitLongCon1 = SequenceDataSeries()
self.__exitLongCon2 = SequenceDataSeries()
self.__exitShortCon1 = SequenceDataSeries()
self.__exitShortCon2 = SequenceDataSeries()
##########################################################################
def getHigh(self):
return self.__high
def getLow(self):
return self.__low
def getClose(self):
return self.__close
def getBollinger(self):
return self.__UpperBand, self.__LowerBand
def getMA(self):
return self.__MA
def getDateTime(self):
return self.__datetime
def getPosition(self):
return self.__p
def getTest(self):
return self.__filterCon, self.__ccMACon1, self.__ccMACon2, \
self.__enterCon, self.__enterLongCon1, self.__enterLongCon2, self.__enterShortCon1, \
self.__enterShortCon2, self.__exitLongCon1, self.__exitLongCon2, \
self.__exitShortCon1, self.__exitShortCon2
def onEnterCanceled(self, position):
if self.__longPos == position:
self.__longPos = None
elif self.__shortPos == position:
self.__shortPos = None
else:
assert (False)
def onExitOk(self, position):
if self.__longPos == position:
self.__longPos = None
elif self.__shortPos == position:
self.__shortPos = None
else:
assert (False)
def onBars(self, bars):
# If a position was not opened, check if we should enter a long position.
bar = bars[self.__instrument]
if len(self.__high) > 1:
print self.__close[-1], self.__high[-1], self.__open[
-1], self.__close[-2]
if self.__UpperBand is not None:
print self.__UpperBand[-1]
# filter datetime
###################################################################################
filterCon = len(self.__close) < max(
self.__bollingerlength, self.__malength, self.__closelength)
self.__filterCon.append(filterCon)
if filterCon:
return
# record position
####################################################################################
if self.__longPos is not None and self.__shortPos is None:
self.__p.append(1)
elif self.__longPos is None and self.__shortPos is not None:
self.__p.append(-1)
else:
self.__p.append(0)
# calculate ccMA
####################################################################################
ccMACon1 = self.__longPos is not None or self.__shortPos is not None
ccMACon2 = self.__malength > self.__ccMAlength
if ccMACon1 and ccMACon2:
self.__malength = self.__malength - 1
elif not ccMACon1:
self.__malength = 50
self.__ccMA = np.mean(self.__close[-self.__malength:])
# print self.__malength, self.__ccMA
self.__MA.append(self.__ccMA)
self.__ccMACon1.append(ccMACon1)
self.__ccMACon2.append(ccMACon2)
#open and close condition
######################################################################################
self.__enterLong1 = (cross.cross_above(self.__high, self.__UpperBand) >
0)
self.__enterLong2 = (bar.getClose() >= max(
self.__close[-self.__closelength:]))
self.__enter = ((self.__UpperBand[-1] - self.__LowerBand[-1]) /
bar.getClose() > float(self.__space) / 1000)
# print (self.__UpperBand[-1] - self.__LowerBand[-1]) / bar.getClose()
self.__enterShort1 = cross.cross_below(self.__low,
self.__LowerBand) > 0
self.__enterShort2 = bar.getClose() <= min(
self.__close[-self.__closelength:])
self.__exitLong1 = (bar.getClose() < self.__ccMA)
self.__exitLong2 = (self.__ccMA < self.__UpperBand[-1])
self.__exitShort1 = (bar.getClose() > self.__ccMA)
self.__exitShort2 = (self.__ccMA > self.__LowerBand[-1])
self.__enterCon.append(self.__enter)
self.__enterLongCon1.append(self.__enterLong1)
self.__enterLongCon2.append(self.__enterLong2)
self.__enterShortCon1.append(self.__enterShort1)
self.__enterShortCon2.append(self.__enterShort2)
self.__exitLongCon1.append(self.__exitLong1)
self.__exitLongCon2.append(self.__exitLong2)
self.__exitShortCon1.append(self.__exitShort1)
self.__exitShortCon2.append(self.__exitShort2)
#open and close
#######################################################################################
if self.__longPos is not None:
if self.exitLongSignal():
self.__longPos.exitMarket()
if self.__shortPos is not None:
print 11
self.info("intend long close")
print(self.__UpperBand[-1] -
self.__LowerBand[-1]) / bar.getClose()
elif self.__shortPos is not None:
if self.exitShortSignal():
self.__shortPos.exitMarket()
self.info("intend short close")
print(self.__UpperBand[-1] -
self.__LowerBand[-1]) / bar.getClose()
else:
if self.enterLongSignal():
shares = int(self.getBroker().getCash() * 0.2 /
bars[self.__instrument].getPrice())
self.__longPos = self.enterLong(self.__instrument, shares)
self.info("intend long open")
print(self.__UpperBand[-1] -
self.__LowerBand[-1]) / bar.getClose()
elif self.enterShortSignal():
shares = int(self.getBroker().getCash() * 0.2 /
bars[self.__instrument].getPrice())
self.__shortPos = self.enterShort(self.__instrument, shares)
self.info("intend short open")
print(self.__UpperBand[-1] -
self.__LowerBand[-1]) / bar.getClose()
def enterLongSignal(self):
if self.__enterLong1 and self.__enterLong2 and self.__enter:
return True
def enterShortSignal(self):
if self.__enterShort1 and self.__enterShort2 and self.__enter:
return True
def exitLongSignal(self):
if self.__exitLong1 and self.__exitLong2 and not self.__longPos.exitActive(
):
return True
def exitShortSignal(self):
if self.__exitShort1 and self.__exitShort2 and not self.__shortPos.exitActive(
):
return True
class rbreaker(strategy.BacktestingStrategy):
def __init__(self, feed, instrument,preclose,prehigh,prelow,p1,p2,p3,p4):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__instrument = instrument
self.__longPos = []
self.__shortPos = []
self.__position = SequenceDataSeries()
self.__prices= feed[instrument].getPriceDataSeries()
self.__circ=5
self.__lastLongPos=None
self.__lastShortPos=None
self.__barNum=0
self.__ssetup=prehigh-p1*(preclose-prelow)
self.__senter=((1+p2)/2)*(prehigh+preclose)-p2*prelow
self.__benter=((1+p2)/2)*(prelow+preclose)-p2*prehigh
self.__bsetup=prelow+p1*(prehigh-preclose)
self.__bbreak=self.__ssetup+p3*(self.__ssetup-self.__bsetup)
self.__sbreak=self.__bsetup-p3*(self.__ssetup-self.__bsetup)
self.__moreSsetup=False
self.__lessBsetup=False
self.__couldsbreak=True
self.__couldbbreak=True
self.__p4=p4
def testCon(self):
# record position
#######################################################################
if len(self.__longPos) > 0:
self.__position.append(len(self.__longPos))
if len(self.__shortPos)>0 :
#print(self.__shortPos.getShares())
self.__position.append(-len(self.__shortPos))
elif len(self.__longPos)==0 and len(self.__shortPos)==0:
self.__position.append(0)
#print(0)
def getPrice(self):
return self.__prices
def getTest(self):
return self.__position
def onBars(self, bars):
bar = bars[self.__instrument]
if self.__prices[-1]>self.__ssetup:
self.__moreSsetup=True
else:
self.__couldbbreak=True
if self.__prices[-1]<self.__bsetup:
self.__lessBsetup=True
else:
self.__couldsbreak=True
dt=bars.getDateTime()
h=dt.hour
m=dt.minute
if(h==14 and m>50):
if len(self.__longPos)> 0:
for item in self.__longPos:
if item[0]._Position__exitOrder is None:
item[0].exitMarket()
if len(self.__shortPos)>0:
for item in self.__shortPos:
if item[0]._Position__exitOrder is None:
item[0].exitMarket()
return
self.testCon()
if len(self.__longPos)> 0:
if self.exitLongSignal():
for item in self.__longPos:
if item[0]._Position__exitOrder is None:
item[0].exitMarket()
elif len(self.__shortPos)>0:
if self.exitShortSignal():
for item in self.__shortPos:
if item[0]._Position__exitOrder is None:
item[0].exitMarket()
if self.enterLongSignal():
for i in range(self.enterLongSignal()):
shares = int(self.getBroker().getEquity() * 0.2 / bars[self.__instrument].getPrice())
# self.__longPos.
pos=self.enterLong(self.__instrument, shares)
#pos.exitLimit(bars[self.__instrument].getPrice()*0.99)
self.__longPos.append([pos,0])
self.__lastLongPos=self.__barNum
#print('long'+str(shares))
if self.enterShortSignal():
for i in range(self.enterShortSignal()):
shares = int(self.getBroker().getEquity() * 0.2 / bars[self.__instrument].getPrice())
pos=self.enterShort(self.__instrument, shares)
#pos.exitLimit(bars[self.__instrument].getPrice()*1.01)
self.__shortPos.append([pos,0])
self.__lastShortPos=self.__barNum
def enterLongSignal (self) :
if len(self.__longPos)>=2:
if self.__lessBsetup:
if self.__prices[-1]<self.__benter:
return 1
if self.__couldbbreak:
if self.__prices[-1]>self.__bbreak:
return 1
def enterShortSignal(self) :
if len(self.__shortPos)<=2:
if self.__moreSsetup:
if self.__prices[-1]<self.__senter:
return 1
if self.__couldsbreak:
if self.__prices[-1]<self.__sbreak:
return 1
def exitLongSignal(self) :
for item in self.__longPos:
print(item[1])
if item[0].getReturn()>item[1]:
item[1]=item[0].getReturn()
if item[1]-item[0].getReturn()>self.__p4:
self.__couldbbreak=False
return 1
def exitShortSignal(self):
for item in self.__shortPos:
if item[0].getReturn()>item[1]:
item[1]=item[0].getReturn()
if item[1]-item[0].getReturn()>self.__p4:
self.__couldsbreak=False
return 1
def onEnterCanceled(self, position):
if len(self.__longPos)>0:
if self.__longPos[-1] == position:
del self.__longPos[-1]
self.__lastLongPos==None
if len(self.__shortPos)>0:
if self.__shortPos[-1] == position:
del self.__shortPos[-1]
self.__lastShortPos==None
def onEnterOK(self,position):
pass
def onExitOk(self, position):
if isinstance(position,LongPosition):
self.__longPos = []
elif isinstance(position,ShortPosition):
self.__shortPos = []
else:
assert(False)
def onExitCanceled(self, position):
position.exitMarket()
def getParams(self):
return (self.__bbreak,self.__ssetup,self.__senter,self.__benter,self.__bsetup,self.__sbreak)
class thrSMA(strategy.BacktestingStrategy):
def __init__(self, feed, instrument, fast, slow, signal, up_cum):
strategy.BacktestingStrategy.__init__(self, feed)
self.__instrument = instrument
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.0008))
self.__longPos = None
self.__shortPos = None
self.__prices = feed[instrument].getPriceDataSeries()
self.__macd=macd.MACD(self.__prices,fast,slow,signal)
self.__range=0
self.__circ = int(up_cum)
self.__position = SequenceDataSeries()
def getPrice(self):
return self.__prices
def getMACD(self):
return self.__macd
def testCon(self):
# record position
#######################################################################
if self.__longPos is not None:
self.__position.append(1)
if self.__shortPos is not None:
self.__position.append(-1)
elif self.__longPos is None and self.__shortPos is None:
self.__position.append(0)
def getTest(self):
return self.__position
def onEnterCanceled(self, position):
if self.__longPos == position:
self.__longPos = None
elif self.__shortPos == position:
self.__shortPos = None
else:
assert(False)
def onEnterOK(self):
pass
def onExitOk(self, position):
if self.__longPos == position:
self.__longPos = None
elif self.__shortPos == position:
self.__shortPos = None
else:
assert(False)
def onExitCanceled(self, position):
position.exitMarket()
def buyCon1(self):
if self.__macd[-1] < -self.__range:
#print(self.__macd[-1])
return True
else:
return False
def buyCon2(self):
if self.__macd[-1-self.__circ] is None:
return False
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] > self.__macd[-i-2]:
m1 += 1
if m1 >= self.__circ:
return True
else:
return False
def exitLongCon1(self):
if self.__macd[-1]>0:
return True
else:
return False
def exitLongCon2(self):
if self.__macd[-1-self.__circ] is None:
return False
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] < self.__macd[-i-2]:
m1 += 1
if m1 >= self.__circ:
return True
else:
return False
def exitShortCon1(self):
if self.__macd[-1]<0:
return True
else:
return False
def exitShortCon2(self):
if self.__macd[-1-self.__circ] is None:
return False
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] > self.__macd[-i-2]:
m1 += 1
if m1 >= self.__circ:
return True
else:
return False
def sellCon1(self):
if self.__macd[-1] >self.__range:
return True
else:
return False
def sellCon2(self):
if self.__macd[-1-self.__circ] is None:
return False
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] < self.__macd[-i-2]:
m1 += 1
if m1 >= self.__circ:
return True
else:
return False
def onBars(self, bars):
# If a position was not opened, check if we should enter a long position.
if self.__macd[-1]is None:
return
self.__range=self.__prices[0]*0.004
self.testCon()
if self.__longPos is not None:
if self.exitLongSignal():
self.__longPos.exitMarket()
elif self.__shortPos is not None:
if self.exitShortSignal():
self.__shortPos.exitMarket()
elif self.__longPos is None and self.__shortPos is None:
if self.enterLongSignal():
shares = int(self.getBroker().getEquity() * 0.2 / bars[self.__instrument].getPrice())
self.__longPos = self.enterLong(self.__instrument, shares)
elif self.enterShortSignal():
shares = int(self.getBroker().getEquity() * 0.2 / bars[self.__instrument].getPrice())
self.__shortPos = self.enterShort(self.__instrument, shares)
def enterLongSignal(self) :
if self.buyCon1() and self.buyCon2():
return True
else:
return False
def enterShortSignal(self) :
if self.sellCon1() and self.sellCon2():
return True
else:
return False
def exitLongSignal(self) :
if self.exitLongCon1() and self.exitLongCon2() and not self.__longPos.exitActive():
return True
else:
return False
def exitShortSignal(self):
if self.exitShortCon1() and self.exitShortCon2() and not self.__shortPos.exitActive():
return True
else:
return False
def __init__(self, feed, instrument, bollingerlength, numStdDev, closelength, ccMAlength, malength, space):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.002))
self.__instrument = instrument
self.__bollingerlength = int(bollingerlength)
numStdDev = float(numStdDev) / 10
self.__closelength = int(closelength)
self.__ccMAlength = int(ccMAlength)
self.__malength = int(malength)
self.__longPos = None
self.__shortPos = None
self.__close = feed[instrument].getCloseDataSeries()
self.__high = feed[instrument].getHighDataSeries()
self.__low = feed[instrument].getLowDataSeries()
self.__datetime = feed[instrument].getDateTimes()
self.__bollinger = bollinger.BollingerBands(self.__close, self.__bollingerlength, int(numStdDev))
self.__UpperBand = self.__bollinger.getUpperBand()
self.__LowerBand = self.__bollinger.getLowerBand()
self.__MA = SequenceDataSeries()
self.__space = int(space)
self.__enter = 0
self.__enterLong1 = 0
self.__enterLong2 = 0
self.__enterShort1 = 0
self.__enterShort2 = 0
self.__exitLong1 = 0
self.__exitLong2 = 0
self.__exitShort1 = 0
self.__exitShort1 = 0
#for test
#########################################################################
self.__p = SequenceDataSeries()
self.__filterCon = SequenceDataSeries()
self.__ccMACon1 = SequenceDataSeries()
self.__ccMACon2 = SequenceDataSeries()
self.__enterCon = SequenceDataSeries()
self.__enterLongCon1 = SequenceDataSeries()
self.__enterLongCon2 = SequenceDataSeries()
self.__enterShortCon1 = SequenceDataSeries()
self.__enterShortCon2 = SequenceDataSeries()
self.__exitLongCon1 = SequenceDataSeries()
self.__exitLongCon2 = SequenceDataSeries()
self.__exitShortCon1 = SequenceDataSeries()
self.__exitShortCon2 = SequenceDataSeries()
class Bollinger_Bandit(strategy.BacktestingStrategy):
def __init__(self, feed, instrument, bollingerlength, numStdDev, closelength, ccMAlength, malength, space):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.002))
self.__instrument = instrument
self.__bollingerlength = int(bollingerlength)
numStdDev = float(numStdDev) / 10
self.__closelength = int(closelength)
self.__ccMAlength = int(ccMAlength)
self.__malength = int(malength)
self.__longPos = None
self.__shortPos = None
self.__close = feed[instrument].getCloseDataSeries()
self.__high = feed[instrument].getHighDataSeries()
self.__low = feed[instrument].getLowDataSeries()
self.__datetime = feed[instrument].getDateTimes()
self.__bollinger = bollinger.BollingerBands(self.__close, self.__bollingerlength, int(numStdDev))
self.__UpperBand = self.__bollinger.getUpperBand()
self.__LowerBand = self.__bollinger.getLowerBand()
self.__MA = SequenceDataSeries()
self.__space = int(space)
self.__enter = 0
self.__enterLong1 = 0
self.__enterLong2 = 0
self.__enterShort1 = 0
self.__enterShort2 = 0
self.__exitLong1 = 0
self.__exitLong2 = 0
self.__exitShort1 = 0
self.__exitShort1 = 0
#for test
#########################################################################
self.__p = SequenceDataSeries()
self.__filterCon = SequenceDataSeries()
self.__ccMACon1 = SequenceDataSeries()
self.__ccMACon2 = SequenceDataSeries()
self.__enterCon = SequenceDataSeries()
self.__enterLongCon1 = SequenceDataSeries()
self.__enterLongCon2 = SequenceDataSeries()
self.__enterShortCon1 = SequenceDataSeries()
self.__enterShortCon2 = SequenceDataSeries()
self.__exitLongCon1 = SequenceDataSeries()
self.__exitLongCon2 = SequenceDataSeries()
self.__exitShortCon1 = SequenceDataSeries()
self.__exitShortCon2 = SequenceDataSeries()
##########################################################################
def getHigh(self):
return self.__high
def getLow(self):
return self.__low
def getClose(self):
return self.__close
def getBollinger(self):
return self.__UpperBand, self.__LowerBand
def getMA(self):
return self.__MA
def getDateTime(self):
return self.__datetime
def getPosition(self):
return self.__p
def getTest(self):
return self.__filterCon, self.__ccMACon1, self.__ccMACon2, \
self.__enterCon, self.__enterLongCon1, self.__enterLongCon2, self.__enterShortCon1, \
self.__enterShortCon2, self.__exitLongCon1, self.__exitLongCon2, \
self.__exitShortCon1, self.__exitShortCon2
def onEnterCanceled(self, position):
if self.__longPos == position:
self.__longPos = None
elif self.__shortPos == position:
self.__shortPos = None
else:
assert(False)
def onExitOk(self, position):
if self.__longPos == position:
self.__longPos = None
elif self.__shortPos == position:
self.__shortPos = None
else:
assert(False)
def onBars(self, bars):
# If a position was not opened, check if we should enter a long position.
bar = bars[self.__instrument]
# filter datetime
###################################################################################
filterCon = len(self.__close) < max(self.__bollingerlength, self.__malength, self.__closelength)
self.__filterCon.append(filterCon)
if filterCon:
return
# record position
####################################################################################
if self.__longPos is not None and self.__shortPos is None:
self.__p.append(1)
elif self.__longPos is None and self.__shortPos is not None:
self.__p.append(-1)
else:
self.__p.append(0)
# calculate ccMA
####################################################################################
ccMACon1 = self.__longPos is not None or self.__shortPos is not None
ccMACon2 = self.__malength > self.__ccMAlength
if ccMACon1 and ccMACon2:
self.__malength = self.__malength - 1
elif not ccMACon1:
self.__malength = 50
self.__ccMA = np.mean(self.__close[-self.__malength:])
# print self.__malength, self.__ccMA
self.__MA.append(self.__ccMA)
self.__ccMACon1.append(ccMACon1)
self.__ccMACon2.append(ccMACon2)
#open and close condition
######################################################################################
self.__enterLong1 = (cross.cross_above(self.__high, self.__UpperBand) > 0)
self.__enterLong2 = (bar.getClose() >= max(self.__close[-self.__closelength:]))
self.__enter = ((self.__UpperBand[-1] - self.__LowerBand[-1]) / bar.getClose() > float(self.__space) / 1000)
# print (self.__UpperBand[-1] - self.__LowerBand[-1]) / bar.getClose()
self.__enterShort1 = cross.cross_below(self.__low, self.__LowerBand) > 0
self.__enterShort2 = bar.getClose() <= min(self.__close[-self.__closelength:])
self.__exitLong1 = (bar.getClose() < self.__ccMA)
self.__exitLong2 = (self.__ccMA < self.__UpperBand[-1])
self.__exitShort1 = (bar.getClose() > self.__ccMA)
self.__exitShort2 = (self.__ccMA > self.__LowerBand[-1])
self.__enterCon.append(self.__enter)
self.__enterLongCon1.append(self.__enterLong1)
self.__enterLongCon2.append(self.__enterLong2)
self.__enterShortCon1.append(self.__enterShort1)
self.__enterShortCon2.append(self.__enterShort2)
self.__exitLongCon1.append(self.__exitLong1)
self.__exitLongCon2.append(self.__exitLong2)
self.__exitShortCon1.append(self.__exitShort1)
self.__exitShortCon2.append(self.__exitShort2)
#open and close
#######################################################################################
if self.__longPos is not None:
if self.exitLongSignal():
self.__longPos.exitMarket()
# if self.__shortPos is not None:
# print 11
# self.info("intend long close")
# print (self.__UpperBand[-1] - self.__LowerBand[-1]) / bar.getClose()
elif self.__shortPos is not None:
if self.exitShortSignal():
self.__shortPos.exitMarket()
# self.info("intend short close")
# print (self.__UpperBand[-1] - self.__LowerBand[-1]) / bar.getClose()
else:
if self.enterLongSignal():
shares = int(self.getBroker().getCash() * 0.2 / bars[self.__instrument].getPrice())
self.__longPos = self.enterLong(self.__instrument, shares)
# self.info("intend long open")
# print (self.__UpperBand[-1] - self.__LowerBand[-1]) / bar.getClose()
elif self.enterShortSignal():
shares = int(self.getBroker().getCash() * 0.2 / bars[self.__instrument].getPrice())
self.__shortPos = self.enterShort(self.__instrument, shares)
# self.info("intend short open")
# print (self.__UpperBand[-1] - self.__LowerBand[-1]) / bar.getClose()
def enterLongSignal(self):
if self.__enterLong1 and self.__enterLong2 and self.__enter:
return True
def enterShortSignal(self):
if self.__enterShort1 and self.__enterShort2 and self.__enter:
return True
def exitLongSignal(self):
if self.__exitLong1 and self.__exitLong2 and not self.__longPos.exitActive():
return True
def exitShortSignal(self):
if self.__exitShort1 and self.__exitShort2 and not self.__shortPos.exitActive():
return True
class bollinger_band(strategy.BacktestingStrategy):
def __init__(self, feed, instrument,longline,shortline,bollingerlength, numStdDev):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__instrument = instrument
self.__bollingerlength = int(bollingerlength)
self.__close = feed[instrument].getMatchDataSeries()
numStdDev = float(numStdDev) / 10
self.__longPos = []
self.__shortPos = []
self.__macd=macd.MACD(self.__close,shortline,longline,10)
self.__bollinger = bollinger.BollingerBands(self.__macd, self.__bollingerlength, int(numStdDev))
self.__UpperBand = self.__bollinger.getUpperBand()
self.__LowerBand = self.__bollinger.getLowerBand()
self.__position = SequenceDataSeries()
self.__circ=5
self.__lastLongPos=None
self.__lastShortPos=None
self.__barNum=0
self.__macdMin=[]
self.__macdMax=[]
def getPrice(self):
return self.__prices
def getMACD(self):
return self.__macd
def getBollingerBands(self):
return self.__bollinger
def testCon(self):
# record position
#######################################################################
if len(self.__longPos) > 0:
self.__position.append(len(self.__longPos))
if len(self.__shortPos)>0 :
#print(self.__shortPos.getShares())
self.__position.append(-len(self.__shortPos))
elif len(self.__longPos)==0 and len(self.__shortPos)==0:
self.__position.append(0)
#print(0)
def getTest(self):
return self.__position
def onBars(self, bars):
bar = bars[self.__instrument]
lower = self.__bollinger.getLowerBand()[-1]
upper = self.__bollinger.getUpperBand()[-1]
self.__barNum=self.__barNum+1
# print(self.getActivePositions())
if self.__macd[-1] is None:
#print (self.__macd[-1])
return
if self.__macd[-1]>self.__macdMax:
self.__macdMax=self.__macd[-1]
if self.__macd[-1]<=self.__macdMin:
self.__macdMin=self.__macd[-1]
if lower is None or upper is None:
return
self.testCon()
if len(self.__longPos)> 0:
if self.exitLongSignal():
for pos in self.__longPos:
pos.exitMarket()
elif len(self.__shortPos)>0:
if self.exitShortSignal():
for pos in self.__shortPos:
pos.exitMarket()
if self.enterLongSignal():
for i in range(self.enterLongSignal()):
shares = int(self.getBroker().getEquity() * 0.2 / bars[self.__instrument].getMatch())
# self.__longPos.
self.__longPos.append(self.enterLong(self.__instrument, shares))
self.__lastLongPos=self.__barNum
#print('long'+str(shares))
elif self.enterShortSignal():
for i in range(self.enterShortSignal()):
shares = int(self.getBroker().getEquity() * 0.2 / bars[self.__instrument].getMatch())
self.__shortPos.append(self.enterShort(self.__instrument, shares))
self.__lastShortPos=self.__barNum
#print('short'+str(shares))
def enterLongSignal (self) :
if self.__lastLongPos is not None:
if self.__barNum-self.__lastLongPos<60:
return 0
if self.__UpperBand[-1-self.__circ] is None:
return 0
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] <= self.__LowerBand[-i-2]:
m1 += 1
if m1 >= self.__circ-1 and cross.cross_above(self.__macd,self.__LowerBand)>0:
if self.__macd[-1]>0:
return 0
else:
if self.__macdMin==self.__macd[-1] :
return 2
else:
return 1
else:
return 0
def enterShortSignal(self) :
if self.__lastShortPos is not None:
if self.__barNum-self.__lastShortPos<60:
return 0
if self.__UpperBand[-1-self.__circ] is None:
return 0
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] >= self.__UpperBand[-i-2]:
m1 += 1
if m1 >= self.__circ-1 and cross.cross_below(self.__macd,self.__UpperBand)>0:
if self.__macd[-1]<0:
return 0
else:
if self.__macdMax==self.__macd[-1]:
return 2
else:
return 1
else:
return 0
def exitLongSignal(self) :
if self.__UpperBand[-1-self.__circ] is None:
return False
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] >= self.__UpperBand[-i-2]:
m1 += 1
if m1 >= self.__circ-1 and cross.cross_below(self.__macd,self.__UpperBand)>0:
return True
elif self.__macd[-1]>=self.__UpperBand[-1] and self.__macdMax==self.__macd[-1]:
return True
elif self.__macd[-1]*1.001>=self.__UpperBand[-1] and self.__macd[-1]>-0.1:
return True
else:
return False
def exitShortSignal(self):
if self.__UpperBand[-1-self.__circ] is None:
return False
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] <= self.__LowerBand[-i-2]:
m1 += 1
if m1 >= self.__circ-1 and cross.cross_above(self.__macd,self.__LowerBand)>0:
return True
elif self.__macd[-1]<=self.__LowerBand[-1] and self.__macdMin==self.__macd[-1]:
return True
elif self.__macd[-1]<=self.__LowerBand[-1]*1.001 and self.__macd[-1]<0.11:
return True
else:
return False
def onEnterCanceled(self, position):
if self.__longPos[-1] == position:
del self.__longPos[-1]
self.__lastLongPos==None
elif self.__shortPos[-1] == position:
del self.__shortPos[-1]
self.__lastShortPos==None
else:
assert(False)
def onEnterOK(self,position):
pass
def onExitOk(self, position):
if isinstance(position,LongPosition):
self.__longPos = []
elif isinstance(position,ShortPosition):
self.__shortPos = []
else:
assert(False)
def onExitCanceled(self, position):
position.exitMarket()
class fourSMA(strategy.BacktestingStrategy):
def __init__(self, feed, instrument, mall, mals, masl, mass):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__instrument = instrument
self.__close = feed[instrument].getCloseDataSeries()
self.__longPos = None
self.__shortPos = None
self.__mall = ma.SMA(self.__close, int(mall))
self.__mals = ma.SMA(self.__close, int(mals))
self.__masl = ma.SMA(self.__close, int(masl))
self.__mass = ma.SMA(self.__close, int(mass))
self.__position = SequenceDataSeries()
def getPrice(self):
return self.__prices
def getSMA(self):
return self.__mall, self.__mals, self.__mass, self.__masl
def testCon(self):
# record position
#######################################################################
if self.__longPos is not None:
self.__position.append(1)
if self.__shortPos is not None:
self.__position.append(-1)
elif self.__longPos is None and self.__shortPos is None:
self.__position.append(0)
def getTest(self):
return self.__position
def onEnterCanceled(self, position):
if self.__longPos == position:
self.__longPos = None
elif self.__shortPos == position:
self.__shortPos = None
else:
assert (False)
def onExitOk(self, position):
if self.__longPos == position:
self.__longPos = None
elif self.__shortPos == position:
self.__shortPos = None
else:
assert (False)
def onExitCanceled(self, position):
position.exitMarket()
def onEnterOk(self, position):
pass
def onBars(self, bars):
bar = bars[self.__instrument]
if self.__mall[-1] is None:
return
self.testCon()
if self.__longPos is not None:
if self.exitLongSignal():
self.__longPos.exitMarket()
elif self.__shortPos is not None:
if self.exitShortSignal():
self.__shortPos.exitMarket()
elif self.__longPos is None and self.__shortPos is None:
if self.enterLongSignal():
shares = int(self.getBroker().getEquity() * 0.2 /
bar.getPrice())
self.__longPos = self.enterLong(self.__instrument, shares)
elif self.enterShortSignal():
shares = int(self.getBroker().getEquity() * 0.2 /
bar.getPrice())
self.__shortPos = self.enterShort(self.__instrument, shares)
def enterLongSignal(self):
if cross.cross_above(self.__mals, self.__mall) > 0:
return True
def enterShortSignal(self):
if cross.cross_below(self.__mals, self.__mall) > 0:
return True
def exitLongSignal(self):
if cross.cross_below(
self.__mass,
self.__masl) > 0 and not self.__longPos.exitActive():
return True
def exitShortSignal(self):
if cross.cross_above(
self.__mass,
self.__masl) > 0 and not self.__shortPos.exitActive():
return True
class fourSMA(strategy.BacktestingStrategy):
def __init__(self, feed, instrument, mall, mals, masl, mass):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__instrument = instrument
self.__close = feed[instrument].getCloseDataSeries()
self.__longPos = None
self.__shortPos = None
self.__mall = ma.SMA(self.__close, int(mall))
self.__mals = ma.SMA(self.__close, int(mals))
self.__masl = ma.SMA(self.__close, int(masl))
self.__mass = ma.SMA(self.__close, int(mass))
self.__position = SequenceDataSeries()
def getPrice(self):
return self.__prices
def getSMA(self):
return self.__mall,self.__mals,self.__mass,self.__masl
def testCon(self):
# record position
#######################################################################
if self.__longPos is not None:
self.__position.append(1)
if self.__shortPos is not None:
self.__position.append(-1)
elif self.__longPos is None and self.__shortPos is None:
self.__position.append(0)
def getTest(self):
return self.__position
def onEnterCanceled(self, position):
if self.__longPos == position:
self.__longPos = None
elif self.__shortPos == position:
self.__shortPos = None
else:
assert(False)
def onExitOk(self, position):
if self.__longPos == position:
self.__longPos = None
elif self.__shortPos == position:
self.__shortPos = None
else:
assert(False)
def onExitCanceled(self, position):
position.exitMarket()
def onEnterOk(self, position):
pass
def onBars(self, bars):
bar = bars[self.__instrument]
if self.__mall[-1] is None:
return
self.testCon()
if self.__longPos is not None:
if self.exitLongSignal():
self.__longPos.exitMarket()
elif self.__shortPos is not None:
if self.exitShortSignal():
self.__shortPos.exitMarket()
elif self.__longPos is None and self.__shortPos is None:
if self.enterLongSignal():
shares = int(self.getBroker().getEquity() * 0.2 / bar.getPrice())
self.__longPos = self.enterLong(self.__instrument, shares)
elif self.enterShortSignal():
shares = int(self.getBroker().getEquity() * 0.2 / bar.getPrice())
self.__shortPos = self.enterShort(self.__instrument, shares)
def enterLongSignal(self) :
if cross.cross_above(self.__mals, self.__mall) > 0:
return True
def enterShortSignal(self) :
if cross.cross_below(self.__mals, self.__mall) > 0:
return True
def exitLongSignal(self) :
if cross.cross_below(self.__mass, self.__masl) > 0 and not self.__longPos.exitActive():
return True
def exitShortSignal(self):
if cross.cross_above(self.__mass, self.__masl) > 0 and not self.__shortPos.exitActive():
return True
class midBaseStrategy(strategy.BacktestingStrategy):
def getFeeds(self,timeFrom=None,timeTo=None):
import os,sys
xpower = os.path.abspath(os.path.join(os.path.dirname(__file__),os.pardir,os.pardir,os.pardir,'midProjects','histdata'))
sys.path.append(xpower)
import dataCenter as dataCenter
self.dataCenter = dataCenter.dataCenter()
feeds = self.dataCenter.getFeedsForPAT(dataProvider = self.dataProvider,storageType = self.storageType,instruments = self.instruments,
period=self.period,timeTo = timeTo,timeFrom=timeFrom)
return feeds
def getFeedNew(self,timeFrom=None,timeTo=None):
'''mid should not be named the same with base class'''
import os,sys
xpower = os.path.abspath(os.path.join(os.path.dirname(__file__),os.pardir,os.pardir,os.pardir,'midProjects','histdata'))
sys.path.append(xpower)
import dataCenter as dataCenter
self.dataCenter = dataCenter.dataCenter()
feed = self.dataCenter.getFeedForPAT(dataProvider = self.dataProvider,storageType = self.storageType,instruments = self.instruments,
period=self.period,timeTo = timeTo,timeFrom=timeFrom)
return feed
def initEa(self,timeFrom=None,timeTo=None):
self.results = {}
feed = self.getFeedNew(timeFrom = timeFrom,timeTo = timeTo)
self.mid_DEFAULT_MAX_LEN = 10 * DEFAULT_MAX_LEN
mid_DEFAULT_MAX_LEN = self.mid_DEFAULT_MAX_LEN
#mid set init cash
cash_or_brk = 1000000
volumeLimit = 0.5 #mid used to calculate available volume for an order: availableVolume = volumeLeft * volumeLimit
#mid set fillstrategy
fillStrategy = fillstrategy.DefaultStrategy(volumeLimit = volumeLimit)
broker = backtesting.Broker(cash_or_brk, feed)
broker.setFillStrategy(fillStrategy)
#mid init base
strategy.BacktestingStrategy.__init__(self, feed,broker)
#mid 计算ma将使用当天的收盘价格计算
#mid 1)
self.closePrices = {}
self.longPosition = {}
self.shortPosition = {}
self.buySignal = {}
self.sellSignal = {}
self.timeFrom = timeFrom
self.timeTo = timeTo
#mid follow vars will be used only this class
self.__portfolio_value = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
self.__available_cash = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
self.__exitBar_position_pnl = {}
self.__curLongPositionCost = {} #mid init position value
self.__curShortPositionCost = {} #mid init position value
self.__position_volume = {} #mid 当前持有头寸数量
self.__position_cost = {} #mid 当前持有头寸开仓成本
self.__position_pnl = {} #mid 当前持有头寸价值
self.__position_cumulativePNL = {} #mid 当前 symbol 持有头寸cumulative pnl 价值
self.__buy = {}
self.__sell = {}
for instrument in self.instruments:
dataSeries = feed[instrument]
dataSeries.setMaxLen(mid_DEFAULT_MAX_LEN)
closeSeries = dataSeries.getCloseDataSeries()
#mid 2)
prices = closeSeries
prices.setMaxLen(mid_DEFAULT_MAX_LEN)
#mid follow vars will be used in subclass
self.closePrices[instrument] = prices
self.longPosition[instrument] = None
self.shortPosition[instrument] = None
self.buySignal[instrument] = False
self.sellSignal[instrument] = False
#mid follow vars will be used only this class
self.__curLongPositionCost[instrument] = 0 #mid init position value
self.__curShortPositionCost[instrument] = 0
self.__exitBar_position_pnl[instrument] = None
#mid init position value
self.__position_volume[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量
self.__position_cost[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本
self.__position_pnl[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值
self.__position_cumulativePNL[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
self.__buy[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
self.__sell[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
def getAssetStructure(self):
#mid --------------------------------
#mid 当前账户资产结构如下方式获取
#mid Long 和 Short不会同时存在
#mid 在开仓前，若有反向持仓，则此过程查询并输出已持有的反向持仓
broker = self.getBroker()
portfolio_value = broker.getEquity()
cash = broker.getCash()
if self.shortPosition is not None or self.longPosition is not None:
bars = self.getFeed().getCurrentBars()
positions = broker.getPositions()
positionsOpenValue = {}
positionsCloseValue = {}
for key,value in positions.items():
print "key:"+key+",value:"+str(value)
bar = bars.getBar(key)
openPrice = bar.getOpen()
closePrice = bar.getClose()
share = broker.getShares(key)
positionsOpenValue[key] = openPrice*share
positionsCloseValue[key] = closePrice*share
print
print 'current bar asset structure'
print 'open cash %2.f.' % (cash)
for key,value in positionsOpenValue.items():
print "key:"+key+",value:"+str(value)
print 'close cash %2.f.' % (cash)
for key,value in positionsCloseValue.items():
print "key:"+key+",value:"+str(value)
print 'portfolio:%2.f' % (portfolio_value)
return portfolio_value,cash,sum(positionsCloseValue.values())
return portfolio_value,cash,0
def sampleSub01(self,instrument):
"""mid not called anywhere
because of open price gap,method below is not right.
"""
broker = self.getBroker()
a = broker.getEquity()
b = self.getResult()
lastOpenPrice = None
lastClosePrice = None
bar = self.getFeed().getLastBar(instrument)
if bar is not None:
lastOpenPrice = bar.getOpen()
lastClosePrice = bar.getClose()
#lastPrice = self.getLastPrice(instrument)
pnl = (lastClosePrice - lastOpenPrice) * share
else:
pnl = 0 #mid instrument is dislisted.
if(len(self.__position_cumulativePNL[instrument])>0):
lastCumulativePNL = self.__position_cumulativePNL[instrument][-1]
else:
lastCumulativePNL = 0
def recordAccount(self):
# record position
#######################################################################
broker = self.getBroker()
curTime = self.getCurrentDateTime()
currentTime = self.getCurrentDateTime()
cash = broker.getCash(includeShort=False)
portfolio_value = broker.getEquity() #mid 按close价格计算的权益
print
self.info("onBars().recordAccount().Current time:%s"%(str(currentTime)))
self.info("onBars().recordAccount().----portfolio value: %.2f" % (portfolio_value))
self.info("onBars().recordAccount().----cash in portfolio: %.2f" % (cash))
self.__portfolio_value.appendWithDateTime(currentTime,portfolio_value)
self.__available_cash.appendWithDateTime(currentTime,cash)
totalCumulativePNL = 0
time = self.getCurrentDateTime()
if(time == dt.datetime(2010,12,21,0,0)):
a = 8
for instrument in self.instruments:
share = broker.getShares(instrument) #mid position is dict of share
lastClosePrice = self.getLastPrice(instrument)
if(lastClosePrice is None):
continue
position_value = lastClosePrice*share
if(share > 0):
position_cost = self.__curLongPositionCost[instrument]
elif(share < 0):
position_cost = self.__curShortPositionCost[instrument]
else:
position_cost = 0
position_pnl = (position_value - position_cost)
self.__position_volume[instrument].appendWithDateTime(currentTime,abs(share))
self.__position_cost[instrument].appendWithDateTime(currentTime,abs(position_cost))
self.__position_pnl[instrument].appendWithDateTime(currentTime,position_pnl)
self.__buy[instrument].appendWithDateTime(currentTime,self.buySignal[instrument])
self.__sell[instrument].appendWithDateTime(currentTime,self.sellSignal[instrument])
if(share != 0):
if(len(self.__position_pnl[instrument])>2):
currentPositionPnl = self.__position_pnl[instrument][-1]
lastPositionPnl = self.__position_pnl[instrument][-2]
currentBarPnl = currentPositionPnl - lastPositionPnl
else:
currentBarPnl = self.__position_pnl[instrument][-1]
else:
currentBarPnl = 0
if(self.__exitBar_position_pnl[instrument] is not None):
"""mid
如果当前bar有某个position在open price被closed掉，则当前bar的position_pnl是0.
在当前bar的openprice和上一bar的closeprice之间没有gap时，这个算法是合理的，但是，gap往往是存在的，
所以，据此计算的barPnl在exitbar上会有gap导致的误差
在此特别处理exitbar
"""
currentExitedPositionPnl = self.__exitBar_position_pnl[instrument]
lastPositionPnl = self.__position_pnl[instrument][-2]
currentBarExitedPnl = currentExitedPositionPnl - lastPositionPnl
self.__exitBar_position_pnl[instrument] = None
currentBarPnl = currentBarPnl + currentBarExitedPnl
if(len(self.__position_cumulativePNL[instrument])>0):
lastCumulativePNL = self.__position_cumulativePNL[instrument][-1]
cumulativePNL = lastCumulativePNL + currentBarPnl
else:
cumulativePNL = currentBarPnl
self.__position_cumulativePNL[instrument].appendWithDateTime(currentTime,cumulativePNL)
if(True):
self.info("onBars().recordAccount().--------mid current bar PNL: %.3f" %(currentBarPnl))
self.info("onBars().recordAccount().--------%s" % (instrument))
self.info("onBars().recordAccount().--------share:%.3f" % (share))
self.info("onBars().recordAccount().--------lastClosePrice:%.3f" % (lastClosePrice))
self.info("onBars().recordAccount().--------mid calculated position value: %.3f" %(position_value))
self.info("onBars().recordAccount().--------mid position cost: %.3f" %(position_cost))
self.info("onBars().recordAccount().--------mid calculated postion pnl: %.3f" %(position_pnl))
self.info("onBars().recordAccount().--------mid CumulativePNL: %.3f" %(cumulativePNL))
totalCumulativePNL = totalCumulativePNL + cumulativePNL
if(abs(1000000 - (portfolio_value - totalCumulativePNL))>0.00000001):
self.info("onBars().recordAccount().--------mid initCash: %.3f" %(portfolio_value - totalCumulativePNL))
a = 8
def getPortfolioValue(self):
return self.__portfolio_value
def getAvailableCash(self):
return self.__available_cash
def getCurInstrument(self):
return self.curInstrument
def getPositionValue(self,instrument):
return self.__position_cumulativePNL[instrument]
def getPositionVolume(self,instrument):
return self.__position_volume[instrument]
def getPositionCost(self,instrument):
return self.__position_cost[instrument]
def getPositionPnl(self,instrument):
return self.__position_pnl[instrument]
def getBuy(self,instrument):
return self.__buy[instrument]
def getSell(self,instrument):
return self.__sell[instrument]
def onEnterOk(self, position):
'''mid
由于getEquity()返回的是依据当日close价格计算出来的权益
所以，这个值不能作为持仓成本
持仓成本需要以onEnterOk时bar的open价格计算
由于经常有跳开现象，所以依据bar(n-1).close发出的market order，
在bar(n).open执行时通常会有gap出现，表现在position_cost图上时就是持有成本离计划成本会有跳口，
'''
print
currentTime = self.getCurrentDateTime()
execInfo = position.getEntryOrder().getExecutionInfo()
self.info("onEnterOK().ExecutionInfo.Current time: %s"%(execInfo.getDateTime()))
#mid 1)record the position cost
instrument = position.getInstrument()
feed = self.getFeed()
bars = feed.getCurrentBars()
bar = bars.getBar(instrument)
openPrice = bar.getOpen()
closePrice = self.getLastPrice(instrument) #mid lastPrice == closePrice
if(False):
'''mid long+short
计算获取instrument的净头寸
long = 10,short = -5
则position = 5
'''
share = self.getBroker().getShares(instrument)
else:
'''mid only long or short
计算当前position代表的头寸
如果当前为long，则求出long头寸并不考虑short
long = 10,short = -5
若position == long
则此处求出 position=10
'''
share = position.getShares()
if isinstance(position, strategy.position.LongPosition):
self.__curLongPositionCost[instrument] = openPrice*share
if isinstance(position, strategy.position.ShortPosition):
self.__curShortPositionCost[instrument] = openPrice*share
#mid 1.1) a example to show price gap
planedCost = 100000
if(planedCost - abs(self.__curLongPositionCost[instrument]) > 1000):
'''mid
跳开gap导致的n-1 day计划持仓金额和n day实际持仓金额之间的差额
以n-1day的close价格为依据计算share to open
n-1 day close = 10
n day open = 9.8
如果是要open 100000元
则原计划持有数量shares = 100000/10 = 10000
实际持有成本 = 计划持有数量 × 实际open价格
= 10000 × 9.8 = 980000'''
pass
#mid 2)log account info after enterOKed.
execInfo = position.getEntryOrder().getExecutionInfo()
portfolio = self.getResult()
cash = self.getBroker().getCash()
self.info("onEnterOk().symbol:%s" % (instrument))
self.info("onEnterOk().current available cash: %.2f,portfolio: %.2f." % (cash,portfolio))
if isinstance(position, strategy.position.LongPosition):
print str(self.__curLongPositionCost[instrument])+'='+str(share)+'*'+str(openPrice)
self.info("onEnterOK().ExecutionInfo: %s,OPEN LONG %.2f at $%.2f"
% (execInfo.getDateTime(),execInfo.getQuantity(),execInfo.getPrice()))
elif isinstance(position, strategy.position.ShortPosition):
print str(self.__curShortPositionCost[instrument])+'='+str(share)+'*'+str(openPrice)
self.info("onEnterOK().ExecutionInfo: %s,OPEN SHORT %.2f at $%.2f"
% (execInfo.getDateTime(),execInfo.getQuantity(),execInfo.getPrice()))
def onEnterCanceled(self, position):
instrument = position.getInstrument()
self.info("onEnterCanceled().current available cash: %.2f." % (self.getBroker().getCash()))
if isinstance(position, strategy.position.LongPosition):
self.longPosition[instrument] = None
self.info("onEnterCanceled().OPEN LONG cancled.")
elif isinstance(position, strategy.position.ShortPosition):
self.shortPosition[instrument] = None
self.info("onEnterCanceled().OPEN SHORT cancled.")
def onExitOk(self, position):
execInfo = position.getExitOrder().getExecutionInfo()
portfolio = self.getResult()
cash = self.getBroker().getCash()
instrument = position.getInstrument()
print
currentTime = self.getCurrentDateTime()
self.info("onExitOk().ExecutionInfo.Current time: %s"%(execInfo.getDateTime()))
self.info("onExitOk().instrument:%s." % (instrument))
self.info("onExitOk().current available cash: %.2f,portfolio: %.2f." % (cash,portfolio))
exQuantity = execInfo.getQuantity()
exPrice = execInfo.getPrice()
exAmount = exQuantity * exPrice
#self.sampleSub01(instrument)
if isinstance(position, strategy.position.LongPosition):
positionCost = self.__curLongPositionCost[instrument]
self.__exitBar_position_pnl[instrument] = exAmount - positionCost
self.longPosition[instrument] = None
self.__curLongPositionCost[instrument] = 0
self.info("onExitOk().ExecutionInfo: %s,CLOSE LONG %.2f at $%.2f"
% (execInfo.getDateTime(),execInfo.getQuantity(),execInfo.getPrice()))
elif isinstance(position, strategy.position.ShortPosition):
positionCost = self.__curShortPositionCost[instrument]
self.__exitBar_position_pnl[instrument] = -exAmount - positionCost
self.shortPosition[instrument] = None
self.__curShortPositionCost[instrument] = 0
self.info("onExitOk().ExecutionInfo: %s,CLOSE SHORT %.2f at $%.2f"
% (execInfo.getDateTime(),execInfo.getQuantity(),execInfo.getPrice()))
def onExitCanceled(self, position):
# If the exit was canceled, re-submit it.
if isinstance(position, strategy.position.LongPosition):
self.longPosition[instrument] = None
elif isinstance(position, strategy.position.ShortPosition):
self.shortPosition[instrument] = None
def logInfo(self,bars = None):
pLong,pShort = 0,0
if(self.longPosition is not None):
pLong = self.longPosition.getShares()
if(self.shortPosition is not None):
pShort = self.shortPosition.getShares()
bar = bars[self.instrument]
pOpen = bar.getOpen()
pHigh = bar.getHigh()
pLow = bar.getLow()
pClose = bar.getClose()
pPrice = bar.getPrice()
self.info('logInfo().price:%.3f,open:%.2f,high:%.2f,low:%.2f,close:%.2f'%(pPrice,pOpen,pHigh,pLow,pClose))
#self.info('long:%.2f#short:%.2f'%(pLong,pShort))
def closePosition(self):
for instrument in self.instruments:
if(self.longPosition[instrument] is not None and self.sellSignal[instrument] == True
and not self.longPosition[instrument].exitActive()):
print
self.info("onBars().closePosition(), instrument:%s" % (instrument))
self.info("onBars().closePosition(), LONG POSITION to close %.2f" % (self.longPosition[instrument].getShares()))
self.longPosition[instrument].exitMarket()
if(self.shortPosition[instrument] is not None and self.buySignal[instrument] == True
and not self.shortPosition[instrument].exitActive()):
print
self.info("onBars().closePosition(), instrument:%s" % (instrument))
self.info("onBars().closePosition(), SHORT POSITION to close %.2f" % (self.shortPosition[instrument].getShares()))
self.shortPosition[instrument].exitMarket()
def openPosition(self):
'''mid
此处是onBars，这个和zipline的概念完全不同
zipline中，需要覆写的是handle_data，这个东西是个tick概念，所以没有OHLC的，只是个price
PAT中，每次onBars，都会传入一个newbar的OHLC，此时，要如何按这个OHLC决策，全由你
依据OHLC做完决策后，可以发送交易指令：
* Order.Type.MARKET
* Order.Type.LIMIT
* Order.Type.STOP
* Order.Type.STOP_LIMIT
1.市价单，依据下一个bar的openPrice执行命令：
self.enterLong()
2.限价单
3.止损单市价单
4.止损限价单
当前似乎没有止盈单
在均线策略中，应该在每个newbar到来时，按closePrice的均线计算指标值，然后发送市价单
1.每个newbar按close价格计算指标，并在下一个bar按open成交
2.每个newbar按open价格计算指标，并在此newbar按open成交
以上1,2的计算逻辑是一致的。如果当前bar的close和下一个bar的open相差无几时，两种算法的回测结果也应相差无几
'''
# mid 2)open
if(self.shortAllowed):
for instrument in self.instruments:
self.curInstrument = instrument
if(self.sellSignal[instrument] == True):
# Enter a buy market order. The order is good till canceled.
bar = self.getFeed().getLastBar(instrument)
volume = 0
lastClose = 0
if bar is not None:
volume = bar.getVolume()
lastClose = bar.getClose()
shares = self.money.getShares(strat = self)
print
self.info("onBars().openPosition(), instrument %s" % (instrument))
self.info("onBars().openPosition(), SHORT POSITION to open %.2f" % (shares))
self.info("onBars().openPosition(), lastClose: %.2f,%.2f" % (self.getLastPrice(instrument),lastClose))
self.info("onBars().openPosition(), need amount: %.2f" % (shares*self.getLastPrice(instrument)))
self.info("onBars().openPosition(), available amount: %.2f." % (self.getBroker().getCash() ))
self.info("onBars().openPosition(), available volume: %.2f." % (volume))
self.shortPosition[instrument] = self.enterShort(instrument, shares, True)
if(self.longAllowed):
for instrument in self.instruments:
self.curInstrument = instrument
if(self.buySignal[instrument] == True):
shares = self.money.getShares(strat = self)
print
self.info("onBars().openPosition(), instrument %s" % (instrument))
self.info("onBars().openPosition(), LONG POSITION to open %.2f" % (shares) )
self.info("onBars().openPosition(), need amount: %.2f." % (shares*self.getLastPrice(instrument)))
self.info("onBars().openPosition(), available amount: %.2f." % (self.getBroker().getCash() ))
self.longPosition[instrument] = self.enterLong(instrument, shares, True)
def __analiseEachSymbol(self,instrument):
dataForCandle = self.dataCenter.getCandleData(dataProvider = self.dataProvider,dataStorage = self.storageType,dataPeriod = self.period,
symbol = instrument,dateStart=self.timeFrom,dateEnd = self.timeTo)
self.analyzer.analyseEachSymbol(self.results[instrument],dataForCandle,InKLine = self.InKLine)
def __analiseSummary(self):
dataProvider = self.benchDataProvider
instrument = self.benchSymbol
dataForCandle = self.dataCenter.getCandleData(dataProvider = dataProvider,dataStorage = self.storageType,dataPeriod = self.period,
symbol = instrument,dateStart=self.timeFrom,dateEnd = self.timeTo)
self.analyzer.analyseSummary(self.result,dataForCandle)
def run(self,timeFrom = None,timeTo = None):
self.initEa(timeFrom = timeFrom,timeTo = timeTo)
self.initIndicators()
#self.strat.setUseAdjustedValues(False)
self.initAnalyzer()
strategy.BacktestingStrategy.run(self)
for instrument in self.instruments:
buy = self.getBuy(instrument)
sell = self.getSell(instrument)
position_value = self.getPositionValue(instrument)
position_volume = self.getPositionVolume(instrument)
position_cost = self.getPositionCost(instrument)
position_pnl = self.getPositionPnl(instrument)
self.results[instrument] = pd.DataFrame({'position_volume':list(position_volume),'position_cost':list(position_cost),
'position_pnl':list(position_pnl),
'buy':list(buy),'sell':list(sell),'position_value':list(position_value)},
columns=['position_volume','position_cost','position_pnl','buy','sell','position_value'],
index=position_volume.getDateTimes())
self.addIndicators(instrument)
#------------------------------------
if(self.toPlotEachSymbol):
self.__analiseEachSymbol(instrument)
if(self.toPlotSummary):
portfolio_value = self.getPortfolioValue()
available_cash = self.getAvailableCash()
self.result = pd.DataFrame({'available_cash':list(available_cash),'portfolio_value':list(portfolio_value)},
columns=['available_cash','portfolio_value'],
index=portfolio_value.getDateTimes())
self.__analiseSummary()
return self.results
#mid from ea
#----------------------------------------------------------------------
def summary(self):
return "from %s to %s:returns:%.2f%%,sharpe:%.2f,MaxDrawdown:%.2f%%,Longest drawdown duration:(%s)" % (str(self.timeFrom),str(self.timeTo),
self.returnsAnalyzer.getCumulativeReturns()[-1] * 100,
self.sharpeRatioAnalyzer.getSharpeRatio(0.05),
self.drawdownAnalyzer.getMaxDrawDown() * 100,
self.drawdownAnalyzer.getLongestDrawDownDuration())
def detail(self):
""""""
print "-------------------------------------------------------------------------"
print "Final portfolio value: $%.2f" % self.getResult()
print "Cumulative returns: %.2f %%" % (self.returnsAnalyzer.getCumulativeReturns()[-1] * 100)
print "Sharpe ratio: %.2f" % (self.sharpeRatioAnalyzer.getSharpeRatio(0.05))
print "Max. drawdown: %.2f %%" % (self.drawdownAnalyzer.getMaxDrawDown() * 100)
print "Longest drawdown duration: (%s)" % (self.drawdownAnalyzer.getLongestDrawDownDuration())
print
print "Total trades: %d" % (self.tradesAnalyzer.getCount())
if self.tradesAnalyzer.getCount() > 0:
profits = self.tradesAnalyzer.getAll()
print "Avg. profit: $%2.f" % (profits.mean())
print "Profits std. dev.: $%2.f" % (profits.std())
print "Max. profit: $%2.f" % (profits.max())
print "Min. profit: $%2.f" % (profits.min())
returns = self.tradesAnalyzer.getAllReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print
print "Profitable trades: %d" % (self.tradesAnalyzer.getProfitableCount())
if self.tradesAnalyzer.getProfitableCount() > 0:
profits = self.tradesAnalyzer.getProfits()
print "Avg. profit: $%2.f" % (profits.mean())
print "Profits std. dev.: $%2.f" % (profits.std())
print "Max. profit: $%2.f" % (profits.max())
print "Min. profit: $%2.f" % (profits.min())
returns = self.tradesAnalyzer.getPositiveReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print
print "Unprofitable trades: %d" % (self.tradesAnalyzer.getUnprofitableCount())
if self.tradesAnalyzer.getUnprofitableCount() > 0:
losses = self.tradesAnalyzer.getLosses()
print "Avg. loss: $%2.f" % (losses.mean())
print "Losses std. dev.: $%2.f" % (losses.std())
print "Max. loss: $%2.f" % (losses.min())
print "Min. loss: $%2.f" % (losses.max())
returns = self.tradesAnalyzer.getNegativeReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print "-------------------------------------------------------------------------"
def initAnalyzer(self):
from pyalgotrade.stratanalyzer import sharpe
from pyalgotrade.stratanalyzer import returns
from pyalgotrade.stratanalyzer import drawdown
from pyalgotrade.stratanalyzer import trades
# 1.0) 策略结果
self.returnsAnalyzer = returns.Returns()
# 1.1) 夏普比率
self.sharpeRatioAnalyzer = sharpe.SharpeRatio()
# 1.2)
self.drawdownAnalyzer = drawdown.DrawDown()
# 1.3)
self.tradesAnalyzer = trades.Trades()
self.attachAnalyzer(self.sharpeRatioAnalyzer)
self.attachAnalyzer(self.returnsAnalyzer)
self.attachAnalyzer(self.tradesAnalyzer)
self.attachAnalyzer(self.drawdownAnalyzer)
class midBaseStrategy(strategy.BacktestingStrategy):
def getFeeds(self, timeFrom=None, timeTo=None):
import os, sys
xpower = os.path.abspath(
os.path.join(os.path.dirname(__file__), os.pardir, os.pardir,
os.pardir, 'midProjects', 'histdata'))
sys.path.append(xpower)
import dataCenter as dataCenter
self.dataCenter = dataCenter.dataCenter()
feeds = self.dataCenter.getFeedsForPAT(dataProvider=self.dataProvider,
storageType=self.storageType,
instruments=self.instruments,
period=self.period,
timeTo=timeTo,
timeFrom=timeFrom)
return feeds
def initEa(self, timeFrom=None, timeTo=None):
feeds = self.getFeeds(timeFrom=timeFrom, timeTo=timeTo)
instrument = self.instrument
strategy.BacktestingStrategy.__init__(self, feeds[instrument])
self.mid_DEFAULT_MAX_LEN = 10 * DEFAULT_MAX_LEN
mid_DEFAULT_MAX_LEN = self.mid_DEFAULT_MAX_LEN
#mid 计算ma将使用当天的收盘价格计算
#mid 1)
feed = feeds[instrument]
dataSeries = feed[instrument]
dataSeries.setMaxLen(mid_DEFAULT_MAX_LEN)
closeSeries = dataSeries.getCloseDataSeries()
#mid 2)
prices = closeSeries
prices.setMaxLen(mid_DEFAULT_MAX_LEN)
self.closePrices = prices
#mid follow vars will be used in subclass
self.timeFrom = timeFrom
self.timeTo = timeTo
self.instrument = instrument
self.longPosition = None
self.shortPosition = None
self.buySignal = False
self.sellSignal = False
#mid follow vars will be used only this class
self.__curPositionCost = 0 #mid init position value
mid_DEFAULT_MAX_LEN = self.mid_DEFAULT_MAX_LEN
self.__position_volume = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量
self.__position_cost = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本
self.__position_pnl = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值
self.__portfolio_value = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
self.__buy = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
self.__sell = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
def getAssetStructure(self):
#mid --------------------------------
#mid 当前账户资产结构如下方式获取
#mid Long 和 Short不会同时存在
#mid 在开仓前，若有反向持仓，则此过程查询并输出已持有的反向持仓
broker = self.getBroker()
portfolio_value = broker.getEquity()
cash = broker.getCash()
if self.shortPosition is not None or self.longPosition is not None:
bars = self.getFeed().getCurrentBars()
positions = broker.getPositions()
positionsOpenValue = {}
positionsCloseValue = {}
for key, value in positions.items():
print "key:" + key + ",value:" + str(value)
bar = bars.getBar(key)
openPrice = bar.getOpen()
closePrice = bar.getClose()
share = broker.getShares(key)
positionsOpenValue[key] = openPrice * share
positionsCloseValue[key] = closePrice * share
print
print 'current bar asset structure'
print 'open cash %2.f.' % (cash)
for key, value in positionsOpenValue.items():
print "key:" + key + ",value:" + str(value)
print 'close cash %2.f.' % (cash)
for key, value in positionsCloseValue.items():
print "key:" + key + ",value:" + str(value)
print 'portfolio:%2.f' % (portfolio_value)
return portfolio_value, cash, sum(positionsCloseValue.values())
return portfolio_value, cash, 0
def recordPositions(self):
# record position
#######################################################################
broker = self.getBroker()
position = broker.getPositions() #mid position is dict of share
share = broker.getShares(
self.instrument) #mid position is dict of share
lastPrice = self.getLastPrice(self.instrument)
portfolio_value = broker.getEquity() #mid 按close价格计算的权益
cash = broker.getCash()
position_value = portfolio_value - cash
position_pnl = position_value - self.__curPositionCost
print
print 'cash: %.2f' % (cash)
print 'position value: %.2f' % (portfolio_value - cash)
print 'mid calc: %.2f' % (lastPrice * share + cash)
print 'broker returned: %.2f' % (portfolio_value)
curTime = self.getCurrentDateTime()
currentTime = self.getCurrentDateTime()
self.__position_volume.appendWithDateTime(currentTime, abs(share))
self.__position_cost.appendWithDateTime(currentTime,
abs(self.__curPositionCost))
self.__position_pnl.appendWithDateTime(currentTime, position_pnl)
self.__portfolio_value.appendWithDateTime(currentTime, portfolio_value)
self.__buy.appendWithDateTime(currentTime, self.buySignal)
self.__sell.appendWithDateTime(currentTime, self.sellSignal)
def getInstrument(self):
return self.instrument
def getPortfolio(self):
return self.__portfolio_value
def getPositionVolume(self):
return self.__position_volume
def getPositionCost(self):
return self.__position_cost
def getPositionPnl(self):
return self.__position_pnl
def getBuy(self):
return self.__buy
def getSell(self):
return self.__sell
def onEnterOk(self, position):
execInfo = position.getEntryOrder().getExecutionInfo()
portfolio = self.getResult()
cash = self.getBroker().getCash()
'''mid
以下两种方法都是为了计算持仓成本
由于getEquity()返回的是依据当日close价格计算出来的权益
所以，这个值不能作为持仓成本
持仓成本需要以onEnterOk时bar的open价格计算
所以应使用第二种算法
由于经常有跳开现象，所以依据bar(n-1).close发出的market order，
在bar(n).open执行时通常会有gap出现，表现在position_cost图上时就是持有成本离计划成本会有跳口，
'''
if (False): #mid two methods to cacl cost.
portfolio_value = self.getBroker().getEquity()
self.__curPositionCost = portfolio_value - cash
else:
feed = self.getFeed()
bars = feed.getCurrentBars()
bar = bars.getBar(self.instrument)
openPrice = bar.getOpen()
closePrice = self.getLastPrice(
self.instrument) #mid lastPrice == closePrice
share = self.getBroker().getShares(self.instrument)
self.__curPositionCost = openPrice * share
self.info("onEnterOk().current available cash: %.2f,portfolio: %.2f." %
(cash, portfolio))
if isinstance(position, strategy.position.LongPosition):
self.info("onEnterOK().ExecutionInfo: %s,OPEN LONG %.2f at $%.2f" %
(execInfo.getDateTime(), execInfo.getQuantity(),
execInfo.getPrice()))
elif isinstance(position, strategy.position.ShortPosition):
self.info(
"onEnterOK().ExecutionInfo: %s,OPEN SHORT %.2f at $%.2f" %
(execInfo.getDateTime(), execInfo.getQuantity(),
execInfo.getPrice()))
def onEnterCanceled(self, position):
self.info("onEnterCanceled().current available cash: %.2f." %
(self.getBroker().getCash()))
if isinstance(position, strategy.position.LongPosition):
self.longPosition = None
self.info("onEnterCanceled().OPEN LONG cancled.")
elif isinstance(position, strategy.position.ShortPosition):
self.shortPosition = None
self.info("onEnterCanceled().OPEN SHORT cancled.")
def onExitOk(self, position):
execInfo = position.getExitOrder().getExecutionInfo()
portfolio = self.getResult()
cash = self.getBroker().getCash()
self.info("onExitOk().current available cash: %.2f,portfolio: %.2f." %
(cash, portfolio))
if isinstance(position, strategy.position.LongPosition):
self.longPosition = None
self.info("onExitOk().ExecutionInfo: %s,CLOSE LONG %.2f at $%.2f" %
(execInfo.getDateTime(), execInfo.getQuantity(),
execInfo.getPrice()))
elif isinstance(position, strategy.position.ShortPosition):
self.shortPosition = None
self.info(
"onExitOk().ExecutionInfo: %s,CLOSE SHORT %.2f at $%.2f" %
(execInfo.getDateTime(), execInfo.getQuantity(),
execInfo.getPrice()))
def onExitCanceled(self, position):
# If the exit was canceled, re-submit it.
if isinstance(position, strategy.position.LongPosition):
self.longPosition = None
elif isinstance(position, strategy.position.ShortPosition):
self.shortPosition = None
def logInfo(self, bars=None):
pLong, pShort = 0, 0
if (self.longPosition is not None):
pLong = self.longPosition.getShares()
if (self.shortPosition is not None):
pShort = self.shortPosition.getShares()
bar = bars[self.instrument]
pOpen = bar.getOpen()
pHigh = bar.getHigh()
pLow = bar.getLow()
pClose = bar.getClose()
pPrice = bar.getPrice()
self.info(
'logInfo().price:%.3f,open:%.2f,high:%.2f,low:%.2f,close:%.2f' %
(pPrice, pOpen, pHigh, pLow, pClose))
#self.info('long:%.2f#short:%.2f'%(pLong,pShort))
def closePosition(self):
if (self.longPosition is not None and self.sellSignal == True):
self.info(
"onBars().Status info,before exitMarket(), LONG POSITION to close %.2f"
% (self.longPosition.getShares()))
self.longPosition.exitMarket()
if (self.shortPosition is not None and self.buySignal == True):
self.info(
"onBars().Status info,before exitMarket(), SHORT POSITION to close %.2f"
% (self.shortPosition.getShares()))
self.shortPosition.exitMarket()
def openPosition(self):
'''mid
此处是onBars，这个和zipline的概念完全不同
zipline中，需要覆写的是handle_data，这个东西是个tick概念，所以没有OHLC的，只是个price
PAT中，每次onBars，都会传入一个newbar的OHLC，此时，要如何按这个OHLC决策，全由你
依据OHLC做完决策后，可以发送交易指令：
* Order.Type.MARKET
* Order.Type.LIMIT
* Order.Type.STOP
* Order.Type.STOP_LIMIT
1.市价单，依据下一个bar的openPrice执行命令：
self.enterLong()
2.限价单
3.止损单市价单
4.止损限价单
当前似乎没有止盈单
在均线策略中，应该在每个newbar到来时，按closePrice的均线计算指标值，然后发送市价单
1.每个newbar按close价格计算指标，并在下一个bar按open成交
2.每个newbar按open价格计算指标，并在此newbar按open成交
以上1,2的计算逻辑是一致的。如果当前bar的close和下一个bar的open相差无几时，两种算法的回测结果也应相差无几
'''
# mid 2)open
if (self.buySignal == True):
shares = self.money.getShares(strat=self)
self.info(
"onBars().Status info,before enterLong(), LONG POSITION to open %.2f,need amount: %.2f,available amount: %.2f."
% (shares, shares * self.getLastPrice(self.instrument),
self.getBroker().getCash()))
self.longPosition = self.enterLong(self.instrument, shares, True)
if (self.sellSignal == True):
# Enter a buy market order. The order is good till canceled.
shares = self.money.getShares(strat=self)
self.info(
"onBars().Status info,before enterShort(), SHORT POSITION to open %.2f,need amount: %.2f,available amount: %.2f."
% (shares, shares * self.getLastPrice(self.instrument),
self.getBroker().getCash()))
self.shortPosition = self.enterShort(self.instrument, shares, True)
def __analise(self):
dataForCandle = self.dataCenter.getCandleData(
dataProvider=self.dataProvider,
dataStorage=self.storageType,
dataPeriod=self.period,
symbol=self.instrument,
dateStart=self.timeFrom,
dateEnd=self.timeTo)
self.analyzer.analyze(self.result, dataForCandle, InKLine=self.InKLine)
def run(self, timeFrom=None, timeTo=None):
self.initEa(timeFrom=timeFrom, timeTo=timeTo)
self.initIndicators()
#self.strat.setUseAdjustedValues(False)
self.initAnalyzer()
strategy.BacktestingStrategy.run(self)
buy = self.getBuy()
sell = self.getSell()
portfolio_value = self.getPortfolio()
position_volume = self.getPositionVolume()
position_cost = self.getPositionCost()
position_pnl = self.getPositionPnl()
self.result = pd.DataFrame(
{
'position_volume': list(position_volume),
'position_cost': list(position_cost),
'position_pnl': list(position_pnl),
'buy': list(buy),
'sell': list(sell),
'portfolio_value': list(portfolio_value)
},
columns=[
'position_volume', 'position_cost', 'position_pnl', 'buy',
'sell', 'portfolio_value'
],
index=position_volume.getDateTimes())
self.addIndicators()
#------------------------------------
if (self.toPlot):
self.__analise()
return self.result
#mid from ea
#----------------------------------------------------------------------
def summary(self):
return "from %s to %s:returns:%.2f%%,sharpe:%.2f,MaxDrawdown:%.2f%%,Longest drawdown duration:(%s)" % (
str(self.timeFrom), str(self.timeTo),
self.returnsAnalyzer.getCumulativeReturns()[-1] * 100,
self.sharpeRatioAnalyzer.getSharpeRatio(0.05),
self.drawdownAnalyzer.getMaxDrawDown() * 100,
self.drawdownAnalyzer.getLongestDrawDownDuration())
def detail(self):
""""""
print "-------------------------------------------------------------------------"
print "Final portfolio value: $%.2f" % self.getResult()
print "Cumulative returns: %.2f %%" % (
self.returnsAnalyzer.getCumulativeReturns()[-1] * 100)
print "Sharpe ratio: %.2f" % (
self.sharpeRatioAnalyzer.getSharpeRatio(0.05))
print "Max. drawdown: %.2f %%" % (
self.drawdownAnalyzer.getMaxDrawDown() * 100)
print "Longest drawdown duration: (%s)" % (
self.drawdownAnalyzer.getLongestDrawDownDuration())
print
print "Total trades: %d" % (self.tradesAnalyzer.getCount())
if self.tradesAnalyzer.getCount() > 0:
profits = self.tradesAnalyzer.getAll()
print "Avg. profit: $%2.f" % (profits.mean())
print "Profits std. dev.: $%2.f" % (profits.std())
print "Max. profit: $%2.f" % (profits.max())
print "Min. profit: $%2.f" % (profits.min())
returns = self.tradesAnalyzer.getAllReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print
print "Profitable trades: %d" % (
self.tradesAnalyzer.getProfitableCount())
if self.tradesAnalyzer.getProfitableCount() > 0:
profits = self.tradesAnalyzer.getProfits()
print "Avg. profit: $%2.f" % (profits.mean())
print "Profits std. dev.: $%2.f" % (profits.std())
print "Max. profit: $%2.f" % (profits.max())
print "Min. profit: $%2.f" % (profits.min())
returns = self.tradesAnalyzer.getPositiveReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print
print "Unprofitable trades: %d" % (
self.tradesAnalyzer.getUnprofitableCount())
if self.tradesAnalyzer.getUnprofitableCount() > 0:
losses = self.tradesAnalyzer.getLosses()
print "Avg. loss: $%2.f" % (losses.mean())
print "Losses std. dev.: $%2.f" % (losses.std())
print "Max. loss: $%2.f" % (losses.min())
print "Min. loss: $%2.f" % (losses.max())
returns = self.tradesAnalyzer.getNegativeReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print "-------------------------------------------------------------------------"
def initAnalyzer(self):
from pyalgotrade.stratanalyzer import sharpe
from pyalgotrade.stratanalyzer import returns
from pyalgotrade.stratanalyzer import drawdown
from pyalgotrade.stratanalyzer import trades
# 1.0) 策略结果
self.returnsAnalyzer = returns.Returns()
# 1.1) 夏普比率
self.sharpeRatioAnalyzer = sharpe.SharpeRatio()
# 1.2)
self.drawdownAnalyzer = drawdown.DrawDown()
# 1.3)
self.tradesAnalyzer = trades.Trades()
self.attachAnalyzer(self.sharpeRatioAnalyzer)
self.attachAnalyzer(self.returnsAnalyzer)
self.attachAnalyzer(self.tradesAnalyzer)
self.attachAnalyzer(self.drawdownAnalyzer)
def initEa(self, timeFrom=None, timeTo=None):
feeds = self.getFeeds(timeFrom=timeFrom, timeTo=timeTo)
instrument = self.instrument
strategy.BacktestingStrategy.__init__(self, feeds[instrument])
self.mid_DEFAULT_MAX_LEN = 10 * DEFAULT_MAX_LEN
mid_DEFAULT_MAX_LEN = self.mid_DEFAULT_MAX_LEN
#mid 计算ma将使用当天的收盘价格计算
#mid 1)
feed = feeds[instrument]
dataSeries = feed[instrument]
dataSeries.setMaxLen(mid_DEFAULT_MAX_LEN)
closeSeries = dataSeries.getCloseDataSeries()
#mid 2)
prices = closeSeries
prices.setMaxLen(mid_DEFAULT_MAX_LEN)
self.closePrices = prices
#mid follow vars will be used in subclass
self.timeFrom = timeFrom
self.timeTo = timeTo
self.instrument = instrument
self.longPosition = None
self.shortPosition = None
self.buySignal = False
self.sellSignal = False
#mid follow vars will be used only this class
self.__curPositionCost = 0 #mid init position value
mid_DEFAULT_MAX_LEN = self.mid_DEFAULT_MAX_LEN
self.__position_volume = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量
self.__position_cost = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本
self.__position_pnl = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值
self.__portfolio_value = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
self.__buy = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
self.__sell = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
class DMACrossOver(strategy.BacktestingStrategy):
def __init__(self, feed = None, instrument = '',shortPeriod = 0,longPeriod = 0,money = None,longAllowed=True,shortAllowed=True):
strategy.BacktestingStrategy.__init__(self, feed)
self.position_cost = 0 #mid init position value
mid_DEFAULT_MAX_LEN = 10 * DEFAULT_MAX_LEN
self.__instrument = instrument
self.__longPosition = None
self.__shortPosition = None
self.__position_volume = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量
self.__position_cost = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本
self.__position_pnl = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值
self.__portfolio_value = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
self.__buy = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
self.__sell = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
self.__buySignal = False
self.__sellSignal = False
self.money = money
self.longAllowed = True
self.shortAllowed = True
#mid 计算ma将使用当天的收盘价格计算
#mid 1)
dataSeries = feed[instrument]
dataSeries.setMaxLen(mid_DEFAULT_MAX_LEN)
closeSeries = dataSeries.getCloseDataSeries()
#mid 2)
prices = closeSeries
prices.setMaxLen(mid_DEFAULT_MAX_LEN)
#mid 3)
self.__sma = ma.SMA(prices, shortPeriod,maxLen=mid_DEFAULT_MAX_LEN)
self.__lma = ma.SMA(prices,longPeriod,maxLen=mid_DEFAULT_MAX_LEN)
self.i = 0
def getAssetStructure(self):
#mid --------------------------------
#mid 当前账户资产结构如下方式获取
#mid Long 和 Short不会同时存在
#mid 在开仓前，若有反向持仓，则此过程查询并输出已持有的反向持仓
broker = self.getBroker()
portfolio_value = broker.getEquity()
cash = broker.getCash()
if self.__shortPosition is not None or self.__longPosition is not None:
bars = self.getFeed().getCurrentBars()
positions = broker.getPositions()
positionsOpenValue = {}
positionsCloseValue = {}
for key,value in positions.items():
print "key:"+key+",value:"+str(value)
bar = bars.getBar(key)
openPrice = bar.getOpen()
closePrice = bar.getClose()
share = broker.getShares(key)
positionsOpenValue[key] = openPrice*share
positionsCloseValue[key] = closePrice*share
print
print 'current bar asset structure'
print 'open cash %2.f.' % (cash)
for key,value in positionsOpenValue.items():
print "key:"+key+",value:"+str(value)
print 'close cash %2.f.' % (cash)
for key,value in positionsCloseValue.items():
print "key:"+key+",value:"+str(value)
print 'portfolio:%2.f' % (portfolio_value)
return portfolio_value,cash,sum(positionsCloseValue.values())
return portfolio_value,cash,0
def recordPositions(self):
# record position
#######################################################################
broker = self.getBroker()
position = broker.getPositions() #mid position is dict of share
share = broker.getShares(self.__instrument) #mid position is dict of share
lastPrice = self.getLastPrice(self.__instrument)
portfolio_value = broker.getEquity() #mid 按close价格计算的权益
cash = broker.getCash()
position_value = portfolio_value - cash
position_pnl = position_value - self.position_cost
print
print 'cash: %.2f' %(cash)
print 'position value: %.2f' % (portfolio_value - cash)
print 'mid calc: %.2f' %(lastPrice*share+cash)
print 'broker returned: %.2f' %(portfolio_value)
curTime = self.getCurrentDateTime()
if(False):
yLimit = self.money.getShares()*1.1
if(self.i==0):
self.__position.append(yLimit)
self.i = self.i + 1
elif(self.i==1):
self.__position.append(-yLimit)
self.i = self.i + 1
else:
currentTime = self.getCurrentDateTime()
self.__position.appendWithDateTime(currentTime,abs(share))
#self.__position.append(share)
else:
currentTime = self.getCurrentDateTime()
self.__position_volume.appendWithDateTime(currentTime,abs(share))
self.__position_cost.appendWithDateTime(currentTime,abs(self.position_cost))
self.__position_pnl.appendWithDateTime(currentTime,position_pnl)
self.__portfolio_value.appendWithDateTime(currentTime,portfolio_value)
self.__buy.appendWithDateTime(currentTime,self.__buySignal)
self.__sell.appendWithDateTime(currentTime,self.__sellSignal)
def getInstrument(self):
return self.__instrument
def getPortfolio(self):
return self.__portfolio_value
def getPositionVolume(self):
return self.__position_volume
def getPositionCost(self):
return self.__position_cost
def getPositionPnl(self):
return self.__position_pnl
def getSMA(self):
return self.__sma
def getLMA(self):
return self.__lma
def getBuy(self):
return self.__buy
def getSell(self):
return self.__sell
def onEnterOk(self, position):
execInfo = position.getEntryOrder().getExecutionInfo()
portfolio = self.getResult()
cash = self.getBroker().getCash()
'''mid
以下两种方法都是为了计算持仓成本
由于getEquity()返回的是依据当日close价格计算出来的权益
所以，这个值不能作为持仓成本
持仓成本需要以onEnterOk时bar的open价格计算
所以应使用第二种算法
由于经常有跳开现象，所以依据bar(n-1).close发出的market order，
在bar(n).open执行时通常会有gap出现，表现在position_cost图上时就是持有成本离计划成本会有跳口，
'''
if(False):#mid two methods to cacl cost.
portfolio_value = self.getBroker().getEquity()
self.position_cost = portfolio_value - cash
else:
feed = self.getFeed()
bars = feed.getCurrentBars()
bar = bars.getBar(self.__instrument)
openPrice = bar.getOpen()
closePrice = self.getLastPrice(self.__instrument) #mid lastPrice == closePrice
share = self.getBroker().getShares(self.__instrument)
self.position_cost = openPrice*share
self.info("onEnterOk().current available cash: %.2f,portfolio: %.2f." % (cash,portfolio))
if isinstance(position, strategy.position.LongPosition):
self.info("onEnterOK().ExecutionInfo: %s,OPEN LONG %.2f at $%.2f"
% (execInfo.getDateTime(),execInfo.getQuantity(),execInfo.getPrice()))
elif isinstance(position, strategy.position.ShortPosition):
self.info("onEnterOK().ExecutionInfo: %s,OPEN SHORT %.2f at $%.2f"
% (execInfo.getDateTime(),execInfo.getQuantity(),execInfo.getPrice()))
def onEnterCanceled(self, position):
self.info("onEnterCanceled().current available cash: %.2f." % (self.getBroker().getCash()))
if isinstance(position, strategy.position.LongPosition):
self.__longPosition = None
self.info("onEnterCanceled().OPEN LONG cancled.")
elif isinstance(position, strategy.position.ShortPosition):
self.__shortPosition = None
self.info("onEnterCanceled().OPEN SHORT cancled.")
def onExitOk(self, position):
execInfo = position.getExitOrder().getExecutionInfo()
portfolio = self.getResult()
cash = self.getBroker().getCash()
self.info("onExitOk().current available cash: %.2f,portfolio: %.2f." % (cash,portfolio))
if isinstance(position, strategy.position.LongPosition):
self.__longPosition = None
self.info("onExitOk().ExecutionInfo: %s,CLOSE LONG %.2f at $%.2f"
% (execInfo.getDateTime(),execInfo.getQuantity(),execInfo.getPrice()))
elif isinstance(position, strategy.position.ShortPosition):
self.__shortPosition = None
self.info("onExitOk().ExecutionInfo: %s,CLOSE SHORT %.2f at $%.2f"
% (execInfo.getDateTime(),execInfo.getQuantity(),execInfo.getPrice()))
def onExitCanceled(self, position):
# If the exit was canceled, re-submit it.
if isinstance(position, strategy.position.LongPosition):
self.__longPosition = None
elif isinstance(position, strategy.position.ShortPosition):
self.__shortPosition = None
def logInfo(self,bars = None):
pLong,pShort = 0,0
if(self.__longPosition is not None):
pLong = self.__longPosition.getShares()
if(self.__shortPosition is not None):
pShort = self.__shortPosition.getShares()
bar = bars[self.__instrument]
pOpen = bar.getOpen()
pHigh = bar.getHigh()
pLow = bar.getLow()
pClose = bar.getClose()
pPrice = bar.getPrice()
self.info('logInfo().price:%.3f,open:%.2f,high:%.2f,low:%.2f,close:%.2f'%(pPrice,pOpen,pHigh,pLow,pClose))
#self.info('long:%.2f#short:%.2f'%(pLong,pShort))
def run(self):
strategy.BacktestingStrategy.run(self)
sma = self.getSMA()
lma = self.getLMA()
buy = self.getBuy()
sell = self.getSell()
portfolio_value = self.getPortfolio()
position_volume = self.getPositionVolume()
position_cost = self.getPositionCost()
position_pnl = self.getPositionPnl()
result = pd.DataFrame({'position_volume':list(position_volume),'position_cost':list(position_cost),'position_pnl':list(position_pnl),'short_ema':list(sma),'long_ema':list(lma),
'buy':list(buy),'sell':list(sell),'portfolio_value':list(portfolio_value)},
columns=['position_volume','position_cost','position_pnl','short_ema','long_ema','buy','sell','portfolio_value'],
index=position_volume.getDateTimes())
return result
def onBars(self, bars):
'''mid
此处是onBars，这个和zipline的概念完全不同
zipline中，需要覆写的是handle_data，这个东西是个tick概念，所以没有OHLC的，只是个price
PAT中，每次onBars，都会传入一个newbar的OHLC，此时，要如何按这个OHLC决策，全由你
依据OHLC做完决策后，可以发送交易指令：
* Order.Type.MARKET
* Order.Type.LIMIT
* Order.Type.STOP
* Order.Type.STOP_LIMIT
1.市价单，依据下一个bar的openPrice执行命令：
self.enterLong()
2.限价单
3.止损单市价单
4.止损限价单
当前似乎没有止盈单
在均线策略中，应该在每个newbar到来时，按closePrice的均线计算指标值，然后发送市价单
1.每个newbar按close价格计算指标，并在下一个bar按open成交
2.每个newbar按open价格计算指标，并在此newbar按open成交
以上1,2的计算逻辑是一致的。如果当前bar的close和下一个bar的open相差无几时，两种算法的回测结果也应相差无几
'''
self.__buySignal,self.__sellSignal = False,False
# mid 1)close
if(self.longAllowed):
if self.__longPosition is not None and not self.__longPosition.exitActive():
#mid 有多仓，检查是否需要平仓
if(cross.cross_below(self.__sma, self.__lma) > 0):
print
self.info("onBars().Status info,before exitMarket(), LONG POSITION to close %.2f"
% (self.__longPosition.getShares()))
self.__longPosition.exitMarket()
if(self.shortAllowed):
if self.__shortPosition is not None and not self.__shortPosition.exitActive():
if(cross.cross_above(self.__sma, self.__lma) > 0):
print
self.info("onBars().Status info,before exitMarket(), SHORT POSITION to close %.2f"
% (self.__shortPosition.getShares()))
self.__shortPosition.exitMarket()
# mid 2)open
if(self.longAllowed):
if self.__longPosition is None:
#mid 无多仓，检查是否需要开多仓
if cross.cross_above(self.__sma, self.__lma) > 0:
# Enter a buy market order. The order is good till canceled.
shares = self.money.getShares(strat = self)
self.info("onBars().Status info,before enterLong(), LONG POSITION to open %.2f,need amount: %.2f,available amount: %.2f." %
(shares,shares*self.getLastPrice(self.__instrument),self.getBroker().getCash() ))
self.__longPosition = self.enterLong(self.__instrument, shares, True)
self.__buySignal = True
if(self.shortAllowed):
if self.__shortPosition is None:
if cross.cross_below(self.__sma, self.__lma) > 0:
# Enter a buy market order. The order is good till canceled.
shares = self.money.getShares(strat = self)
self.info("onBars().Status info,before enterShort(), SHORT POSITION to open %.2f,need amount: %.2f,available amount: %.2f." %
(shares,shares*self.getLastPrice(self.__instrument),self.getBroker().getCash() ))
self.__shortPosition = self.enterShort(self.__instrument, shares, True)
self.__sellSignal = True
self.recordPositions()
def __init__(self, feed, instrument, bollingerlength, numStdDev,
closelength, ccMAlength, malength, space):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.002))
self.__instrument = instrument
self.__bollingerlength = int(bollingerlength)
numStdDev = float(numStdDev) / 10
self.__closelength = int(closelength)
self.__ccMAlength = int(ccMAlength)
self.__malength = int(malength)
self.__longPos = None
self.__shortPos = None
self.__close = feed[instrument].getCloseDataSeries()
self.__open = feed[instrument].getOpenDataSeries()
self.__high = feed[instrument].getHighDataSeries()
self.__low = feed[instrument].getLowDataSeries()
self.__datetime = feed[instrument].getDateTimes()
self.__bollinger = bollinger.BollingerBands(self.__close,
self.__bollingerlength,
int(numStdDev))
self.__UpperBand = self.__bollinger.getUpperBand()
self.__LowerBand = self.__bollinger.getLowerBand()
self.__MA = SequenceDataSeries()
self.__space = int(space)
self.__enter = 0
self.__enterLong1 = 0
self.__enterLong2 = 0
self.__enterShort1 = 0
self.__enterShort2 = 0
self.__exitLong1 = 0
self.__exitLong2 = 0
self.__exitShort1 = 0
self.__exitShort1 = 0
#for test
#########################################################################
self.__p = SequenceDataSeries()
self.__filterCon = SequenceDataSeries()
self.__ccMACon1 = SequenceDataSeries()
self.__ccMACon2 = SequenceDataSeries()
self.__enterCon = SequenceDataSeries()
self.__enterLongCon1 = SequenceDataSeries()
self.__enterLongCon2 = SequenceDataSeries()
self.__enterShortCon1 = SequenceDataSeries()
self.__enterShortCon2 = SequenceDataSeries()
self.__exitLongCon1 = SequenceDataSeries()
self.__exitLongCon2 = SequenceDataSeries()
self.__exitShortCon1 = SequenceDataSeries()
self.__exitShortCon2 = SequenceDataSeries()
class Macd(SequenceDataSeries):
def __init__(self,
instrument,
dataSeries,
fastEMA,
slowEMA,
signalEMA,
maxLen=None):
assert (fastEMA > 0)
assert (slowEMA > 0)
assert (fastEMA < slowEMA)
assert (signalEMA > 0)
super(Macd, self).__init__(maxLen)
self.__instrument = instrument
self.__skipNum = max(fastEMA, slowEMA, signalEMA)
self.__fastEMAWindow = EMAEventWindow(fastEMA)
self.__slowEMAWindow = EMAEventWindow(slowEMA)
self.__signalEMAWindow = EMAEventWindow(signalEMA)
self.__signal = SequenceDataSeries(maxLen) #dea
self.__histogram = SequenceDataSeries(maxLen) #macd
self.__cross = SequenceDataSeries(
maxLen) #dead cross signals and gold cross signals
self.__close_prices = dataSeries.getPriceDataSeries()
self.top_divergences = list()
self.double_top_divergences = list()
self.bottom_divergences = list()
self.double_bottom_divergences = list()
self.cross_detect = CrossDetect()
self.max_limit_detect = MaxLimitDetect
self.min_limit_detect = MinLimitDetect
self.top_divergence_detect = TopDivergenceDetect()
self.bottom_divergence_detect = BottomDivergenceDetect()
self.__close_prices.getNewValueEvent().subscribe(self.__onNewValue)
def newCross(self, cross_type, cross_date, limit_dif, area, limit_dif_date,
macd, macd_date, close, close_date):
if cross_type == GOLD:
return GoldCross(cross_date, limit_dif, area, limit_dif_date, macd,
macd_date, close, close_date)
else:
return DeathCross(cross_date, limit_dif, area, limit_dif_date,
macd, macd_date, close, close_date)
def createNewCross(self, current_date, pre_cross_type, current_cross_type,
detect):
"""
获取三种极值的时间和极值[MACD，CLOSE, DIF]
:param current_date: 当前bar的date
:param pre_cross_type: 前一个交叉点的类型
:param current_cross_type: 当前交叉点的类型
:param detect: 极值检测类对象
:return: new class
"""
pre_cross_signal_date = self.getPreSignalDate(pre_cross_type)
if pre_cross_signal_date is None:
return self.newCross(current_cross_type, current_date, None, None,
None, None, None, None, None)
dif, dif_date = detect.get_limit_info_in(self, pre_cross_signal_date,
current_date)
close, close_date = detect.get_close_limit_info_in(
self.__close_prices, pre_cross_signal_date, current_date)
macd, macd_date = detect.get_limit_info_in(self.__histogram,
pre_cross_signal_date,
current_date)
area = detect.get_sum_info_in(self.__histogram, pre_cross_signal_date,
current_date)
return self.newCross(current_cross_type, current_date, dif, area,
dif_date, macd, macd_date, close, close_date)
def getPreSignalDate(self, pre_cross_type):
"""
获取dif和dea前一个交叉点的时间
:param pre_cross_type: 前一次交叉的类型[金叉或死叉]
:return:
"""
slength = len(self.__cross)
if slength == 0: return None
for x in range(slength - 1, -1, -1):
if self.__cross[x].type == pre_cross_type:
return self.__cross[x].cdate
return None
def getDif(self):
return self
def getDea(self):
"""Returns a :class:`pyalgotrade.dataseries.DataSeries` with the EMA over the MACD."""
return self.__signal
def getMacd(self):
"""Returns a :class:`pyalgotrade.dataseries.DataSeries` with the histogram (the difference between the MACD and the Signal)."""
return self.__histogram
def __onNewValue(self, dataSeries, dateTime, value):
self.__fastEMAWindow.onNewValue(dateTime, value)
self.__slowEMAWindow.onNewValue(dateTime, value)
fastValue = self.__fastEMAWindow.getValue()
slowValue = self.__slowEMAWindow.getValue()
if fastValue is None or slowValue is None:
diffValue = None
else:
diffValue = fastValue - slowValue
self.__signalEMAWindow.onNewValue(dateTime, diffValue)
deaValue = self.__signalEMAWindow.getValue()
if diffValue is None or deaValue is None:
macdValue = None
else:
macdValue = 2 * (diffValue - deaValue)
self.appendWithDateTime(dateTime, diffValue) #dif
self.__signal.appendWithDateTime(dateTime, deaValue) #dea
self.__histogram.appendWithDateTime(dateTime, macdValue) #macd
if len(self) >= self.__skipNum:
preMacdValue = self.__histogram[-2]
if self.cross_detect.is_cross(preMacdValue, macdValue, GoldCross):
cross = self.createNewCross(dateTime, DEATH, GOLD,
self.min_limit_detect)
log.debug("code:%s 类型:%s, 日期:%s, dif:%s, area:%s, dif date:%s, macd:%s, macd date:%s, close:%s, close date:%s" %\
(self.__instrument, cross.type, cross.cdate, cross.dif, cross.area, cross.dif_date, cross.macd, cross.macd_date, cross.close, cross.close_date))
self.__cross.appendWithDateTime(dateTime, cross)
#self.bottom_divergences = self.bottom_divergence_detect.get_divergences(self.__cross, self, self.__histogram)
self.double_bottom_divergences = self.bottom_divergence_detect.get_double_divergences(
self.__cross, self, self.__histogram)
elif self.cross_detect.is_cross(preMacdValue, macdValue,
DeathCross):
cross = self.createNewCross(dateTime, GOLD, DEATH,
self.max_limit_detect)
log.debug("code:%s 类型:%s, 日期:%s, dif:%s, area:%s, dif date:%s, macd:%s, macd date:%s, close:%s, close date:%s" %\
(self.__instrument, cross.type, cross.cdate, cross.dif, cross.area, cross.dif_date, cross.macd, cross.macd_date, cross.close, cross.close_date))
self.__cross.appendWithDateTime(dateTime, cross)
#self.top_divergences = self.top_divergence_detect.get_divergences(self.__cross, self, self.__histogram)
self.double_top_divergences = self.top_divergence_detect.get_double_divergences(
self.__cross, self, self.__histogram)
else:
log.debug("%s 没有信号" % dateTime)
else:
log.debug("%s 还需要skip" % dateTime)
def __init_pivot_levels(levels, maxLen=None):
return {l: SequenceDataSeries(maxLen) for l in levels}
def initEa(self, timeFrom=None, timeTo=None):
self.results = {}
feed = self.getFeedNew(timeFrom=timeFrom, timeTo=timeTo)
self.mid_DEFAULT_MAX_LEN = 10 * DEFAULT_MAX_LEN
mid_DEFAULT_MAX_LEN = self.mid_DEFAULT_MAX_LEN
#mid set init cash
cash_or_brk = 1000000
volumeLimit = 0.5 #mid used to calculate available volume for an order: availableVolume = volumeLeft * volumeLimit
#mid set fillstrategy
fillStrategy = fillstrategy.DefaultStrategy(volumeLimit=volumeLimit)
broker = backtesting.Broker(cash_or_brk, feed)
broker.setFillStrategy(fillStrategy)
#mid init base
strategy.BacktestingStrategy.__init__(self, feed, broker)
#mid 计算ma将使用当天的收盘价格计算
#mid 1)
self.closePrices = {}
self.longPosition = {}
self.shortPosition = {}
self.buySignal = {}
self.sellSignal = {}
self.timeFrom = timeFrom
self.timeTo = timeTo
#mid follow vars will be used only this class
self.__portfolio_value = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 记录资产组合(cash + 各个持仓证券的价值和)的合计价值变化
self.__available_cash = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 记录资产组合的现金变化
self.__long_exitBar_pnl = {} #mid 多头平仓bar产生的pnl
self.__long_position_volume = {} #mid 当前多头数量
self.__long_position_cost = {} #mid 当前持有多头开仓成本
self.__long_position_currentBar_pnl = {} #mid 当前持有多头当前bar产生的pnl
self.__long_position_pnl = {} #mid 当前多头累计产生的pnl
self.__short_exitBar_pnl = {}
self.__short_position_volume = {} #mid 当前持有头寸数量
self.__short_position_cost = {} #mid 当前持有头寸开仓成本
self.__short_position_currentBar_pnl = {} #mid 当前持有头寸价值
self.__short_position_pnl = {}
self.__position_cumulativePNL = {
} #mid 当前 symbol 持有头寸cumulative pnl 价值(包括该symbol多头和空头的所有开仓平仓产生的pnl)
self.__buy = {}
self.__sell = {}
for instrument in self.instruments:
dataSeries = feed[instrument]
dataSeries.setMaxLen(mid_DEFAULT_MAX_LEN)
closeSeries = dataSeries.getCloseDataSeries()
#mid 2)
prices = closeSeries
prices.setMaxLen(mid_DEFAULT_MAX_LEN)
#mid follow vars will be used in subclass
self.closePrices[instrument] = prices
self.longPosition[instrument] = None
self.shortPosition[instrument] = None
self.buySignal[instrument] = False
self.sellSignal[instrument] = False
#mid follow vars will be used only this class
self.__long_exitBar_pnl[instrument] = None
self.__short_exitBar_pnl[instrument] = None
self.__long_position_volume[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量
self.__short_position_volume[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量
self.__long_position_cost[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本
self.__short_position_cost[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本
self.__long_position_currentBar_pnl[
instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值
self.__short_position_currentBar_pnl[
instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值
self.__short_position_pnl[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN)
self.__long_position_pnl[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN)
self.__position_cumulativePNL[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN)
self.__buy[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN)
self.__sell[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN)
def __init__(self,
feed=None,
instrument='',
shortPeriod=0,
longPeriod=0,
money=None,
longAllowed=True,
shortAllowed=True):
strategy.BacktestingStrategy.__init__(self, feed)
self.position_cost = 0 #mid init position value
mid_DEFAULT_MAX_LEN = 10 * DEFAULT_MAX_LEN
self.__instrument = instrument
self.__longPosition = None
self.__shortPosition = None
self.__position_volume = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量
self.__position_cost = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本
self.__position_pnl = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值
self.__portfolio_value = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
self.__buy = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
self.__sell = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
self.__buySignal = False
self.__sellSignal = False
self.money = money
self.longAllowed = True
self.shortAllowed = True
#mid 计算ma将使用当天的收盘价格计算
#mid 1)
dataSeries = feed[instrument]
dataSeries.setMaxLen(mid_DEFAULT_MAX_LEN)
closeSeries = dataSeries.getOpenDataSeries()
#mid 2)
prices = closeSeries
prices.setMaxLen(mid_DEFAULT_MAX_LEN)
#mid 3)
self.__sma = ma.SMA(prices, shortPeriod, maxLen=mid_DEFAULT_MAX_LEN)
self.__lma = ma.SMA(prices, longPeriod, maxLen=mid_DEFAULT_MAX_LEN)
self.i = 0
class bollinger_band(strategy.BacktestingStrategy):
def __init__(self, feed, instrument, bollingerlength, numStdDev):
strategy.BacktestingStrategy.__init__(self, feed)
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0))
self.__instrument = instrument
self.__bollingerlength = int(bollingerlength)
self.__close = feed[instrument].getPriceDataSeries()
numStdDev = float(numStdDev) / 10
self.__longPos = []
self.__macd=macd.MACD(self.__close,50,150,10)
self.__bollinger = bollinger.BollingerBands(self.__macd, self.__bollingerlength, int(numStdDev))
self.__UpperBand = self.__bollinger.getUpperBand()
self.__LowerBand = self.__bollinger.getLowerBand()
self.__position = SequenceDataSeries()
self.__circ=5
def getPrice(self):
return self.__prices
def getMACD(self):
return self.__macd
def getBollingerBands(self):
return self.__bollinger
def testCon(self):
# record position
#######################################################################
if len(self.__longPos) > 0:
self.__position.append(len(self.__longPos))
elif len(self.__longPos)==0 :
self.__position.append(0)
#print(0)
def getTest(self):
return self.__position
def onBars(self, bars):
bar = bars[self.__instrument]
lower = self.__bollinger.getLowerBand()[-1]
upper = self.__bollinger.getUpperBand()[-1]
# print(self.getActivePositions())
if lower is None:
return
self.testCon()
if len(self.__longPos)> 0:
if self.exitLongSignal():
for pos in self.__longPos:
pos.exitMarket()
elif len(self.__longPos)<5 :
if self.enterLongSignal():
shares =1
# self.__longPos.
self.__longPos.append(self.enterLong(self.__instrument, shares))
def enterLongSignal (self) :
if self.__UpperBand[-1-self.__circ] is None:
return False
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] <= self.__LowerBand[-i-2]:
m1 += 1
if m1 >= self.__circ-1 and cross.cross_above(self.__macd,self.__LowerBand)>0:
return True
else:
return False
def enterShortSignal(self) :
if self.__UpperBand[-1-self.__circ] is None:
return False
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] >= self.__UpperBand[-i-2]:
m1 += 1
if m1 >= self.__circ-1 and cross.cross_below(self.__macd,self.__UpperBand)>0:
return True
else:
return False
def exitLongSignal(self) :
if self.__UpperBand[-1-self.__circ] is None:
return False
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] >= self.__UpperBand[-i-2]:
m1 += 1
if m1 >= self.__circ-1 and cross.cross_below(self.__macd,self.__UpperBand)>0:
return True
else:
return False
def exitShortSignal(self):
if self.__UpperBand[-1-self.__circ] is None:
return False
m1 = 0
for i in range(self.__circ):
if self.__macd[-i-1] <= self.__LowerBand[-i-2]:
m1 += 1
if m1 >= self.__circ-1 and cross.cross_above(self.__macd,self.__LowerBand)>0:
return True
else:
return False
def onEnterCanceled(self, position):
if len(self.__longPos)>0:
if self.__longPos[-1] == position:
del self.__longPos[-1]
#else:
#assert(False)
def onEnterOK(self,position):
pass
def onExitOk(self, position):
if isinstance(position,LongPosition):
self.__longPos = []
else:
assert(False)
def onExitCanceled(self, position):
position.exitMarket()
def metric_goquant_to_backtest(metric_data_series):
ret = SequenceDataSeries()
for i, v in metric_data_series.items():
ret.appendWithDateTime(i, v)
return ret
class SingleMA(strategy.BacktestingStrategy):
def __init__(self, feed, instrument, n, initialCash = 1000000):
strategy.BacktestingStrategy.__init__(self, feed, initialCash)
self.__instrument = instrument
self.getBroker().setFillStrategy(DefaultStrategy(None))
self.getBroker().setCommission(TradePercentage(0.001))
self.__position = None
self.__prices = feed[instrument].getPriceDataSeries()
self.__malength = int(n)
self.__ma = ma.SMA(self.__prices, self.__malength)
self.__pos = SequenceDataSeries() # record signal
def getPrice(self):
return self.__prices
def getMA(self):
return self.__ma
def testCon(self):
if self.__position is not None:
self.__pos.append(1)
elif self.__position is None:
self.__pos.append(0)
def getPos(self):
return self.__pos
def onEnterCanceled(self, position):
self.__position = None
def onEnterOk(self, position):
execInfo = position.getEntryOrder().getExecutionInfo()
instrumentInfo = position.getInstrument()
self.info("BUY %s at $%.2f" % (instrumentInfo, execInfo.getPrice()))
def onExitOk(self, position):
execInfo = position.getExitOrder().getExecutionInfo()
instrumentInfo = position.getInstrument()
self.info("SELL %s at $%.2f" % (instrumentInfo, execInfo.getPrice()))
self.__position = None
def onExitCancelled(self, position):
self.__position.exitMarket()
def onBars(self, bars):
closePrice = bars[self.__instrument].getPrice()
if self.__ma[-1] is None:
return
self.testCon()
if self.__position is not None:
if not self.__position.exitActive() and closePrice < self.__ma[-1]:
self.__position.exitMarket()
if self.__position is None:
if closePrice > self.__ma[-1]:
shares = int(self.getBroker().getEquity() * 0.9 / closePrice)
self.__position = self.enterLong(self.__instrument, shares)
def initEa(self,timeFrom=None,timeTo=None):
self.results = {}
feed = self.getFeedNew(timeFrom = timeFrom,timeTo = timeTo)
self.mid_DEFAULT_MAX_LEN = 10 * DEFAULT_MAX_LEN
mid_DEFAULT_MAX_LEN = self.mid_DEFAULT_MAX_LEN
#mid set init cash
cash_or_brk = 1000000
volumeLimit = 0.5 #mid used to calculate available volume for an order: availableVolume = volumeLeft * volumeLimit
#mid set fillstrategy
fillStrategy = fillstrategy.DefaultStrategy(volumeLimit = volumeLimit)
broker = backtesting.Broker(cash_or_brk, feed)
broker.setFillStrategy(fillStrategy)
#mid init base
strategy.BacktestingStrategy.__init__(self, feed,broker)
#mid 计算ma将使用当天的收盘价格计算
#mid 1)
self.closePrices = {}
self.longPosition = {}
self.shortPosition = {}
self.buySignal = {}
self.sellSignal = {}
self.timeFrom = timeFrom
self.timeTo = timeTo
#mid follow vars will be used only this class
self.__portfolio_value = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
self.__available_cash = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
self.__exitBar_position_pnl = {}
self.__curLongPositionCost = {} #mid init position value
self.__curShortPositionCost = {} #mid init position value
self.__position_volume = {} #mid 当前持有头寸数量
self.__position_cost = {} #mid 当前持有头寸开仓成本
self.__position_pnl = {} #mid 当前持有头寸价值
self.__position_cumulativePNL = {} #mid 当前 symbol 持有头寸cumulative pnl 价值
self.__buy = {}
self.__sell = {}
for instrument in self.instruments:
dataSeries = feed[instrument]
dataSeries.setMaxLen(mid_DEFAULT_MAX_LEN)
closeSeries = dataSeries.getCloseDataSeries()
#mid 2)
prices = closeSeries
prices.setMaxLen(mid_DEFAULT_MAX_LEN)
#mid follow vars will be used in subclass
self.closePrices[instrument] = prices
self.longPosition[instrument] = None
self.shortPosition[instrument] = None
self.buySignal[instrument] = False
self.sellSignal[instrument] = False
#mid follow vars will be used only this class
self.__curLongPositionCost[instrument] = 0 #mid init position value
self.__curShortPositionCost[instrument] = 0
self.__exitBar_position_pnl[instrument] = None
#mid init position value
self.__position_volume[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量
self.__position_cost[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本
self.__position_pnl[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值
self.__position_cumulativePNL[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
self.__buy[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
self.__sell[instrument] = SequenceDataSeries(maxLen = mid_DEFAULT_MAX_LEN)
class midBaseStrategy(strategy.BacktestingStrategy):
def getFeeds(self, timeFrom=None, timeTo=None):
import os, sys
xpower = os.path.abspath(
os.path.join(os.path.dirname(__file__), os.pardir, os.pardir,
os.pardir, 'midProjects', 'histdata'))
sys.path.append(xpower)
import dataCenter as dataCenter
self.dataCenter = dataCenter.dataCenter()
feeds = self.dataCenter.getFeedsForPAT(dataProvider=self.dataProvider,
storageType=self.storageType,
instruments=self.instruments,
period=self.period,
timeTo=timeTo,
timeFrom=timeFrom)
return feeds
def getFeedNew(self, timeFrom=None, timeTo=None):
'''mid should not be named the same with base class'''
import os, sys
xpower = os.path.abspath(
os.path.join(os.path.dirname(__file__), os.pardir, os.pardir,
os.pardir, 'midProjects', 'histdata'))
sys.path.append(xpower)
import dataCenter as dataCenter
self.dataCenter = dataCenter.dataCenter()
feed = self.dataCenter.getFeedForPAT(dataProvider=self.dataProvider,
storageType=self.storageType,
instruments=self.instruments,
period=self.period,
timeTo=timeTo,
timeFrom=timeFrom)
return feed
def initEa(self, timeFrom=None, timeTo=None):
self.results = {}
feed = self.getFeedNew(timeFrom=timeFrom, timeTo=timeTo)
self.mid_DEFAULT_MAX_LEN = 10 * DEFAULT_MAX_LEN
mid_DEFAULT_MAX_LEN = self.mid_DEFAULT_MAX_LEN
#mid set init cash
cash_or_brk = 1000000
volumeLimit = 0.5 #mid used to calculate available volume for an order: availableVolume = volumeLeft * volumeLimit
#mid set fillstrategy
fillStrategy = fillstrategy.DefaultStrategy(volumeLimit=volumeLimit)
broker = backtesting.Broker(cash_or_brk, feed)
broker.setFillStrategy(fillStrategy)
#mid init base
strategy.BacktestingStrategy.__init__(self, feed, broker)
#mid 计算ma将使用当天的收盘价格计算
#mid 1)
self.closePrices = {}
self.longPosition = {}
self.shortPosition = {}
self.buySignal = {}
self.sellSignal = {}
self.timeFrom = timeFrom
self.timeTo = timeTo
#mid follow vars will be used only this class
self.__portfolio_value = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 记录资产组合(cash + 各个持仓证券的价值和)的合计价值变化
self.__available_cash = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 记录资产组合的现金变化
self.__long_exitBar_pnl = {} #mid 多头平仓bar产生的pnl
self.__long_position_volume = {} #mid 当前多头数量
self.__long_position_cost = {} #mid 当前持有多头开仓成本
self.__long_position_currentBar_pnl = {} #mid 当前持有多头当前bar产生的pnl
self.__long_position_pnl = {} #mid 当前多头累计产生的pnl
self.__short_exitBar_pnl = {}
self.__short_position_volume = {} #mid 当前持有头寸数量
self.__short_position_cost = {} #mid 当前持有头寸开仓成本
self.__short_position_currentBar_pnl = {} #mid 当前持有头寸价值
self.__short_position_pnl = {}
self.__position_cumulativePNL = {
} #mid 当前 symbol 持有头寸cumulative pnl 价值(包括该symbol多头和空头的所有开仓平仓产生的pnl)
self.__buy = {}
self.__sell = {}
for instrument in self.instruments:
dataSeries = feed[instrument]
dataSeries.setMaxLen(mid_DEFAULT_MAX_LEN)
closeSeries = dataSeries.getCloseDataSeries()
#mid 2)
prices = closeSeries
prices.setMaxLen(mid_DEFAULT_MAX_LEN)
#mid follow vars will be used in subclass
self.closePrices[instrument] = prices
self.longPosition[instrument] = None
self.shortPosition[instrument] = None
self.buySignal[instrument] = False
self.sellSignal[instrument] = False
#mid follow vars will be used only this class
self.__long_exitBar_pnl[instrument] = None
self.__short_exitBar_pnl[instrument] = None
self.__long_position_volume[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量
self.__short_position_volume[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量
self.__long_position_cost[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本
self.__short_position_cost[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本
self.__long_position_currentBar_pnl[
instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值
self.__short_position_currentBar_pnl[
instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值
self.__short_position_pnl[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN)
self.__long_position_pnl[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN)
self.__position_cumulativePNL[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN)
self.__buy[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN)
self.__sell[instrument] = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN)
def getAssetStructure(self):
#mid --------------------------------
#mid 当前账户资产结构如下方式获取
#mid Long 和 Short不会同时存在
#mid 在开仓前，若有反向持仓，则此过程查询并输出已持有的反向持仓
broker = self.getBroker()
portfolio_value = broker.getEquity()
cash = broker.getCash()
if self.shortPosition is not None or self.longPosition is not None:
bars = self.getFeed().getCurrentBars()
positions = broker.getPositions()
positionsOpenValue = {}
positionsCloseValue = {}
for key, value in positions.items():
print "key:" + key + ",value:" + str(value)
bar = bars.getBar(key)
openPrice = bar.getOpen()
closePrice = bar.getClose()
share = broker.getShares(key)
positionsOpenValue[key] = openPrice * share
positionsCloseValue[key] = closePrice * share
print
print 'current bar asset structure'
print 'open cash %2.f.' % (cash)
for key, value in positionsOpenValue.items():
print "key:" + key + ",value:" + str(value)
print 'close cash %2.f.' % (cash)
for key, value in positionsCloseValue.items():
print "key:" + key + ",value:" + str(value)
print 'portfolio:%2.f' % (portfolio_value)
return portfolio_value, cash, sum(positionsCloseValue.values())
return portfolio_value, cash, 0
def sampleSub01(self, instrument):
"""mid not called anywhere
because of open price gap,method below is not right.
"""
broker = self.getBroker()
a = broker.getEquity()
b = self.getResult()
lastOpenPrice = None
lastClosePrice = None
bar = self.getFeed().getLastBar(instrument)
if bar is not None:
lastOpenPrice = bar.getOpen()
lastClosePrice = bar.getClose()
#lastPrice = self.getLastPrice(instrument)
pnl = (lastClosePrice - lastOpenPrice) * share
else:
pnl = 0 #mid instrument is dislisted.
if (len(self.__position_cumulativePNL[instrument]) > 0):
lastCumulativePNL = self.__position_cumulativePNL[instrument][-1]
else:
lastCumulativePNL = 0
def recordAccount(self):
# record position
#######################################################################
broker = self.getBroker()
curTime = self.getCurrentDateTime()
currentTime = self.getCurrentDateTime()
cash = broker.getCash(includeShort=False)
portfolio_value = broker.getEquity() #mid 按close价格计算的权益
print
self.info("onBars().recordAccount().Current time:%s" %
(str(currentTime)))
self.info("onBars().recordAccount().----portfolio value: %.2f" %
(portfolio_value))
self.info("onBars().recordAccount().----cash in portfolio: %.2f" %
(cash))
self.__portfolio_value.appendWithDateTime(currentTime, portfolio_value)
self.__available_cash.appendWithDateTime(currentTime, cash)
totalCumulativePNL = 0
time = self.getCurrentDateTime()
if (time == dt.datetime(2010, 12, 22, 0, 0)):
a = 8
for instrument in self.instruments:
lastClosePrice = self.getLastPrice(instrument)
if (lastClosePrice is None):
continue
#position_value = lastClosePrice*share
longPosition = self.longPosition[instrument]
longQuantity = 0
longPnl = 0
longStandingCurBarPnl = 0
longValue = 0
longCost = 0
shortPosition = self.shortPosition[instrument]
shortQuantity = 0
shortPnl = 0
shortStandingCurBarPnl = 0
shortValue = 0
shortCost = 0
if (longPosition):
entryInfo = longPosition.getEntryOrder()
execInfo = entryInfo.getExecutionInfo()
if (execInfo):
longPnl = longPosition.getPnL()
longStandingCurBarPnl = longPnl - self.__lastLongPnl
longQuantity = longPosition.getQuantity()
longCostPrice = execInfo.getPrice()
longCost = longQuantity * longCostPrice
self.__lastLongPnl = longPnl
if (shortPosition):
entryInfo = shortPosition.getEntryOrder()
execInfo = entryInfo.getExecutionInfo()
if (execInfo):
shortPnl = shortPosition.getPnL()
shortStandingCurBarPnl = shortPnl - self.__lastShortPnl
shortQuantity = shortPosition.getQuantity()
shortCostPrice = execInfo.getPrice()
shortCost = shortQuantity * shortCostPrice
self.__lastShortPnl = shortPnl
if (self.__long_exitBar_pnl[instrument]):
self.__long_position_currentBar_pnl[
instrument].appendWithDateTime(
currentTime, self.__long_exitBar_pnl[instrument])
self.__long_exitBar_pnl[instrument] = None
else:
self.__long_position_currentBar_pnl[
instrument].appendWithDateTime(currentTime,
longStandingCurBarPnl)
if (self.__short_exitBar_pnl[instrument]):
self.__short_position_currentBar_pnl[
instrument].appendWithDateTime(
currentTime, self.__short_exitBar_pnl[instrument])
self.__short_exitBar_pnl[instrument] = None
else:
self.__short_position_currentBar_pnl[
instrument].appendWithDateTime(currentTime,
shortStandingCurBarPnl)
#self.__short_position_pnl[instrument].appendWithDateTime(currentTime,shortCurBarPnl)
self.__long_position_pnl[instrument].appendWithDateTime(
currentTime, longPnl)
self.__short_position_pnl[instrument].appendWithDateTime(
currentTime, shortPnl)
self.__long_position_cost[instrument].appendWithDateTime(
currentTime, longCost)
self.__short_position_cost[instrument].appendWithDateTime(
currentTime, shortCost)
self.__long_position_volume[instrument].appendWithDateTime(
currentTime, longQuantity)
self.__short_position_volume[instrument].appendWithDateTime(
currentTime, shortQuantity)
self.__buy[instrument].appendWithDateTime(
currentTime, self.buySignal[instrument])
self.__sell[instrument].appendWithDateTime(
currentTime, self.sellSignal[instrument])
cumulativePNL = 0
longCurBarPnl = self.__long_position_currentBar_pnl[instrument][-1]
shortCurBarPnl = self.__short_position_currentBar_pnl[instrument][
-1]
currentBarPnl = longCurBarPnl + shortCurBarPnl
if (len(self.__position_cumulativePNL[instrument]) > 0):
lastCumulativePNL = self.__position_cumulativePNL[instrument][
-1]
cumulativePNL = lastCumulativePNL + currentBarPnl
else:
cumulativePNL = currentBarPnl
self.__position_cumulativePNL[instrument].appendWithDateTime(
currentTime, cumulativePNL)
"""mid
如果当前bar有某个position在open price被closed掉，则当前bar的position_pnl是0.
在当前bar的openprice和上一bar的closeprice之间没有gap时，这个算法是合理的，但是，gap往往是存在的，
所以，据此计算的barPnl在exitbar上会有gap导致的误差
在此特别处理exitbar
"""
"""
if(self.__exitBar_position_pnl[instrument] is not None):
currentExitedPositionPnl = self.__exitBar_position_pnl[instrument]
lastPositionPnl = self.__position_pnl[instrument][-2]
currentBarExitedPnl = currentExitedPositionPnl - lastPositionPnl
self.__exitBar_position_pnl[instrument] = None
currentBarPnl = currentBarPnl + currentBarExitedPnl
if(len(self.__position_cumulativePNL[instrument])>0):
lastCumulativePNL = self.__position_cumulativePNL[instrument][-1]
cumulativePNL = lastCumulativePNL + currentBarPnl
else:
cumulativePNL = currentBarPnl
self.__position_cumulativePNL[instrument].appendWithDateTime(currentTime,cumulativePNL)
"""
if (True):
self.info("onBars().recordAccount().--------%s" % (instrument))
self.info(
"onBars().recordAccount().--------mid current bar longPNL: %.3f"
% (longCurBarPnl))
self.info(
"onBars().recordAccount().--------mid current bar longQuantity:%.3f"
% (longQuantity))
self.info(
"onBars().recordAccount().--------mid current bar longValue: %.3f"
% (longValue))
self.info(
"onBars().recordAccount().--------mid current bar longCost: %.3f"
% (longCost))
self.info(
"onBars().recordAccount().--------mid current bar shortPNL: %.3f"
% (shortPnl))
self.info(
"onBars().recordAccount().--------mid current bar shortQuantity:%.3f"
% (shortQuantity))
self.info(
"onBars().recordAccount().--------mid calculated position value: %.3f"
% (shortValue))
self.info(
"onBars().recordAccount().--------mid calculated shortPnl: %.3f"
% (shortCost))
self.info(
"onBars().recordAccount().--------mid CumulativePNL: %.3f"
% (cumulativePNL))
totalCumulativePNL = totalCumulativePNL + cumulativePNL
if (abs(1000000 -
(portfolio_value - totalCumulativePNL)) > 0.00000001):
self.info("onBars().recordAccount().--------mid initCash: %.3f" %
(portfolio_value - totalCumulativePNL))
a = 8
def getPortfolioValue(self):
return self.__portfolio_value
def getAvailableCash(self):
return self.__available_cash
def getCurInstrument(self):
return self.curInstrument
def getPositionValue(self, instrument):
return self.__position_cumulativePNL[instrument]
def getLongVolume(self, instrument):
return self.__long_position_volume[instrument]
def getShortVolume(self, instrument):
return self.__short_position_volume[instrument]
def getLongCost(self, instrument):
return self.__long_position_cost[instrument]
def getShortCost(self, instrument):
return self.__short_position_cost[instrument]
def getLongPnl(self, instrument):
return self.__long_position_pnl[instrument]
def getShortPnl(self, instrument):
return self.__short_position_pnl[instrument]
def getBuy(self, instrument):
return self.__buy[instrument]
def getSell(self, instrument):
return self.__sell[instrument]
def onEnterOk(self, position):
'''mid
由于getEquity()返回的是依据当日close价格计算出来的权益
所以，这个值不能作为持仓成本
持仓成本需要以onEnterOk时bar的open价格计算
由于经常有跳开现象，所以依据bar(n-1).close发出的market order，
在bar(n).open执行时通常会有gap出现，表现在position_cost图上时就是持有成本离计划成本会有跳口，
'''
print
currentTime = self.getCurrentDateTime()
execInfo = position.getEntryOrder().getExecutionInfo()
self.info("onEnterOK().ExecutionInfo.Current time: %s" %
(execInfo.getDateTime()))
#mid 1)record the position cost
instrument = position.getInstrument()
feed = self.getFeed()
bars = feed.getCurrentBars()
bar = bars.getBar(instrument)
openPrice = bar.getOpen()
closePrice = self.getLastPrice(
instrument) #mid lastPrice == closePrice
#mid 2)log account info after enterOKed.
execInfo = position.getEntryOrder().getExecutionInfo()
portfolio = self.getResult()
cash = self.getBroker().getCash()
self.info("onEnterOk().symbol:%s" % (instrument))
self.info("onEnterOk().current available cash: %.2f,portfolio: %.2f." %
(cash, portfolio))
if isinstance(position, strategy.position.LongPosition):
self.__lastLongPnl = 0
self.info("onEnterOK().ExecutionInfo: %s,OPEN LONG %.2f at $%.2f" %
(execInfo.getDateTime(), execInfo.getQuantity(),
execInfo.getPrice()))
elif isinstance(position, strategy.position.ShortPosition):
self.__lastShortPnl = 0
self.info(
"onEnterOK().ExecutionInfo: %s,OPEN SHORT %.2f at $%.2f" %
(execInfo.getDateTime(), execInfo.getQuantity(),
execInfo.getPrice()))
def onEnterCanceled(self, position):
instrument = position.getInstrument()
self.info("onEnterCanceled().current available cash: %.2f." %
(self.getBroker().getCash()))
if isinstance(position, strategy.position.LongPosition):
self.longPosition[instrument] = None
self.info("onEnterCanceled().OPEN LONG cancled.")
elif isinstance(position, strategy.position.ShortPosition):
self.shortPosition[instrument] = None
self.info("onEnterCanceled().OPEN SHORT cancled.")
def onExitOk(self, position):
exitInfo = position.getExitOrder().getExecutionInfo()
entryInfo = position.getEntryOrder().getExecutionInfo()
instrument = position.getInstrument()
print
currentTime = self.getCurrentDateTime()
self.info("onExitOk().ExecutionInfo.Current time: %s" %
(exitInfo.getDateTime()))
self.info("onExitOk().instrument:%s." % (instrument))
exitQuantity = exitInfo.getQuantity()
exitPrice = exitInfo.getPrice()
exitAmount = exitQuantity * exitPrice
entryQuantity = entryInfo.getQuantity()
entryPrice = entryInfo.getPrice()
entryCost = entryQuantity * entryPrice
#self.sampleSub01(instrument)
if isinstance(position, strategy.position.LongPosition):
positionCost = entryCost
longPnl = position.getPnL()
longCurBarPnl = longPnl - self.__lastLongPnl
#self.__long_position_pnl[instrument].appendWithDateTime(currentTime,longCurBarPnl)
self.__long_exitBar_pnl[instrument] = longCurBarPnl
self.longPosition[instrument] = None
self.info("onExitOk().ExecutionInfo: %s,CLOSE LONG %.2f at $%.2f" %
(exitInfo.getDateTime(), exitQuantity, exitPrice))
elif isinstance(position, strategy.position.ShortPosition):
positionCost = entryCost
shortPnl = position.getPnL()
shortCurBarPnl = shortPnl - self.__lastShortPnl
#self.__long_position_pnl[instrument].appendWithDateTime(currentTime,longCurBarPnl)
self.__short_exitBar_pnl[instrument] = shortCurBarPnl
self.shortPosition[instrument] = None
self.info("onExitOk().ExecutionInfo: %s,CLOSE LONG %.2f at $%.2f" %
(exitInfo.getDateTime(), exitQuantity, exitPrice))
def onExitCanceled(self, position):
# If the exit was canceled, re-submit it.
if isinstance(position, strategy.position.LongPosition):
self.longPosition[instrument] = None
elif isinstance(position, strategy.position.ShortPosition):
self.shortPosition[instrument] = None
def logInfo(self, bars=None):
pLong, pShort = 0, 0
if (self.longPosition is not None):
pLong = self.longPosition.getShares()
if (self.shortPosition is not None):
pShort = self.shortPosition.getShares()
bar = bars[self.instrument]
pOpen = bar.getOpen()
pHigh = bar.getHigh()
pLow = bar.getLow()
pClose = bar.getClose()
pPrice = bar.getPrice()
self.info(
'logInfo().price:%.3f,open:%.2f,high:%.2f,low:%.2f,close:%.2f' %
(pPrice, pOpen, pHigh, pLow, pClose))
#self.info('long:%.2f#short:%.2f'%(pLong,pShort))
def closePosition(self):
for instrument in self.instruments:
if (self.longPosition[instrument] is not None
and self.sellSignal[instrument] == True
and not self.longPosition[instrument].exitActive()):
print
self.info("onBars().closePosition(), instrument:%s" %
(instrument))
self.info(
"onBars().closePosition(), LONG POSITION to close %.2f" %
(self.longPosition[instrument].getShares()))
self.longPosition[instrument].exitMarket()
if (self.shortPosition[instrument] is not None
and self.buySignal[instrument] == True
and not self.shortPosition[instrument].exitActive()):
print
self.info("onBars().closePosition(), instrument:%s" %
(instrument))
self.info(
"onBars().closePosition(), SHORT POSITION to close %.2f" %
(self.shortPosition[instrument].getShares()))
self.shortPosition[instrument].exitMarket()
def openPosition(self):
'''mid
此处是onBars，这个和zipline的概念完全不同
zipline中，需要覆写的是handle_data，这个东西是个tick概念，所以没有OHLC的，只是个price
PAT中，每次onBars，都会传入一个newbar的OHLC，此时，要如何按这个OHLC决策，全由你
依据OHLC做完决策后，可以发送交易指令：
* Order.Type.MARKET
* Order.Type.LIMIT
* Order.Type.STOP
* Order.Type.STOP_LIMIT
1.市价单，依据下一个bar的openPrice执行命令：
self.enterLong()
2.限价单
3.止损单市价单
4.止损限价单
当前似乎没有止盈单
在均线策略中，应该在每个newbar到来时，按closePrice的均线计算指标值，然后发送市价单
1.每个newbar按close价格计算指标，并在下一个bar按open成交
2.每个newbar按open价格计算指标，并在此newbar按open成交
以上1,2的计算逻辑是一致的。如果当前bar的close和下一个bar的open相差无几时，两种算法的回测结果也应相差无几
'''
# mid 2)open
if (self.shortAllowed):
for instrument in self.instruments:
self.curInstrument = instrument
if (self.sellSignal[instrument] == True):
# Enter a buy market order. The order is good till canceled.
bar = self.getFeed().getLastBar(instrument)
volume = 0
lastClose = 0
if bar is not None:
volume = bar.getVolume()
lastClose = bar.getClose()
shares = self.money.getShares(strat=self)
print
self.info("onBars().openPosition(), instrument %s" %
(instrument))
self.info(
"onBars().openPosition(), SHORT POSITION to open %.2f"
% (shares))
self.info("onBars().openPosition(), lastClose: %.2f,%.2f" %
(self.getLastPrice(instrument), lastClose))
self.info("onBars().openPosition(), need amount: %.2f" %
(shares * self.getLastPrice(instrument)))
self.info(
"onBars().openPosition(), available amount: %.2f." %
(self.getBroker().getCash()))
self.info(
"onBars().openPosition(), available volume: %.2f." %
(volume))
self.shortPosition[instrument] = self.enterShort(
instrument, shares, True)
if (self.longAllowed):
for instrument in self.instruments:
self.curInstrument = instrument
if (self.buySignal[instrument] == True):
shares = self.money.getShares(strat=self)
print
self.info("onBars().openPosition(), instrument %s" %
(instrument))
self.info(
"onBars().openPosition(), LONG POSITION to open %.2f" %
(shares))
self.info("onBars().openPosition(), need amount: %.2f." %
(shares * self.getLastPrice(instrument)))
self.info(
"onBars().openPosition(), available amount: %.2f." %
(self.getBroker().getCash()))
self.longPosition[instrument] = self.enterLong(
instrument, shares, True)
def __analiseEachSymbol(self, instrument):
dataForCandle = self.dataCenter.getCandleData(
dataProvider=self.dataProvider,
dataStorage=self.storageType,
dataPeriod=self.period,
symbol=instrument,
dateStart=self.timeFrom,
dateEnd=self.timeTo)
self.analyzer.analyseEachSymbol(self.results[instrument],
dataForCandle,
InKLine=self.InKLine)
def __analiseSummary(self):
dataProvider = self.benchDataProvider
instrument = self.benchSymbol
dataForCandle = self.dataCenter.getCandleData(
dataProvider=dataProvider,
dataStorage=self.storageType,
dataPeriod=self.period,
symbol=instrument,
dateStart=self.timeFrom,
dateEnd=self.timeTo)
self.analyzer.analyseSummary(self.result, dataForCandle)
def run(self, timeFrom=None, timeTo=None):
self.initEa(timeFrom=timeFrom, timeTo=timeTo)
self.initIndicators()
#self.strat.setUseAdjustedValues(False)
self.initAnalyzer()
strategy.BacktestingStrategy.run(self)
for instrument in self.instruments:
buy = self.getBuy(instrument)
sell = self.getSell(instrument)
position_value = self.getPositionValue(instrument)
long_volume = self.getLongVolume(instrument)
short_volume = self.getShortVolume(instrument)
long_cost = self.getLongCost(instrument)
long_pnl = self.getLongPnl(instrument)
short_cost = self.getShortCost(instrument)
short_pnl = self.getShortPnl(instrument)
self.results[instrument] = pd.DataFrame(
{
'long_volume': list(long_volume),
'long_cost': list(long_cost),
'long_pnl': list(long_pnl),
'short_cost': list(short_cost),
'short_pnl': list(short_pnl),
'buy': list(buy),
'sell': list(sell),
'position_value': list(position_value)
},
columns=[
'long_volume', 'long_cost', 'long_pnl', 'short_cost',
'short_pnl', 'buy', 'sell', 'position_value'
],
index=long_volume.getDateTimes())
self.addIndicators(instrument)
#------------------------------------
if (self.toPlotEachSymbol):
self.__analiseEachSymbol(instrument)
if (self.toPlotSummary):
portfolio_value = self.getPortfolioValue()
available_cash = self.getAvailableCash()
self.result = pd.DataFrame(
{
'available_cash': list(available_cash),
'portfolio_value': list(portfolio_value)
},
columns=['available_cash', 'portfolio_value'],
index=portfolio_value.getDateTimes())
self.__analiseSummary()
return self.results
#mid from ea
#----------------------------------------------------------------------
def summary(self):
return "from %s to %s:returns:%.2f%%,sharpe:%.2f,MaxDrawdown:%.2f%%,Longest drawdown duration:(%s)" % (
str(self.timeFrom), str(self.timeTo),
self.returnsAnalyzer.getCumulativeReturns()[-1] * 100,
self.sharpeRatioAnalyzer.getSharpeRatio(0.05),
self.drawdownAnalyzer.getMaxDrawDown() * 100,
self.drawdownAnalyzer.getLongestDrawDownDuration())
def detail(self):
""""""
print "-------------------------------------------------------------------------"
print "Final portfolio value: $%.2f" % self.getResult()
print "Cumulative returns: %.2f %%" % (
self.returnsAnalyzer.getCumulativeReturns()[-1] * 100)
print "Sharpe ratio: %.2f" % (
self.sharpeRatioAnalyzer.getSharpeRatio(0.05))
print "Max. drawdown: %.2f %%" % (
self.drawdownAnalyzer.getMaxDrawDown() * 100)
print "Longest drawdown duration: (%s)" % (
self.drawdownAnalyzer.getLongestDrawDownDuration())
print
print "Total trades: %d" % (self.tradesAnalyzer.getCount())
if self.tradesAnalyzer.getCount() > 0:
profits = self.tradesAnalyzer.getAll()
print "Avg. profit: $%2.f" % (profits.mean())
print "Profits std. dev.: $%2.f" % (profits.std())
print "Max. profit: $%2.f" % (profits.max())
print "Min. profit: $%2.f" % (profits.min())
returns = self.tradesAnalyzer.getAllReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print
print "Profitable trades: %d" % (
self.tradesAnalyzer.getProfitableCount())
if self.tradesAnalyzer.getProfitableCount() > 0:
profits = self.tradesAnalyzer.getProfits()
print "Avg. profit: $%2.f" % (profits.mean())
print "Profits std. dev.: $%2.f" % (profits.std())
print "Max. profit: $%2.f" % (profits.max())
print "Min. profit: $%2.f" % (profits.min())
returns = self.tradesAnalyzer.getPositiveReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print
print "Unprofitable trades: %d" % (
self.tradesAnalyzer.getUnprofitableCount())
if self.tradesAnalyzer.getUnprofitableCount() > 0:
losses = self.tradesAnalyzer.getLosses()
print "Avg. loss: $%2.f" % (losses.mean())
print "Losses std. dev.: $%2.f" % (losses.std())
print "Max. loss: $%2.f" % (losses.min())
print "Min. loss: $%2.f" % (losses.max())
returns = self.tradesAnalyzer.getNegativeReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print "-------------------------------------------------------------------------"
def initAnalyzer(self):
from pyalgotrade.stratanalyzer import sharpe
from pyalgotrade.stratanalyzer import returns
from pyalgotrade.stratanalyzer import drawdown
from pyalgotrade.stratanalyzer import trades
# 1.0) 策略结果
self.returnsAnalyzer = returns.Returns()
# 1.1) 夏普比率
self.sharpeRatioAnalyzer = sharpe.SharpeRatio()
# 1.2)
self.drawdownAnalyzer = drawdown.DrawDown()
# 1.3)
self.tradesAnalyzer = trades.Trades()
self.attachAnalyzer(self.sharpeRatioAnalyzer)
self.attachAnalyzer(self.returnsAnalyzer)
self.attachAnalyzer(self.tradesAnalyzer)
self.attachAnalyzer(self.drawdownAnalyzer)
class DMACrossOver(strategy.BacktestingStrategy):
def __init__(self,
feed=None,
instrument='',
shortPeriod=0,
longPeriod=0,
money=None,
longAllowed=True,
shortAllowed=True):
strategy.BacktestingStrategy.__init__(self, feed)
self.position_cost = 0 #mid init position value
mid_DEFAULT_MAX_LEN = 10 * DEFAULT_MAX_LEN
self.__instrument = instrument
self.__longPosition = None
self.__shortPosition = None
self.__position_volume = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸数量
self.__position_cost = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸开仓成本
self.__position_pnl = SequenceDataSeries(
maxLen=mid_DEFAULT_MAX_LEN) #mid 当前持有头寸价值
self.__portfolio_value = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
self.__buy = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
self.__sell = SequenceDataSeries(maxLen=mid_DEFAULT_MAX_LEN)
self.__buySignal = False
self.__sellSignal = False
self.money = money
self.longAllowed = True
self.shortAllowed = True
#mid 计算ma将使用当天的收盘价格计算
#mid 1)
dataSeries = feed[instrument]
dataSeries.setMaxLen(mid_DEFAULT_MAX_LEN)
closeSeries = dataSeries.getOpenDataSeries()
#mid 2)
prices = closeSeries
prices.setMaxLen(mid_DEFAULT_MAX_LEN)
#mid 3)
self.__sma = ma.SMA(prices, shortPeriod, maxLen=mid_DEFAULT_MAX_LEN)
self.__lma = ma.SMA(prices, longPeriod, maxLen=mid_DEFAULT_MAX_LEN)
self.i = 0
def getAssetStructure(self):
#mid --------------------------------
#mid 当前账户资产结构如下方式获取
#mid Long 和 Short不会同时存在
#mid 在开仓前，若有反向持仓，则此过程查询并输出已持有的反向持仓
broker = self.getBroker()
portfolio_value = broker.getEquity()
cash = broker.getCash()
if self.__shortPosition is not None or self.__longPosition is not None:
bars = self.getFeed().getCurrentBars()
positions = broker.getPositions()
positionsOpenValue = {}
positionsCloseValue = {}
for key, value in positions.items():
print "key:" + key + ",value:" + str(value)
bar = bars.getBar(key)
openPrice = bar.getOpen()
closePrice = bar.getClose()
share = broker.getShares(key)
positionsOpenValue[key] = openPrice * share
positionsCloseValue[key] = closePrice * share
print
print 'current bar asset structure'
print 'open cash %2.f.' % (cash)
for key, value in positionsOpenValue.items():
print "key:" + key + ",value:" + str(value)
print 'close cash %2.f.' % (cash)
for key, value in positionsCloseValue.items():
print "key:" + key + ",value:" + str(value)
print 'portfolio:%2.f' % (portfolio_value)
return portfolio_value, cash, sum(positionsCloseValue.values())
return portfolio_value, cash, 0
def recordPositions(self):
# record position
#######################################################################
broker = self.getBroker()
position = broker.getPositions() #mid position is dict of share
share = broker.getShares(
self.__instrument) #mid position is dict of share
lastPrice = self.getLastPrice(self.__instrument)
portfolio_value = broker.getEquity() #mid 按close价格计算的权益
cash = broker.getCash()
position_value = portfolio_value - cash
position_pnl = position_value - self.position_cost
print
print 'cash: %.2f' % (cash)
print 'position value: %.2f' % (portfolio_value - cash)
print 'mid calc: %.2f' % (lastPrice * share + cash)
print 'broker returned: %.2f' % (portfolio_value)
curTime = self.getCurrentDateTime()
if (False):
yLimit = self.money.getShares() * 1.1
if (self.i == 0):
self.__position.append(yLimit)
self.i = self.i + 1
elif (self.i == 1):
self.__position.append(-yLimit)
self.i = self.i + 1
else:
currentTime = self.getCurrentDateTime()
self.__position.appendWithDateTime(currentTime, abs(share))
#self.__position.append(share)
else:
currentTime = self.getCurrentDateTime()
self.__position_volume.appendWithDateTime(currentTime, abs(share))
self.__position_cost.appendWithDateTime(currentTime,
abs(self.position_cost))
self.__position_pnl.appendWithDateTime(currentTime, position_pnl)
self.__portfolio_value.appendWithDateTime(currentTime,
portfolio_value)
self.__buy.appendWithDateTime(currentTime, self.__buySignal)
self.__sell.appendWithDateTime(currentTime, self.__sellSignal)
def getInstrument(self):
return self.__instrument
def getPortfolio(self):
return self.__portfolio_value
def getPositionVolume(self):
return self.__position_volume
def getPositionCost(self):
return self.__position_cost
def getPositionPnl(self):
return self.__position_pnl
def getSMA(self):
return self.__sma
def getLMA(self):
return self.__lma
def getBuy(self):
return self.__buy
def getSell(self):
return self.__sell
def onEnterOk(self, position):
execInfo = position.getEntryOrder().getExecutionInfo()
portfolio = self.getResult()
cash = self.getBroker().getCash()
'''mid
以下两种方法都是为了计算持仓成本
由于getEquity()返回的是依据当日close价格计算出来的权益
所以，这个值不能作为持仓成本
持仓成本需要以onEnterOk时bar的open价格计算
所以应使用第二种算法
由于经常有跳开现象，所以依据bar(n-1).close发出的market order，
在bar(n).open执行时通常会有gap出现，表现在position_cost图上时就是持有成本离计划成本会有跳口，
'''
if (False): #mid two methods to cacl cost.
portfolio_value = self.getBroker().getEquity()
self.position_cost = portfolio_value - cash
else:
feed = self.getFeed()
bars = feed.getCurrentBars()
bar = bars.getBar(self.__instrument)
openPrice = bar.getOpen()
closePrice = self.getLastPrice(
self.__instrument) #mid lastPrice == closePrice
share = self.getBroker().getShares(self.__instrument)
self.position_cost = openPrice * share
self.info("onEnterOk().current available cash: %.2f,portfolio: %.2f." %
(cash, portfolio))
if isinstance(position, strategy.position.LongPosition):
self.info("onEnterOK().ExecutionInfo: %s,OPEN LONG %.2f at $%.2f" %
(execInfo.getDateTime(), execInfo.getQuantity(),
execInfo.getPrice()))
elif isinstance(position, strategy.position.ShortPosition):
self.info(
"onEnterOK().ExecutionInfo: %s,OPEN SHORT %.2f at $%.2f" %
(execInfo.getDateTime(), execInfo.getQuantity(),
execInfo.getPrice()))
def onEnterCanceled(self, position):
self.info("onEnterCanceled().current available cash: %.2f." %
(self.getBroker().getCash()))
if isinstance(position, strategy.position.LongPosition):
self.__longPosition = None
self.info("onEnterCanceled().OPEN LONG cancled.")
elif isinstance(position, strategy.position.ShortPosition):
self.__shortPosition = None
self.info("onEnterCanceled().OPEN SHORT cancled.")
def onExitOk(self, position):
execInfo = position.getExitOrder().getExecutionInfo()
portfolio = self.getResult()
cash = self.getBroker().getCash()
self.info("onExitOk().current available cash: %.2f,portfolio: %.2f." %
(cash, portfolio))
if isinstance(position, strategy.position.LongPosition):
self.__longPosition = None
self.info("onExitOk().ExecutionInfo: %s,CLOSE LONG %.2f at $%.2f" %
(execInfo.getDateTime(), execInfo.getQuantity(),
execInfo.getPrice()))
elif isinstance(position, strategy.position.ShortPosition):
self.__shortPosition = None
self.info(
"onExitOk().ExecutionInfo: %s,CLOSE SHORT %.2f at $%.2f" %
(execInfo.getDateTime(), execInfo.getQuantity(),
execInfo.getPrice()))
def onExitCanceled(self, position):
# If the exit was canceled, re-submit it.
if isinstance(position, strategy.position.LongPosition):
self.__longPosition = None
elif isinstance(position, strategy.position.ShortPosition):
self.__shortPosition = None
def logInfo(self, bars=None):
pLong, pShort = 0, 0
if (self.__longPosition is not None):
pLong = self.__longPosition.getShares()
if (self.__shortPosition is not None):
pShort = self.__shortPosition.getShares()
bar = bars[self.__instrument]
pOpen = bar.getOpen()
pHigh = bar.getHigh()
pLow = bar.getLow()
pClose = bar.getClose()
pPrice = bar.getPrice()
self.info(
'logInfo().price:%.3f,open:%.2f,high:%.2f,low:%.2f,close:%.2f' %
(pPrice, pOpen, pHigh, pLow, pClose))
#self.info('long:%.2f#short:%.2f'%(pLong,pShort))
def run(self):
strategy.BacktestingStrategy.run(self)
sma = self.getSMA()
lma = self.getLMA()
buy = self.getBuy()
sell = self.getSell()
portfolio_value = self.getPortfolio()
position_volume = self.getPositionVolume()
position_cost = self.getPositionCost()
position_pnl = self.getPositionPnl()
result = pd.DataFrame(
{
'position_volume': list(position_volume),
'position_cost': list(position_cost),
'position_pnl': list(position_pnl),
'short_ema': list(sma),
'long_ema': list(lma),
'buy': list(buy),
'sell': list(sell),
'portfolio_value': list(portfolio_value)
},
columns=[
'position_volume', 'position_cost', 'position_pnl',
'short_ema', 'long_ema', 'buy', 'sell', 'portfolio_value'
],
index=position_volume.getDateTimes())
return result
def onBars(self, bars):
'''mid
此处是onBars，这个和zipline的概念完全不同
zipline中，需要覆写的是handle_data，这个东西是个tick概念，所以没有OHLC的，只是个price
PAT中，每次onBars，都会传入一个newbar的OHLC，此时，要如何按这个OHLC决策，全由你
依据OHLC做完决策后，可以发送交易指令：
* Order.Type.MARKET
* Order.Type.LIMIT
* Order.Type.STOP
* Order.Type.STOP_LIMIT
1.市价单，依据下一个bar的openPrice执行命令：
self.enterLong()
2.限价单
3.止损单市价单
4.止损限价单
当前似乎没有止盈单
在均线策略中，应该在每个newbar到来时，按closePrice的均线计算指标值，然后发送市价单
1.每个newbar按close价格计算指标，并在下一个bar按open成交
2.每个newbar按open价格计算指标，并在此newbar按open成交
以上1,2的计算逻辑是一致的。如果当前bar的close和下一个bar的open相差无几时，两种算法的回测结果也应相差无几
'''
self.__buySignal, self.__sellSignal = False, False
# mid 1)close
if (self.longAllowed):
if self.__longPosition is not None and not self.__longPosition.exitActive(
):
#mid 有多仓，检查是否需要平仓
if (cross.cross_below(self.__sma, self.__lma) > 0):
print
self.info(
"onBars().Status info,before exitMarket(), LONG POSITION to close %.2f"
% (self.__longPosition.getShares()))
self.__longPosition.exitMarket()
if (self.shortAllowed):
if self.__shortPosition is not None and not self.__shortPosition.exitActive(
):
if (cross.cross_above(self.__sma, self.__lma) > 0):
print
self.info(
"onBars().Status info,before exitMarket(), SHORT POSITION to close %.2f"
% (self.__shortPosition.getShares()))
self.__shortPosition.exitMarket()
# mid 2)open
if (self.longAllowed):
if self.__longPosition is None:
#mid 无多仓，检查是否需要开多仓
if cross.cross_above(self.__sma, self.__lma) > 0:
# Enter a buy market order. The order is good till canceled.
shares = self.money.getShares(strat=self)
self.info(
"onBars().Status info,before enterLong(), LONG POSITION to open %.2f,need amount: %.2f,available amount: %.2f."
%
(shares, shares * self.getLastPrice(self.__instrument),
self.getBroker().getCash()))
self.__longPosition = self.enterLong(
self.__instrument, shares, True)
self.__buySignal = True
if (self.shortAllowed):
if self.__shortPosition is None:
if cross.cross_below(self.__sma, self.__lma) > 0:
# Enter a buy market order. The order is good till canceled.
shares = self.money.getShares(strat=self)
self.info(
"onBars().Status info,before enterShort(), SHORT POSITION to open %.2f,need amount: %.2f,available amount: %.2f."
%
(shares, shares * self.getLastPrice(self.__instrument),
self.getBroker().getCash()))
self.__shortPosition = self.enterShort(
self.__instrument, shares, True)
self.__sellSignal = True
self.recordPositions()
def adjustBars(self): for key, value in self.__barsDict.iteritems(): basicbars = [] bars = value bars_in_dtrange = [bar for bar in bars if self.__startdate.replace(tzinfo=None) <= bar.getDateTime() <= self.__enddate.replace(tzinfo=None)] bars_in_dtrange.sort(key=lambda bar: bar.getDateTime(), reverse=True) k = 0 splitdataList = [] dividendList = [] for bar in bars_in_dtrange: splitdata = float(bar.getSplit()) dividend = float(bar.getDividend()) if splitdata != 1.0: splitdataList.append(bar.getSplit()) if dividend != 0.0: adjFactor = (bar.getClose() + bar.getDividend()) / bar.getClose() dividendList.append(adjFactor) #### Special case.... end date / analysis date nothing to do.. if (k==0): bar = BasicBar(bar.getDateTime(), bar.getOpen() , bar.getHigh(), bar.getLow(), bar.getClose(), bar.getVolume(), bar.getClose(), Frequency.DAY) basicbars.append(bar) else: #### Adjust OHLC & Volume data for split adjustments and dividend adjustments Open = bar.getOpen() High = bar.getHigh() Low = bar.getLow() Close = bar.getClose() Volume = bar.getVolume() ### adjust data for splits for split in splitdataList: Open = Open / split High = High / split Low = Low / split Close = Close /split Volume = Volume * split ### adjust data for dividends for adjFactor in dividendList: Open = Open / adjFactor High = High / adjFactor Low = Low / adjFactor Close = Close / adjFactor Volume = Volume * adjFactor bar = BasicBar(bar.getDateTime(), Open , High, Low, Close, Volume, Close, Frequency.DAY) basicbars.append(bar) k +=1 DateTimes = [] OpenSeries = SequenceDataSeries(4000) HighSeries = SequenceDataSeries(4000) LowSeries = SequenceDataSeries(4000) CloseSeries = SequenceDataSeries(4000) VolumeSeries = SequenceDataSeries(4000) TypicalSeries = SequenceDataSeries(4000) barSeries = BarDataSeries(4000) basicbars.sort(key=lambda bar: bar.getDateTime(), reverse=False) for bar in basicbars: DateTimes.append(bar.getDateTime()) OpenSeries.appendWithDateTime(bar.getDateTime(), bar.getOpen()) HighSeries.appendWithDateTime(bar.getDateTime(), bar.getHigh()) LowSeries.appendWithDateTime(bar.getDateTime(), bar.getLow()) CloseSeries.appendWithDateTime(bar.getDateTime(), bar.getClose()) VolumeSeries.appendWithDateTime(bar.getDateTime(), bar.getVolume()) TypicalSeries.appendWithDateTime(bar.getDateTime(), (bar.getClose()+bar.getHigh()+bar.getLow())/3.0) barSeries.appendWithDateTime(bar.getDateTime(), bar) self.__DateTimes[key+"_adjusted"] = DateTimes self.__OpenDataSeries[key+"_adjusted"] = OpenSeries self.__HighDataSeries[key+"_adjusted"] = HighSeries self.__LowDataSeries[key+"_adjusted"] = LowSeries self.__CloseDataSeries[key+"_adjusted"] = CloseSeries self.__VolumeDataSeries[key+"_adjusted"] = VolumeSeries self.__TypicalDataSeries[key+"_adjusted"] = TypicalSeries self.__barSeries[key+"_adjusted"] = barSeries