class GapUpEntryManager:
def __init__(self, settings):
self.minPrice = settings.getfloat("GapAndGoSwingEntry", "minPrice")
self.minAvgVol = settings.getint("GapAndGoSwingEntry", "minAvgVol")
self.minPercent = settings.getfloat("GapAndGoSwingEntry", "minPercent")
targetstr = settings.get("GapAndGoSwingEntry", "target")
if targetstr == "None":
self.target = None
else:
self.target = float(targetstr)
self.volume = Volume()
self.avgvol = SimpleMovingAverage(metric=self.volume, period=21)
self.opn = AdjustedOpen()
self.close = AdjustedClose()
self.lastClose = HistoricMetric(metric=self.close, period=1)
self.high = AdjustedHigh()
self.lastHigh = HistoricMetric(metric=self.high, period=1)
self.low = AdjustedLow()
self.inBottomRange=0.1
self.inTopRange=None
def handle(self, perioddata):
self.close.handle(perioddata)
self.lastClose.handle(perioddata)
self.high.handle(perioddata)
self.lastHigh.handle(perioddata)
self.opn.handle(perioddata)
self.volume.handle(perioddata)
self.avgvol.handle(perioddata)
self.low.handle(perioddata)
self.lastdd = perioddata
def checkTrade(self):
if self.close.ready() and self.lastClose.ready() \
and self.opn.ready() and self.volume.ready() \
and self.avgvol.ready():
if self.lastdd.close >= self.minPrice and self.avgvol.value() >= self.minAvgVol \
and self.lastClose.value() > 0 and self.opn.value() > 0 \
and ((self.opn.value()-self.lastClose.value())/self.lastClose.value()) >= self.minPercent \
and self.low.value() >= self.lastHigh.value() \
and (self.inBottomRange == None or ((self.lastdd.adjustedHigh != self.lastdd.adjustedLow) and (self.close.value()-self.lastdd.adjustedLow)/(self.lastdd.adjustedHigh-self.lastdd.adjustedLow)) <= self.inBottomRange) \
and (self.inTopRange == None or ((self.lastdd.adjustedHigh != self.lastdd.adjustedLow) and (self.close.value()-self.lastdd.adjustedLow)/(self.lastdd.adjustedHigh-self.lastdd.adjustedLow)) >= self.inTopRange):
stop = max(0.0, self.low.value() - 0.01)
# stop = max(0.0, self.lastHigh.value())
trade = Trade(self.lastdd.stock, self.lastdd.date, self.close.value(), stop)
if self.target != None:
target = self.close.value() + ((self.close.value()-stop)*self.target)
trade.target = target
return trade
return None
def recommendedPreload(self):
return 22
class MomoPullbackDailyTrigger(DailyTrigger):
def __init__(self, settings):
DailyTrigger.__init__(self, settings)
self.minprice = settings.getfloat("Strategy", "minprice")
self.minvolume = settings.getint("Strategy", "minvolume")
self.minmove = settings.getfloat("Strategy", "minmove")
smatrend = settings.get("Strategy", "dailysmatrendfilter")
if smatrend == "None":
self.dailysmatrendfilter = None
else:
self.dailysmatrendfilter = int(smatrend)
self.volume = Volume()
self.avgvol = SimpleMovingAverage(self.volume, 21)
self.close = AdjustedClose()
if self.dailysmatrendfilter is not None:
self.ma = SimpleMovingAverage(metric=self.close, period=self.dailysmatrendfilter)
else:
self.ma = None
def ready(self):
return (self.ma is None or self.ma.ready()) and self.avgvol.ready() and self.close.ready()
def check(self):
if self.ready() and self.lastpd is not None:
# todo would be a lot faster if I could implement a peek at today to check the move is big enough
if self.lastpd.open >= self.minprice \
and (self.ma is None or self.close.value() > self.ma.value()) \
and self.avgvol.value() >= self.minvolume \
and ((self.peekpd.high - self.peekpd.open) / self.peekpd.open) >= self.minmove:
logger.debug("Saw minimum move in MomoPullbackDailyTrigger, indicating we have a good day")
return True
return False
def handle(self, perioddata):
if self.ma is not None:
self.ma.handle(perioddata)
self.volume.handle(perioddata)
self.avgvol.handle(perioddata)
self.close.handle(perioddata)
self.lastpd = perioddata
def recommendedPreload(self):
mapreload = 0
if self.ma is not None:
mapreload = self.ma.recommendedPreload()
return max(mapreload, self.avgvol.recommendedPreload())
def __init__(self, settings, name=None):
NoScaleInEntryManager.__init__(self, settings, name)
self.minPrice = settings.getfloat("JBMarwoodSupernovaShortEntry", "minPrice")
self.maxPrice = settings.getfloat("JBMarwoodSupernovaShortEntry", "maxPrice")
self.minVol = settings.getint("JBMarwoodSupernovaShortEntry", "minVol")
self.minPctChange = settings.getfloat("JBMarwoodSupernovaShortEntry", "minPctChange")
self.numdays = settings.getint("JBMarwoodSupernovaShortEntry", "numBars")
self.onOpen = settings.getboolean("JBMarwoodSupernovaShortEntry", "enterNextOpen")
self.onDownClose = settings.getboolean("JBMarwoodSupernovaShortEntry", "enterNextDayDownClose")
targetstr = settings.get("JBMarwoodSupernovaShortEntry", "target")
if targetstr == "None":
self.target = None
else:
self.target = float(targetstr)
self.stopPercent = settings.getfloat("JBMarwoodSupernovaShortEntry", "stopPercent")
self.setupYesterday = True
self.rawclose = Close()
self.close = AdjustedClose()
self.oldClose = HistoricMetric(self.close, period=self.numdays)
self.change = Subtract(self.close, self.oldClose)
self.pctChange = Divide(self.change, self.oldClose)
self.volume = Volume()
self._addMetric(self.rawclose)
self._addMetric(self.close)
self._addMetric(self.oldClose)
self._addMetric(self.change)
self._addMetric(self.pctChange)
self._addMetric(self.volume)
def __init__(self, settings):
self.minPrice = settings.getfloat("GapAndGoSwingEntry", "minPrice")
self.minAvgVol = settings.getint("GapAndGoSwingEntry", "minAvgVol")
self.minPercent = settings.getfloat("GapAndGoSwingEntry", "minPercent")
targetstr = settings.get("GapAndGoSwingEntry", "target")
if targetstr == "None":
self.target = None
else:
self.target = float(targetstr)
self.volume = Volume()
self.avgvol = SimpleMovingAverage(metric=self.volume, period=21)
self.opn = AdjustedOpen()
self.close = AdjustedClose()
self.lastClose = HistoricMetric(metric=self.close, period=1)
self.high = AdjustedHigh()
self.lastHigh = HistoricMetric(metric=self.high, period=1)
self.low = AdjustedLow()
self.inBottomRange=0.1
self.inTopRange=None
def __init__(self, settings):
DailyTrigger.__init__(self, settings)
self.minprice = settings.getfloat("Strategy", "minprice")
self.minvolume = settings.getint("Strategy", "minvolume")
self.minmove = settings.getfloat("Strategy", "minmove")
smatrend = settings.get("Strategy", "dailysmatrendfilter")
if smatrend == "None":
self.dailysmatrendfilter = None
else:
self.dailysmatrendfilter = int(smatrend)
self.volume = Volume()
self.avgvol = SimpleMovingAverage(self.volume, 21)
self.close = Close()
if self.dailysmatrendfilter is not None:
self.ma = SimpleMovingAverage(period=self.dailysmatrendfilter)
else:
self.ma = None
class JBMarwoodSupernovaShortEntryManager(NoScaleInEntryManager):
def __init__(self, settings, name=None):
NoScaleInEntryManager.__init__(self, settings, name)
self.minPrice = settings.getfloat("JBMarwoodSupernovaShortEntry", "minPrice")
self.maxPrice = settings.getfloat("JBMarwoodSupernovaShortEntry", "maxPrice")
self.minVol = settings.getint("JBMarwoodSupernovaShortEntry", "minVol")
self.minPctChange = settings.getfloat("JBMarwoodSupernovaShortEntry", "minPctChange")
self.numdays = settings.getint("JBMarwoodSupernovaShortEntry", "numBars")
self.onOpen = settings.getboolean("JBMarwoodSupernovaShortEntry", "enterNextOpen")
self.onDownClose = settings.getboolean("JBMarwoodSupernovaShortEntry", "enterNextDayDownClose")
targetstr = settings.get("JBMarwoodSupernovaShortEntry", "target")
if targetstr == "None":
self.target = None
else:
self.target = float(targetstr)
self.stopPercent = settings.getfloat("JBMarwoodSupernovaShortEntry", "stopPercent")
self.setupYesterday = True
self.rawclose = Close()
self.close = AdjustedClose()
self.oldClose = HistoricMetric(self.close, period=self.numdays)
self.change = Subtract(self.close, self.oldClose)
self.pctChange = Divide(self.change, self.oldClose)
self.volume = Volume()
self._addMetric(self.rawclose)
self._addMetric(self.close)
self._addMetric(self.oldClose)
self._addMetric(self.change)
self._addMetric(self.pctChange)
self._addMetric(self.volume)
def _checkTradeNoScale(self):
trade = None
if self.setupYesterday:
if self.onOpen:
entry = self.periodData.adjustedOpen
stop = entry * (1 + self.stopPercent)
if entry != stop:
trade = Trade(self.periodData.stock, self.periodData.date, entry, stop)
if self.target != None:
target = self.close.value() * (1.0 - self.target)
trade.target = target
elif self.onDownClose and self.periodData.adjustedClose < self.periodData.adjustedOpen:
stop = self.periodData.adjustedHigh + 0.01
# stop = self.close.value()*(1+self.stopPercent)
if stop != self.close.value():
trade = Trade(self.periodData.stock, self.periodData.date, self.close.value(), stop)
if self.target != None:
target = self.close.value() * (1.0 - self.target)
trade.target = target
if (
self.pctChange.ready()
and self.rawclose.value() >= self.minPrice
and self.rawclose.value() <= self.maxPrice
and self.volume.value() >= self.minVol
and self.pctChange.value() >= self.minPctChange
):
if not self.onDownClose and not self.onOpen:
# enter immediately
stop = self.close.value() * (1 + self.stopPercent)
if stop != self.close.value():
trade = Trade(self.periodData.stock, self.periodData.date, self.close.value(), stop)
if self.target != None:
target = self.close.value() * (1.0 - self.target)
trade.target = target
self.setupYesterday = True
else:
self.setupYesterday = False
if trade is not None and (trade.entryPrice == 0 or trade.entryPrice == trade.stop):
return None
return trade
def findsetups(self, fromdt, todt):
datastore = datastorefactory.get_datastore()
# stocks = datastore.filterStocksByAvgVolume(fromdt, minvolume)
stocks = self._getTickers(fromdt, datastore)
for stock in stocks:
dailydata = list()
volume = Volume()
avgvolume = SimpleMovingAverage(metric=volume, period=21)
dailyatr = ATR(20)
atrfromdt = fromdt - timedelta(days=max(self.duration, 40)) # 40 to give the atr time to normalize
dailydataiter = iter(datastore.getDailyData(stock, atrfromdt, todt))
dailydataday = None
try:
while dailydataday == None or dailydataday.date < fromdt:
dailydataday = dailydataiter.next()
# have to fix it to a real object for the atr
dailyatr.handle(dailydataday)
dailydata.append(dailydataday)
except StopIteration:
pass
if len(dailydata) > self.duration:
dailydata = dailydata[len(dailydata) - self.duration :]
# ok, we find the highest high and lowest low first
high = 0
low = None
for ddhighfinder in dailydata:
if high < ddhighfinder.high:
high = ddhighfinder.high
if low == None or ddhighfinder.low < low:
low = ddhighfinder.low
# great, now we find how many lower highs are within the mush factor
atrmush = 0
if dailyatr.value() != None:
atrmush = dailyatr.value() * self.mushinessatr
taps = 0
shorttaps = 0
for ddtapfinder in dailydata:
delta = high - ddtapfinder.high
if delta <= atrmush or delta <= self.mushinessfixed:
taps = taps + 1
shortdelta = ddtapfinder.low - low
if shortdelta <= atrmush or delta <= self.mushinessfixed:
shorttaps = shorttaps + 1
# ok, now we can add the next dd - we go ahead and prep some things for the next loop pass
# since we are no longer using them now
for dailydataday in dailydataiter:
saveatr = dailyatr.value()
volume.handle(dailydataday)
avgvolume.handle(dailydataday)
dailyatr.handle(dailydataday)
dailydata.append(dailydataday)
dailydata = dailydata[1:]
trade = None
# as a hack, now we can check our peek ahead and see for free if we
# ever broke the high today. If not, we are done
if (
self.doLongs
and taps >= self.numtaps
and dailydataday.high > high
and high >= self.minprice
and (self.maxprice == None or high <= self.maxprice)
and avgvolume.ready()
and avgvolume.value() >= self.minavgvolume
and (
self.minAPR == None
or (dailyatr.ready() and dailyatr.value() / dailydataday.adjustedClose) >= self.minAPR
)
):
# ok, we need to scan the day
low = None
donchlow = None
if self.donchianstop != None:
low = Low()
donchlow = Lowest(low, self.donchianstop)
intrafromdt = dailydataday.date
intratodt = intrafromdt + timedelta(hours=24)
intradaydata = datastore.getIntradayData(stock, self.period, intrafromdt, intratodt)
if intradaydata != None and len(intradaydata) > 1:
intradaybar = intradaydata[0]
intralow = intradaybar.low
intrahigh = intradaybar.high
taps = 1
for i in range(1, len(intradaydata)):
intradaybar = intradaydata[i]
if trade == None and (
self.maxintradayrangeatr == None
or (saveatr != None and (intrahigh - intralow) < (saveatr * self.maxintradayrangeatr))
):
intralow = min(intralow, intradaybar.low)
if (
intradaybar.high <= intrahigh
and (intrahigh - intradaybar.high) <= self.mushinessfixed2m
):
taps = taps + 1
if intradaybar.high > intrahigh:
if (
taps >= self.taps2m
and intrahigh >= high
and (
self.maxhour == None
or intradaybar.date.hour < self.maxhour
or (intradaybar.date.hour == self.maxhour and intradaybar.date.minute == 0)
)
and (self.minhour == None or intradaybar.date.hour >= self.minhour)
):
# trade entry
if donchlow != None and donchlow.ready():
stop = donchlow.value() - 0.01
else:
stop = intralow - 0.01
entryPrice = min(intradaybar.open, intrahigh + 0.01)
if entryPrice > stop:
trade = Trade(
stock=stock,
entry=intradaybar.date,
entryPrice=min(intradaybar.open, intrahigh + 0.01),
stop=stop,
)
if self.target:
trade.target = trade.entryPrice + (
self.target * (trade.entryPrice - trade.stop)
)
else:
# need to recalculate taps off this new high as we had no signal yet
intrahigh = intradaybar.high
taps = 1
for j in range(0, i - 1):
if (intrahigh - intradaydata[j].high) < self.mushinessfixed2m:
taps = taps + 1
if trade and trade.exit == None:
if intradaybar.low < trade.trailingstop:
# taken out
trade.exit = intradaybar.date
trade.exitPrice = min(intradaybar.open, trade.trailingstop)
if trade.target != None and intradaybar.high > trade.target:
trade.exit = intradaybar.date
trade.exitPrice = max(intradaybar.open, trade.target)
if low != None:
low.handle(intradaybar)
if donchlow != None:
donchlow.handle(intradaybar)
if trade != None and trade.exit == None:
trade.exit = intradaybar.date
trade.exitPrice = intradaybar.close
if trade:
self.tradeManager.addTrade(trade)
trade = None
trade = None
# SHORTS
# as a hack, now we can check our peek ahead and see for free if we
# ever broke the low today. If not, we are done
if (
self.doShorts
and shorttaps >= self.numtaps
and dailydataday.low < low
and low >= self.minprice
and avgvolume.ready()
and avgvolume.value() >= self.minavgvolume
and (
self.minAPR == None
or (dailyatr.ready() and dailyatr.value() / dailydataday.adjustedClose) >= self.minAPR
)
):
# ok, we need to scan the day
high = None
donchhigh = None
if self.donchianstop != None:
high = High()
donchhigh = Highest(high, self.donchianstop)
intrafromdt = dailydataday.date
intratodt = intrafromdt + timedelta(hours=24)
intradaydata = datastore.getIntradayData(stock, 300, intrafromdt, intratodt)
if intradaydata != None and len(intradaydata) > 1:
intradaybar = intradaydata[0]
intralow = intradaybar.low
intrahigh = intradaybar.high
taps = 1
for i in range(1, len(intradaydata)):
intradaybar = intradaydata[i]
if trade == None and (
self.maxintradayrangeatr == None
or (saveatr != None and (intrahigh - intralow) < (saveatr * self.maxintradayrangeatr))
):
intrahigh = max(intrahigh, intradaybar.high)
if (
intradaybar.low >= intralow
and (intradaybar.low - intralow) <= self.mushinessfixed2m
):
taps = taps + 1
if intradaybar.low < intralow:
if (
taps >= self.taps2m
and intralow <= low
and (
self.maxhour == None
or intradaybar.date.hour < self.maxhour
or (intradaybar.date.hour == self.maxhour and intradaybar.date.minute == 0)
)
and (self.minhour == None or intradaybar.date.hour >= self.minhour)
):
# trade entry
if donchhigh != None and donchhigh.ready():
stop = donchhigh.value() + 0.01
else:
stop = intrahigh + 0.01
entryPrice = min(intradaybar.open, intralow - 0.01)
if entryPrice < stop:
trade = Trade(
stock=stock, entry=intradaybar.date, entryPrice=entryPrice, stop=stop
)
if self.target:
trade.target = trade.entryPrice - (
self.target * (trade.stop - trade.entryPrice)
)
else:
# need to recalculate taps off this new high as we had no signal yet
intralow = intradaybar.low
taps = 1
for j in range(0, i - 1):
if (intralow - intradaydata[j].low) < self.mushinessfixed2m:
taps = taps + 1
if trade and trade.exit == None:
if intradaybar.high >= trade.trailingstop:
# taken out
trade.exit = intradaybar.date
trade.exitPrice = max(intradaybar.open, trade.trailingstop)
if trade.target != None and intradaybar.low < trade.target:
trade.exit = intradaybar.date
trade.exitPrice = min(intradaybar.open, trade.target)
if high != None:
high.handle(intradaybar)
if donchhigh != None:
donchhigh.handle(intradaybar)
if trade != None and trade.exit == None:
trade.exit = intradaybar.date
trade.exitPrice = intradaybar.close
if trade:
self.tradeManager.addTrade(trade)
trade = None
trade = None
# redo daily setup for the next day, already loaded in above the intraday loop
# ok, we find the highest high first
high = 0
low = None
for ddhighfinder in dailydata:
if high < ddhighfinder.high:
high = ddhighfinder.high
if low == None or ddhighfinder.low < low:
low = ddhighfinder.low
# great, now we find how many lower highs are within the mush factor
atrmush = 0
if dailyatr.value() != None:
atrmush = dailyatr.value() * self.mushinessatr
taps = 0
shorttaps = 0
for ddtapfinder in dailydata:
delta = high - ddtapfinder.high
shortdelta = ddtapfinder.low - low
if delta <= atrmush or delta <= self.mushinessfixed:
taps = taps + 1
if shortdelta <= atrmush or shortdelta <= self.mushinessfixed:
shorttaps = shorttaps + 1
return self.tradeManager.getStats()