def __init__(self, settings):
DailyTrigger.__init__(self, settings)
# this is a hack until we implement subscribing to multiple streams of data
self.uptrendcheck = dict()
# if True, we are filtering on uptrending SPY, if false, downtrending SPY
# we are using the PREVIOUS bar data, hence the use of HistoricMetric.
# we do not now if TODAY will close above/below the ma before we enter our
# day trades. An alternative would have been to use the open
ticker = settings.get("TrendFilterDailyTrigger", "ticker")
self.uptrend = settings.getboolean("TrendFilterDailyTrigger", "uptrend")
period = settings.getint("TrendFilterDailyTrigger", "period")
close = AdjustedClose()
lastclose = HistoricMetric(close, 1)
ma = SimpleMovingAverage(metric=close, period=period)
lastma = HistoricMetric(ma, 1)
fromdt = datetime(1900, 1, 1)
todt = datetime.now()
datastore = datastorefactory.get_datastore()
for dd in datastore.getDailyData(ticker, fromdt, todt):
close.handle(dd)
lastclose.handle(dd)
ma.handle(dd)
lastma.handle(dd)
if lastma.ready() and lastclose.ready():
if lastclose.value() > lastma.value():
self.uptrendcheck[dd.date] = True
if lastclose.value() < lastma.value():
self.uptrendcheck[dd.date] = False
class MovingAverageExitManager(ExitManager):
""" Exit on a moving average as a trailing stop
"""
def __init__(self, settings):
ExitManager.__init__(self)
self.period = settings.getint("MovingAverageExitManager", "period")
self.close = AdjustedClose()
self.ma = SimpleMovingAverage(metric=self.close, period=self.period)
def handle(self, perioddata):
ExitManager.handle(self, perioddata)
self.close.handle(perioddata)
self.ma.handle(perioddata)
def checkTrade(self, trade):
if trade is not None and self.ma.ready() and trade.exit is None \
and trade.entryPrice > trade.stop \
and self.perioddata.adjustedClose >= self.ma.value():
trade.exit = self.perioddata.date
trade.exitPrice = self.perioddata.adjustedClose
if trade is not None and self.ma.ready() and trade.exit is None \
and trade.entryPrice < trade.stop \
and self.perioddata.adjustedClose <= self.ma.value():
trade.exit = self.perioddata.date
trade.exitPrice = self.perioddata.adjustedClose
return trade
def recommendedPreload(self):
return self.period + 1
class RSIExitManager(ExitManager):
""" Exit on a target RSI value.
Handles long and short
"""
def __init__(self, settings):
ExitManager.__init__(self)
self.period = settings.getint("RSIExitManager", "period")
self.longExit = settings.getfloat("RSIExitManager", "longExit")
self.shortExit = settings.getfloat("RSIExitManager", "shortExit")
self.close = AdjustedClose()
self.rsi = RSI(metric=self.close, period=self.period)
def handle(self, perioddata):
ExitManager.handle(self, perioddata)
self.close.handle(perioddata)
self.rsi.handle(perioddata)
def checkTrade(self, trade):
if trade is not None and self.rsi.ready() and trade.is_open() \
and ((trade.is_long() and self.rsi.value() >= self.longExit) or
(trade.is_short() and self.rsi.value() <= self.shortExit)):
trade.close(self.perioddata.date, self.perioddata.adjustedClose)
return trade
def recommendedPreload(self):
return self.period + 3
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):
ExitManager.__init__(self)
self.period = settings.getint("RSIExitManager", "period")
self.longExit = settings.getfloat("RSIExitManager", "longExit")
self.shortExit = settings.getfloat("RSIExitManager", "shortExit")
self.close = AdjustedClose()
self.rsi = RSI(metric=self.close, period=self.period)
class MyTrendCheck(Check):
def __init__(self):
Check.__init__(self)
# adjusted close accounts for splits and dividends
self.close = AdjustedClose()
self.ma = SimpleMovingAverage(metric=self.close, period=200)
def handle(self, periodData):
self.close.handle(periodData)
self.ma.handle(periodData)
def ready(self):
return self.close.ready() and self.ma.ready()
def check(self):
if not self.ready():
return False
return self.close.value() > self.ma.value()
def __init__(self, settings=None, name=None):
self.name = name
ExitManager.__init__(self, settings)
bb_period = self._getintsetting("BollingerBreakoutExitManager", "bbPeriod")
bb_stdevs = self._getfloatsetting("BollingerBreakoutExitManager", "bbStdevs")
self.close = AdjustedClose()
self.bb = BollingerBands(metric=self.close, period=bb_period, stdev=bb_stdevs)
self._addMetrics(self.close, self.bb)
class MyTrendCheck(Check):
def __init__(self):
Check.__init__(self)
# adjusted close accounts for splits and dividends
self.close = AdjustedClose()
self.ma = SimpleMovingAverage(metric=self.close, period=200)
def handle(self, periodData):
self.close.handle(periodData)
self.ma.handle(periodData)
def ready(self):
return self.close.ready() and self.ma.ready()
def check(self):
if not self.ready():
return False
return self.close.value() > self.ma.value()
class BollingerBreakoutExitManager(ExitManager):
def __init__(self, settings=None, name=None):
self.name = name
ExitManager.__init__(self, settings)
bb_period = self._getintsetting("BollingerBreakoutExitManager", "bbPeriod")
bb_stdevs = self._getfloatsetting("BollingerBreakoutExitManager", "bbStdevs")
self.close = AdjustedClose()
self.bb = BollingerBands(metric=self.close, period=bb_period, stdev=bb_stdevs)
self._addMetrics(self.close, self.bb)
def checkTrade(self, trade):
if trade is not None and trade.is_open():
if trade.is_long():
if self.close.value() < self.bb.lowerBand():
trade.close(self.perioddata.date, self.perioddata.adjustedClose)
else:
if self.close.value() > self.bb.upperBand():
trade.close(self.perioddata.date, self.perioddata.adjustedClose)
return trade
class MACrossoverEntryManager(EntryManager):
""" Enter on cross higher of the fast ma over the slow ma """
def __init__(self, settings, name=None):
EntryManager.__init__(self, settings, name=name)
fastma = settings.getint("MACrossoverEntryManager", "fastma")
slowma = settings.getint("MACrossoverEntryManager", "slowma")
# AdjustedClose is adjusted for splits and dividends
self.close = AdjustedClose()
self.fastma = SimpleMovingAverage(metric=self.close, period=fastma)
self.slowma = SimpleMovingAverage(metric=self.close, period=slowma)
# add the metrics to the entry manager, this will cause them
# to automatically handle the stream of bar data
self._addMetric(self.close)
self._addMetric(self.fastma)
self._addMetric(self.slowma)
def checkTrade(self, trade):
if trade is not None:
# we don't scale in additional size, already in a trade
return trade
if self.fastma.ready() and self.slowma.ready() \
and self.fastma.value() > self.slowma.value() \
and self.close.value() > 0:
# new trade
entry = self.close.value()
# no stops for this simple strategy
stop = 0.0
# note, self.periodData is the last bar seen, this is provided from
# the base class EntryManager
trade = Trade(self.periodData.stock, self.periodData.date, entry, stop)
return trade
return None
def __init__(self, settings, name=None):
EntryManager.__init__(self, settings, name=name)
fastma = settings.getint("MACrossoverEntryManager", "fastma")
slowma = settings.getint("MACrossoverEntryManager", "slowma")
# AdjustedClose is adjusted for splits and dividends
self.close = AdjustedClose()
self.fastma = SimpleMovingAverage(metric=self.close, period=fastma)
self.slowma = SimpleMovingAverage(metric=self.close, period=slowma)
# add the metrics to the entry manager, this will cause them
# to automatically handle the stream of bar data
self._addMetric(self.close)
self._addMetric(self.fastma)
self._addMetric(self.slowma)
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
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 __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=None, name=None):
NoScaleInEntryManager.__init__(self, settings, name)
self.min_price = self._getfloatsetting("BollingerBreakoutEntryManager", "minPrice")
self.min_vol = self._getintsetting("BollingerBreakoutEntryManager", "minVolume")
bb_period = self._getintsetting("BollingerBreakoutEntryManager", "bbPeriod")
bb_stdevs = self._getfloatsetting("BollingerBreakoutEntryManager", "bbStdevs")
self.do_long = self._getboolsetting("BollingerBreakoutEntryManager", "doLong")
self.do_short = self._getboolsetting("BollingerBreakoutEntryManager", "doShort")
sma_period = self._getintsetting("BollingerBreakoutEntryManager", "smaPeriod")
if sma_period is not None:
self.sma = SimpleMovingAverage(period=sma_period)
else:
self.sma = None
self.raw_close = Close()
self.close = AdjustedClose()
self.vol = AverageVolume()
self.bb = BollingerBands(metric=self.close, period=bb_period, stdev=bb_stdevs)
self._addMetrics(self.sma, self.raw_close, self.close, self.vol, self.bb)
class BollingerBreakoutEntryManager(NoScaleInEntryManager):
def __init__(self, settings=None, name=None):
NoScaleInEntryManager.__init__(self, settings, name)
self.min_price = self._getfloatsetting("BollingerBreakoutEntryManager", "minPrice")
self.min_vol = self._getintsetting("BollingerBreakoutEntryManager", "minVolume")
bb_period = self._getintsetting("BollingerBreakoutEntryManager", "bbPeriod")
bb_stdevs = self._getfloatsetting("BollingerBreakoutEntryManager", "bbStdevs")
self.do_long = self._getboolsetting("BollingerBreakoutEntryManager", "doLong")
self.do_short = self._getboolsetting("BollingerBreakoutEntryManager", "doShort")
sma_period = self._getintsetting("BollingerBreakoutEntryManager", "smaPeriod")
if sma_period is not None:
self.sma = SimpleMovingAverage(period=sma_period)
else:
self.sma = None
self.raw_close = Close()
self.close = AdjustedClose()
self.vol = AverageVolume()
self.bb = BollingerBands(metric=self.close, period=bb_period, stdev=bb_stdevs)
self._addMetrics(self.sma, self.raw_close, self.close, self.vol, self.bb)
def _checkTradeNoScale(self):
trade = None
if self.raw_close.value() >= self.min_price and self.vol.value() >= self.min_vol \
and self.close.value() > self.bb.upperBand() and self.do_long \
and (self.sma is None or self.close.value() > self.sma.value()):
entry_price = self.close.value()
stop = 0
trade = Trade(stock=self.periodData.stock, entry=self.periodData.date, entryPrice=entry_price,
stop=stop)
if self.raw_close.value() >= self.min_price and self.vol.value() >= self.min_vol \
and self.close.value() < self.bb.upperBand() and self.do_short \
and (self.sma is None or self.close.value() < self.sma.value()):
entry_price = self.close.value()
stop = entry_price * 10
trade = Trade(stock=self.periodData.stock, entry=self.periodData.date, entryPrice=entry_price,
stop=stop)
return trade
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 __init__(self, settings):
ExitManager.__init__(self)
self.period = settings.getint("MovingAverageExitManager", "period")
self.close = AdjustedClose()
self.ma = SimpleMovingAverage(metric=self.close, period=self.period)
def generate_random_perioddata(dt):
a = random()*50+50
b = random()*50+50
c = random()*50+50
d = random()*50+50
retval = PeriodData(date=dt,period=Period.DAILY, stock="AAPL", open=a,high=max((a,b,c,d)),low=min(a,b,c,d),close=d,volume=100000,adjustedClose=d)
return retval
def generate_random_series():
retval = list()
dt = datetime(year=2015,month=1,day=1)
for i in range(1000):
dt = dt + timedelta(days=1)
retval.append(generate_random_perioddata(dt))
return retval
# Here begins the example code
# Track the adjusted close and 20 period simple moving average
close = AdjustedClose()
sma = SimpleMovingAverage(metric=close, period=20)
print "Date,SMA"
for periodData in generate_random_series():
close.handle(periodData)
sma.handle(periodData)
if sma.ready() and close.ready():
print "%s,%f" % (periodData.date, sma.value())
def __init__(self):
Check.__init__(self)
# adjusted close accounts for splits and dividends
self.close = AdjustedClose()
self.ma = SimpleMovingAverage(metric=self.close, period=200)
def __init__(self):
Check.__init__(self)
# adjusted close accounts for splits and dividends
self.close = AdjustedClose()
self.ma = SimpleMovingAverage(metric=self.close, period=200)