class MomoAfternoonBreakoutDailyTrigger(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 = Close()
if self.dailysmatrendfilter is not None:
self.ma = SimpleMovingAverage(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.close.value() >= 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:
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)
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
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
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 __init__(self, settings, name=None):
EntryManager.__init__(self, settings, name)
self.minhour = settings.getint("Strategy", "minhour")
self.maxhour = settings.getint("Strategy", "maxhour")
self.target = self._getintsetting("Strategy", "target")
self.minmove = settings.getfloat("Strategy", "minmove")
self.maxprice = self._getfloatsetting("Strategy", "maxprice")
self.maperiod = self._getintsetting("Strategy", "ma")
self.stopPercentToLow = self._getfloatsetting("Strategy", "stopPercentToLow")
self.hod = None
self.open = None
self.hoddate = None
self.low = None
self.close = Close()
self.ma = ExponentialMovingAverage(metric=self.close, period=self.maperiod)
self.mademove = False
self.lastpd = None
class MomoPullbackEntryManager(EntryManager):
"""
Enter at a moving average after a minimum move. Stop is set at a percentage
between the moving average and the low of day.
"""
def __init__(self, settings, name=None):
EntryManager.__init__(self, settings, name)
self.minhour = settings.getint("Strategy", "minhour")
self.maxhour = settings.getint("Strategy", "maxhour")
self.target = self._getintsetting("Strategy", "target")
self.minmove = settings.getfloat("Strategy", "minmove")
self.maxprice = self._getfloatsetting("Strategy", "maxprice")
self.maperiod = self._getintsetting("Strategy", "ma")
self.stopPercentToLow = self._getfloatsetting("Strategy", "stopPercentToLow")
self.hod = None
self.open = None
self.hoddate = None
self.low = None
self.close = Close()
self.ma = ExponentialMovingAverage(metric=self.close, period=self.maperiod)
self.mademove = False
self.lastpd = None
def handle(self, perioddata):
self.close.handle(perioddata)
self.ma.handle(perioddata)
if self.lastpd is not None and self.lastpd.date.day != perioddata.date.day:
self.low = None
self.hod = None
self.hoddate = None
self.mademove = False
if self.open is None:
self.open = perioddata.open
if self.lastpd is not None and (self.low is None or self.lastpd.low < self.low):
self.low = self.lastpd.low
if self.periodData is not None:
# quick, use previous value to update hod
if self.hod is None or self.periodData.high >= self.hod:
self.hod = self.periodData.high
self.hoddate = self.periodData.date
if not self.mademove and self.low is not None and self.hod is not None and self.open is not None and (
self.hod - self.open) / self.open >= self.minmove:
logger.debug("saw minimum desired move in MomoPullbackManager, waiting for pullback")
self.mademove = True
EntryManager.handle(self, perioddata)
self.lastpd = perioddata
def checkTrade(self, trade):
if trade is not None:
# no scale ins
return trade
if self.mademove \
and self.periodData.date.hour >= self.minhour \
and (self.periodData.date.hour < self.maxhour
or (self.periodData.date.hour == self.maxhour and self.periodData.date.minute == 0)) \
and self.periodData.low <= self.ma.value():
# we have an entry
entry = min(self.periodData.open, self.ma.value())
if self.maxprice is None or entry <= self.maxprice:
stop = self.low - 0.01
if self.stopPercentToLow is not None:
stop = entry - (self.stopPercentToLow * (entry - self.low))
# at least 10c
if stop >= entry - 0.1:
stop = entry - 0.1
trade = Trade(self.periodData.stock, self.periodData.date, entry, stop)
if self.target is not None:
target = entry + ((entry - stop) * self.target)
trade.target = target
if self.periodData.low < stop:
trade.exit = self.periodData.date
trade.exitPrice = stop
return trade
return 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): stocks = self._getTickers(fromdt, datastore) for stock in stocks: close = Close() sma = None if self.dailysmatrendfilter != None: sma = SimpleMovingAverage(close, period=self.dailysmatrendfilter) # padded extra to make sure 50 day sma has enough trading days to work with before our window dailydata = datastore.getDailyData(stock, fromdt - timedelta(days=100), todt) prevpd = None for pd in dailydata: if prevpd != None and pd.date >= fromdt: trade = None if pd.open == prevpd.close or prevpd.close == 0: gapsize=0 else: gapsize = (prevpd.close - pd.open)/prevpd.close if gapsize >= self.mingap and (sma == None or (sma.ready() and pd.open < sma.value())) and pd.open >= self.minprice: intrafromdt = pd.date intratodt = pd.date + timedelta(hours=24) intradaydata = iter(datastore.getIntradayData(stock, 300, intrafromdt, intratodt)) try: intradaypd = intradaydata.next() entry = None lod = intradaypd.low prevpd = intradaypd high = High() highesthigh = Highest(metric=high, period=self.donchianstop) high.handle(intradaypd) highesthigh.handle(intradaypd) for intradaypd in intradaydata: if trade == None \ and highesthigh.ready() \ and intradaypd.date.hour >= self.minhour \ and (intradaypd.date.hour < self.maxhour \ or (intradaypd.date.hour == self.maxhour and intradaypd.date.minute==0)) \ and intradaypd.low < lod: entry = lod - 0.01 trade = Trade(stock, intradaypd.date, min(entry, intradaypd.open), highesthigh.value()+0.01) if self.target != None: trade.target = trade.entryPrice + (self.target * (trade.entryPrice-trade.stop)) if trade != None and trade.exit == None: if intradaypd.high >= trade.trailingstop: trade.exit = intradaypd.date trade.exitPrice = max(trade.stop, intradaypd.open) if trade.exit == None and trade.target != None and intradaypd.low <= trade.target: trade.exit = intradaypd.date trade.exitPrice = min(intradaypd.open, trade.target) if intradaypd.low < lod: lod = intradaypd.low high.handle(intradaypd) highesthigh.handle(intradaypd) except StopIteration: pass # eod, close it if it is still open if trade != None and trade.exit == None: trade.exit = intradaypd.date trade.exitPrice = intradaypd.close if trade != None: self.tradeManager.addTrade(trade) # now we can update the indicators - since we finished trading the day close.handle(pd) if sma != None: sma.handle(pd) prevpd = pd return self.tradeManager.getStats()
def findsetups(self, fromdt, todt): numstopouts = 0 stocks = self._getTickers(fromdt, datastore) for stock in stocks: # padded extra to make sure 200 day sma has enough trading days to work with before our window dailydata = datastore.getDailyData(stock, fromdt - timedelta(days=(self.slowma*2)), todt) close = Close() fastma = SimpleMovingAverage(period=self.fastma) slowma = SimpleMovingAverage(period=self.slowma) lastfastma = HistoricMetric(metric=fastma, period=1) lastslowma = HistoricMetric(metric=slowma, period=1) atr = ATR(period=14) lastdd = None trade = None for pd in dailydata: close.handle(pd) fastma.handle(pd) slowma.handle(pd) lastfastma.handle(pd) lastslowma.handle(pd) atr.handle(pd) # check for long stopout if trade != None and pd.low < trade.trailingstop: trade.exit = pd.date trade.exitPrice = min(pd.open, trade.trailingstop) self.tradeManager.addTrade(trade) numstopouts = numstopouts + 1 trade = None # check for long exit if trade != None and fastma.value() < slowma.value(): trade.exit = pd.date trade.exitPrice = pd.close self.tradeManager.addTrade(trade) trade = None if fastma.ready() and slowma.ready() and lastfastma.ready() and lastslowma.ready() and atr.ready(): pass # check for new long if trade == None and fastma.ready() and slowma.ready() \ and lastfastma.ready() and lastslowma.ready() \ and (self.atrStop == None or atr.ready()) \ and pd.date >= fromdt \ and fastma.value() > slowma.value() \ and lastfastma.value() <= lastslowma.value() \ and pd.close >= self.minprice: stop = 0 if self.atrStop != None: stop = max(0,pd.close - (float(self.atrStop) * atr.value())) if self.percentStop != None: stop = max(0, pd.close * (1.0 - self.percentStop)) trade = Trade(stock=stock, entry=pd.date, entryPrice=pd.close, stop=stop) if trade != None and trade.entry == None: trade.exit = lastdd.date trade.exitPrice = lastdd.close self.tradeManager.addTrade(trade) trade = None print "num stopouts was %d" % numstopouts return self.tradeManager.getStats()