def __init__(self, dataSeries, period, numStdDev, maxLen=dataseries.DEFAULT_MAX_LEN):
self.__sma = ma.SMA(dataSeries, period, maxLen=maxLen)
self.__stdDev = stats.StdDev(dataSeries, period, maxLen=maxLen)
self.__upperBand = dataseries.SequenceDataSeries(maxLen)
self.__lowerBand = dataseries.SequenceDataSeries(maxLen)
self.__numStdDev = numStdDev
# It is important to subscribe after sma and stddev since we'll use those values.
dataSeries.getNewValueEvent().subscribe(self.__onNewValue)
def testStdDev_1(self):
values = [1, 1, 2, 3, 5]
seqDS = dataseries.SequenceDataSeries()
stdDev = stats.StdDev(seqDS, 1)
for value in values:
seqDS.append(value)
for i in stdDev:
self.assertEqual(i, 0)
def testStdDev_Bounded(self):
values = [1, 1, 2, 3, 5]
seqDS = dataseries.SequenceDataSeries()
stdDev = stats.StdDev(seqDS, 2, maxLen=2)
for value in values:
seqDS.append(value)
self.assertEqual(stdDev[0], numpy.array([2, 3]).std())
self.assertEqual(stdDev[1], numpy.array([3, 5]).std())
def run_stddev():
global feed
stddev = stats.StdDev(feed[instrument].getCloseDataSeries(), 50)
print "Processing all bars"
feed.loadAll()
print "Processing all StdDev"
for v in stddev:
pass
def testStdDev(self):
values = [1, 1, 2, 3, 5]
seqDS = dataseries.SequenceDataSeries()
stdDev = stats.StdDev(seqDS, 2)
for value in values:
seqDS.append(value)
self.assertEqual(stdDev[0], None)
self.assertEqual(stdDev[1], numpy.array([1, 1]).std())
self.assertEqual(stdDev[2], numpy.array([1, 2]).std())
self.assertEqual(stdDev[3], numpy.array([2, 3]).std())
self.assertEqual(stdDev[4], numpy.array([3, 5]).std())
def __init__(self, feed):
stdDevPeriod = 90
smaPeriod = 20
self.__returns = {}
self.__stdDev = {}
self.__ma = {}
for instrument in feed.getRegisteredInstruments():
priceDS = feed[instrument].getAdjCloseDataSeries()
# Returns over the adjusted close values.
self.__returns[instrument] = roc.RateOfChange(priceDS, 1)
# StdDev over those returns.
self.__stdDev[instrument] = stats.StdDev(self.__returns[instrument], stdDevPeriod)
# MA over the adjusted close values.
self.__ma[instrument] = ma.SMA(priceDS, smaPeriod)
def __init__(self, feed, instruments):
super(BuyOnGap, self).__init__()
stdDevPeriod = 90
smaPeriod = 20
self.__returns = {}
self.__stdDev = {}
self.__ma = {}
for instrument in instruments:
priceDS = feed.getDataSeries(instrument).getAdjCloseDataSeries()
# Returns over the adjusted close values.
self.__returns[instrument] = roc.RateOfChange(priceDS, 1)
# StdDev over those returns.
self.__stdDev[instrument] = stats.StdDev(
self.__returns[instrument], stdDevPeriod)
# MA over the adjusted close values.
self.__ma[instrument] = ma.SMA(priceDS, smaPeriod)
def __init__(self, instrument, feed, brk):
strategy.BaseStrategy.__init__(self, feed, brk)
self.__verbosityLevel = 1
self.__instrument = instrument
self.__orderSize = 0.2
self.__targetPricePct = 0.015
self.__commitPricePct = self.__targetPricePct / 2
self.__stopLossPct = -0.02
# Time to wait for BUY order to get filled.
self.__maxWaitEntry = datetime.timedelta(minutes=3)
# Maximum holding period.
self.__maxHoldPeriod = datetime.timedelta(hours=1)
volatilityPeriod = 5 # How many returns to use to calculate volatility.
self.returnsVolatility = stats.StdDev(
roc.RateOfChange(feed[self.__instrument].getCloseDataSeries(), 1),
volatilityPeriod)
self.__switchNoPos()
