def __init__(self):
super().__init__()
self.lag = Laguerre(self.datas[0],
short_gamma = self.params.short_gamma,
long_gamma=self.params.long_gamma,
pctile=self.params.pctile,
wrnpctile=self.params.wrnpctile,
lkbT=self.params.lkbT,
lkbB=self.params.lkbB,
)
self.wvf = Vix_Fix_Indicator(self.datas[0],
pd = self.params.pd,
bbl=self.params.bbl,
mult=self.params.mult,
lb=self.params.lb,
ph=self.params.ph,
pl=self.params.pl,
)
ap = (self.datas[0].high + self.datas[0].low + self.datas[0].close)/3
esa = btind.ExponentialMovingAverage(ap, period = self.params.n1)
d = btind.ExponentialMovingAverage(abs(ap - esa), period = self.params.n1)
ci = (ap - esa) / (0.015 * d)
self.tci = btind.ExponentialMovingAverage(ci, period = self.params.n2)
self.ma1 = btind.ZeroLagExponentialMovingAverage(self.datas[0], period = self.params.ma1)
self.ma2 = btind.MovingAverageSimple(self.datas[0], period=self.params.ma2)
self.rsi = btind.RelativeStrengthIndex(self.datas[0], period = self.params.rsi_period)
self.prank= btind.PercentRank(self.rsi, period = self.params.percent_period) * 100
self.pendingBuy = False
self.pendingSell = False
def __init__(self, pool_list, dataId_to_ticker_d, ticker_to_dataId_d,start_date,end_date, ref_price):
# Keep a reference to the "close" line in the data[0] dataseries
self.bar_num=0
#self.index_50_date_stock_dict=self.get_index_50_date_stock()
self.dataId_to_ticker_dict = dataId_to_ticker_d
self.ticker_to_dataId_dict = ticker_to_dataId_d
self.position_list = []
self.pool_list = pool_list
self.start_date = start_date
self.end_date = end_date
self.ref_price = ref_price
self.newLowDiv = 100
self.newLowIndex = 0
self.csCount = 0
#mk_view_list order [ticker, cs, sm, ml]
global mk_view_list
mk_view_list = []
mk_view_list.append(pool_list[0])
for x in range(len(conf_mk_view_col)-1):
mk_view_list.append(0)
for d in self.datas:
## d.baseline = btind.ExponentialMovingAverage(d, period=21)
d.ema20 = btind.ExponentialMovingAverage(d, period=20)
d.ema60 = btind.ExponentialMovingAverage(d, period=60)
d.priceDiv = PriceDiv(d)
self.log('stategy Divergence init :' + d._name)
def __init__(self):
super().__init__()
ap = (self.datas[0].high + self.datas[0].low + self.datas[0].close)/3
esa = btind.ExponentialMovingAverage(ap, period = self.params.n1)
d = btind.ExponentialMovingAverage(abs(ap - esa), period = self.params.n1)
ci = (ap - esa) / (0.015 * d)
self.tci = btind.ExponentialMovingAverage(ci, period = self.params.n2)
def __init__(self):
for d in self.datas:
d.fastma = btind.ExponentialMovingAverage(d, period=self.p.fastlength)
d.slowma = btind.ExponentialMovingAverage(d, period=self.p.slowlength)
d.atr = btind.AverageTrueRange(d, period=14)
d.atrp = d.atr/d
if self.p.log:
self.logfile = open('ma_crossover_strat.txt', 'w')
if self.p.recordstats:
self.statsfile = Statistics()
def __init__(self):
for d in self.datas:
d.overma = ZackOverMA(d, avglength=15, sumlength=50)
d.fastma = btind.ExponentialMovingAverage(d, period=self.p.fastlength)
d.slowma = btind.ExponentialMovingAverage(d, period=self.p.slowlength)
d.atr = btind.AverageTrueRange(d, period=14)
d.rsi = btind.RelativeStrengthIndex(d, period=14)
if self.p.log:
self.logfile = open('ma_crossover_strat.txt', 'w')
if self.p.recordstats:
self.statsfile = Statistics()
def __init__(self):
self.rsi = btind.RSI(period=self.params.period)
# self.macd = btind.MACD()
# self.macd = btind.EMA(9) - btind.EMA(14)
# self.signal = btind.EMA(14)
self.sma = btind.SimpleMovingAverage(period=21)
self.ema = btind.ExponentialMovingAverage(period=14)
self.accDe = btind.AccDeOsc(period=14)
self.close_over_sma = self.data.close > self.sma
self.close_over_ema = self.data.close > self.ema
self.sma_ema_diff = self.sma - self.ema
self.buy_sig = bt.And(self.close_over_sma, self.close_over_ema,
self.sma_ema_diff > 0)
self.max_pos = 10
self.overSold = self.rsi < 50
self.overBought = self.rsi > 70
self.oscSig = self.accDe > 0
self.buy_price = []
self.sell_price = []
self.buy_price = []
self.sell_price = []
self.ave_buy = 0
self.ave_sell = 0
def __init__(self):
# Keep a reference to the "close" line in the data[0] dataseries
self.dataclose = self.datas[0].close
# To keep track of pending orders and buy price/commission
self.order = None
self.buyprice = None
self.buycomm = None
# Add a MovingAverageSimple indicator
self.ema1 = btind.ExponentialMovingAverage(self.datas[0],
period=self.p.pfast)
self.ema2 = btind.ExponentialMovingAverage(self.datas[0],
period=self.p.pslow)
self.crossover = btind.CrossOver(self.ema1,
self.ema2) # crossover signal
def __init__(self, pool_list, dataId_to_ticker_d, ticker_to_dataId_d):
# Keep a reference to the "close" line in the data[0] dataseries
self.bar_num = 0
#self.index_50_date_stock_dict=self.get_index_50_date_stock()
self.dataId_to_ticker_dict = dataId_to_ticker_d
self.ticker_to_dataId_dict = ticker_to_dataId_d
self.position_list = []
self.pool_list = pool_list
for d in self.datas:
## d.baseline = btind.ExponentialMovingAverage(d, period=21)
## d.aroon = btind.AroonUpDown(d, period=14)
d.emaSig = btind.ExponentialMovingAverage(d, period=20)
d.emaBase = btind.ExponentialMovingAverage(d, period=40)
d.schaff = SchaffTrend(d)
self.log('stategy data init :' + d._name)
def __init__(self, pool_list, dataId_to_ticker_d, ticker_to_dataId_d):
# Keep a reference to the "close" line in the data[0] dataseries
self.bar_num=0
#self.index_50_date_stock_dict=self.get_index_50_date_stock()
self.dataId_to_ticker_dict = dataId_to_ticker_d
self.ticker_to_dataId_dict = ticker_to_dataId_d
self.position_list = []
self.pool_list = pool_list
self.divUnder = 0 #weight of price divergence
for d in self.datas:
## d.baseline = btind.ExponentialMovingAverage(d, period=21)
d.ema20 = btind.ExponentialMovingAverage(d, period=20)
d.ema60 = btind.ExponentialMovingAverage(d, period=60)
d.priceDiv = PriceDiv(d)
self.log('stategy data init :' + d._name)
def __init__(self):
# To control operation entries
self.orderid = None
# Indicators
poc = btind.SimpleMovingAverage(
self.data0.POC,
period=1,
plotname='POC',
subplot=False,
)
ppoc = btind.SimpleMovingAverage(
self.data0.PPOC,
period=1,
plotname='PPOC',
subplot=False,
)
self.atr = bt.talib.ATR(self.data0.high,
self.data0.low,
self.data0.close,
timeperiod=14)
#self.rsi = bt.talib.RSI(self.data0.close, timeperiod=14)
#self.macd = bt.talib.MACD(self.data0.close)
self.ematr = btind.ExponentialMovingAverage(self.atr, period=89)
self.signal1 = btind.CrossOver(self.data0.close, poc, plot=False)
self.signal2 = btind.CrossOver(self.data0.close, ppoc, plot=False)
self.flag = True
self.flag1 = False
def __init__(self):
self.__fastEMA = btind.ExponentialMovingAverage()
self.__slowEMA = btind.ExponentialMovingAverage()
self.long_alert = self.data.close > self.__slowEMA
self.short_alert = self.data.close < self.__fastEMA
self.long_confirmation = self.__fastEMA > self.__slowEMA
self.short_confirmation = self.__fastEMA < self.__slowEMA
self.long_signal = self.data.close <= self.__fastEMA
self.short_signal = self.data.close >= self.__fastEMA
self.buy_sig = bt.And(self.long_alert, self.long_confirmation,
self.long_signal)
self.sell_sig = bt.And(self.short_alert, self.short_confirmation,
self.short_signal)
def set_datalines(self):
self.indicators = []
period = self.dim_time
self.indicators.append(
btind.ExponentialMovingAverage(self.datas[0], period=15))
self.indicators.append(btind.MACDHisto(self.datas[0]))
self.indicators.append(btind.RSI(self.datas[0], period=15))
self.indicators.append(btind.BollingerBandsPct(self.datas[0]))
def __init__(self):
sma1 = btind.SimpleMovingAverage(self.data)
ema1 = btind.ExponentialMovingAverage()
close_over_sma = self.data.close > sma1
close_over_ema = self.data.close > ema1
sma_ema_diff = sma1 - ema1
buy_sig = bt.And(close_over_sma, close_over_ema, sma_ema_diff > 0)
def __init__(self, pool_list, dataId_to_ticker_d, ticker_to_dataId_d,
start_date, end_date):
# Keep a reference to the "close" line in the data[0] dataseries
self.bar_num = 0
#self.index_50_date_stock_dict=self.get_index_50_date_stock()
self.pool_list = pool_list
self.dataId_to_ticker_dict = dataId_to_ticker_d
self.ticker_to_dataId_dict = ticker_to_dataId_d
self.start_date = start_date
self.end_date = end_date
self.position_list = [
] #postion order ["sym", "date", "close", "high", "perc", "exit","edate","eperc","strategy"]
self.csCount = 0
self.barDiv = 0
self.periodTD9 = 12
self.pastTD9 = [0] * 20
self.downTD9 = 0
self.hasPosition = False
self.entryPrice = 100
self.highPrice = 100
self.newLowDiv = 100
self.newLowBar = 0
self.atrTrend = False
self.curStrategy = 0 #0:idle 10:divergence 11: div + 20ma turn up div+20ma is what happen after divergence
#20:atr
global g_entry_list
g_entry_list = []
# add indicators
for d in self.datas:
## d.baseline = btind.ExponentialMovingAverage(d, period=21)
d.ema20 = btind.ExponentialMovingAverage(d, period=20)
d.ema60 = btind.ExponentialMovingAverage(d, period=60)
d.macd = btind.MACD(d)
d.priceDiv = PriceDiv(d)
d.data_obv = OnBalanceVolume(d)
d.data_obv20 = btind.SMA(d.data_obv, period=20)
d.data_atr = AtrTrend(d)
#d.data_bb = btind.BollingerBands(d, period=20, devfactor=2.0)
#d.data_kc = KeltnerChannel(d, periodEMA = 20, periodATR = 20, devfactor=1.5 )
#d.data_rg = RGChannel(d)
self.log('stategy ATR init :' + d._name)
def __init__(self):
self.sma1 = btind.SimpleMovingAverage(self.data)
self.ema1 = btind.ExponentialMovingAverage()
self.close_over_sma = self.data.close > self.sma1
self.close_over_ema = self.data.close > self.ema1
self.sma_ema_diff = self.sma1 - self.ema1
# 生成交易信号
self.buy_sig = bt.And(self.close_over_sma, self.close_over_ema,
self.sma_ema_diff > 0)
def __init__(self, pool_list, dataId_to_ticker_d, ticker_to_dataId_d,
start_date, end_date):
# Keep a reference to the "close" line in the data[0] dataseries
self.bar_num = 0
#self.index_50_date_stock_dict=self.get_index_50_date_stock()
self.pool_list = pool_list
self.dataId_to_ticker_dict = dataId_to_ticker_d
self.ticker_to_dataId_dict = ticker_to_dataId_d
self.start_date = start_date
self.end_date = end_date
self.position_list = [
] #postion order ["sym", "date", "close", "high", "perc", "exit","edate","eperc"]
self.csCount = 0
self.hasPosition = False
self.entryPrice = 100
self.highPrice = 100
self.newLowDiv = 100
self.newLowBar = 0
global g_entry_list
g_entry_list = []
# add indicators
for d in self.datas:
## d.baseline = btind.ExponentialMovingAverage(d, period=21)
d.ema20 = btind.ExponentialMovingAverage(d, period=20)
d.ema60 = btind.ExponentialMovingAverage(d, period=60)
d.macd = btind.MACD(d)
d.priceDiv = PriceDiv(d)
d.data_obv = OnBalanceVolume(d)
d.data_obv20 = btind.SMA(d.data_obv, period=20)
d.data_bb = btind.BollingerBands(d, period=14, devfactor=2.0)
d.data_kc = KeltnerChannel(d,
periodEMA=20,
periodATR=20,
devfactor=1.5)
d.data_rg = RGChannel(d)
self.log('stategy data init :' + d._name)
def __init__(self):
avgvol = btind.ExponentialMovingAverage(self.data.volume,
period=self.p.avgvollength)
priceUp = btind.If(
self.data.volume(0) > avgvol(0),
btind.If(
self.data(0) > self.data(-1),
(self.data(0) - self.data(-1)) / self.data(0), 0), 0)
priceDown = btind.If(
self.data.volume(0) > avgvol(0),
btind.If(
self.data(0) < self.data(-1),
(self.data(-1) - self.data(0)) / self.data(0), 0), 0)
self.lines.up = self.p.movav(priceUp, period=self.p.period)
self.lines.down = self.p.movav(priceDown, period=self.p.period)
def __init__(self):
# To control operation entries
self.orderid = None
# Indicators
poc = btind.SimpleMovingAverage(self.data0.POC,
period=1,
plotname='POC')
ppoc = btind.SimpleMovingAverage(self.data0.PPOC,
period=1,
plotname='PPOC')
self.atr = bt.talib.ATR(self.data0.high,
self.data0.low,
self.data0.close,
period=14)
self.ematr = btind.ExponentialMovingAverage(self.atr, period=89)
self.dataclose = self.data0.close
self.anchor = 3.0
self.expand = 1.0
self.signal1 = btind.CrossOver(self.dataclose, poc, plotname='POC')
self.signal2 = btind.CrossOver(self.dataclose, ppoc, plotname='PPOC')
#self.trailing = True
self.flag = True
def __init__(self):
ema = btind.ExponentialMovingAverage(self.data, period=self.p.period)
sma = btind.MovingAverageSimple(self.data, period=self.p.period)
self.lines.res = (ema*ema-sma*sma) / (self.data)
