def __init__(self):
# 交易日志
self.buysellLog = ""
# 每日收盘价
self.dataclose = self.datas[0].close
# 订单
self.order = None
self.buyprice = 0
self.buycomm = 0
self.buytime = 0
#10日、60日均线
self.SAM10 = btind.MovingAverageSimple(
self.dataclose(0),
period=self.params.maperiod1,
subplot=False,
plotname=str(self.params.maperiod1) + '日均线')
self.SAM60 = btind.MovingAverageSimple(
self.dataclose(0),
period=self.params.maperiod2,
subplot=False,
plotname=str(self.params.maperiod2) + '日均线')
# 均线交叉
self.Crossover = btind.CrossOver(self.SAM10,
self.SAM60,
plotname='双均线交叉')
def __init__(self):
super().__init__()
self.di = btind.DirectionalMovement(self.datas[0], period = self.p.di_period)
self.ma1 = btind.MovingAverageSimple(self.datas[0], period = self.p.ma1)
self.ma2 = btind.MovingAverageSimple(self.datas[0], period=self.p.ma2)
self.bbands = btind.BollingerBands(self.datas[0], period = self.p.band_period, devfactor = self.p.devfactor)
self.ma = btind.MovingAverageSimple(self.datas[0], period=self.p.band_period)
range = btind.TrueRange(self.datas[0])
self.rangema = btind.MovingAverageSimple(range, period = self.p.band_period)
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
self.order = None
smaFast = btind.MovingAverageSimple(period=self.params.STMAperiod)
smaSlow = btind.MovingAverageSimple(period=self.params.LTMAperiod)
self.buysig = btind.CrossOver(smaFast, smaSlow)
def __init__(self):
for d in self.datas:
d.madiff = ZackOverMA(d, avglength=self.p.avglength, sumlength=self.p.sumlength)
d.ma = btind.MovingAverageSimple(d, period=self.p.avglength)
d.maslope = d.ma(0) - d.ma(-1)
self.logfile = open('log.txt', 'w')
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):
diff = self.data.high(0) - self.data.low(0)
avg = btind.MovingAverageSimple(diff, period=self.p.period)
self.lines.cv = btind.If(
avg(-self.p.rocperiod) == 0, 100,
(avg(0) - avg(-self.p.rocperiod)) / avg(-self.p.rocperiod) * 100)
def __init__(self):
for d in self.datas:
d.overma = ZackOverMA(d,
avglength=self.p.avglength,
sumlength=self.p.sumlength)
d.atr = btind.AverageTrueRange(d, period=self.p.atrperiod)
d.atrp = d.atr / d # atr as a % of stock price
d.ma = btind.MovingAverageSimple(d, period=self.p.avglength)
d.maslope = d.ma(0) - d.ma(-1)
d.avgvolume = btind.MovingAverageSimple(d.volume,
period=self.p.avglength)
d.pivot = ZackPivotPoints(d,
avglength=self.p.pivotavglength,
sumlength=self.p.pivotsumlength)
d.pivot2 = ZPP(d, avglength=9)
if self.p.log:
self.logfile = open('overma.txt', 'w')
def __init__(self):
super().__init__()
self.ma = btind.MovingAverageSimple(self.datas[0], period = self.params.ma)
self.ma1 = btind.MovingAverageSimple(self.datas[0], period = self.params.ma1)
self.ma2 = btind.MovingAverageSimple(self.datas[0], period = self.params.ma2)
self.atr = btind.AverageTrueRange(self.datas[0])
self.kst = btind.KnowSureThing(self.datas[0])
self.macd = btind.MACD(self.datas[0])
self.trix = btind.TrixSignal(self.datas[0])
self.ao = btind.AwesomeOscillator(self.datas[0])
self.tsi = btind.TrueStrengthIndicator(self.datas[0])
self.psar = btind.ParabolicSAR(self.datas[0])
self.adx = btind.AverageDirectionalMovementIndex(self.datas[0])
self.dpo = btind.DetrendedPriceOscillator(self.datas[0])
self.rsi = btind.RSI(self.datas[0])
self.accdec = btind.AccelerationDecelerationOscillator(self.datas[0])
self.bbands = btind.BollingerBands(self.datas[0])
self.cci = btind.CommodityChannelIndex(self.datas[0])
self.pgood = btind.PrettyGoodOscillator(self.datas[0])
self.williamsr = btind.WilliamsR(self.datas[0])
self.uo = btind.UltimateOscillator(self.datas[0])
self.stoch = btind.Stochastic(self.datas[0])
def __init__(self):
for d in self.datas:
d.pivotpoints = ZackPivotPoints(d,
avglength=self.p.avglength,
sumlength=self.p.sumlength)
d.sma = btind.MovingAverageSimple(d, period=self.p.malength)
d.smaslope = d.sma(0) - d.sma(-1)
d.atr = btind.AverageTrueRange(d, period=self.p.atrlength)
d.quality = AboveMAAccum(d,
avglength=self.p.qualityavglength,
sumlength=self.p.qualitysumlength)
if self.p.log:
self.logfile = open('pivotpoints.txt', 'w')
def __init__(self):
ma = btind.MovingAverageSimple(self.data, period=self.p.avglength)
# self.lines.accum = btind.Accum((self.data - ma) / ma)
self.lines.accum = btind.SumN((self.data-ma) / ma, period=self.p.sumlength)
self.lines.slope = self.accum(0) - self.accum(-1)
def __init__(self):
self.l.ha_close = ha_close = (self.data.open + self.data.close + self.data.high + self.data.low) / 4.0
self.l.ha_open = ha_open = (self.l.ha_open(-1) + ha_close(-1)) / 2.0
diff = ha_close(0) - ha_open(0)
self.lines.diff = btind.MovingAverageSimple(diff, period=5)
def __init__(self):
smoothFactor = btind.MovingAverageSimple(self.data, period=self.p.smoothPeriod)
dailyReturn = (self.data(0)-self.data(-1)) / smoothFactor
self.lines.vol = btind.StandardDeviation(dailyReturn, period=self.p.period)
def __init__(self):
price = btind.MovingAverageSimple(self.data, period=self.p.period)
roc = 100 * (price(0) / price(-self.p.period)-1)
maxvol = btind.Highest(self.data.volume, period=self.p.period)
self.lines.effort = roc / maxvol
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)
def __init__(self):
super().__init__()
self.ma1 = btind.MovingAverageSimple(self.datas[0], period = self.params.ma1)
self.ma2 = btind.MovingAverageSimple(self.datas[0], period = self.params.ma2)
self.rsi = btind.LaguerreRSI(self.datas[0], period = self.params.period, gamma = self.params.gamma)
def __init__(self):
self.price = (self.data.close + self.data.high + self.data.low) / 3
self.r2 = btind.MovingAverageSimple(self.price * 2 - self.data.low,
period=self.p.avglength)
self.s2 = btind.MovingAverageSimple(self.price * 2 - self.data.high,
period=self.p.avglength)
def __init__(self):
self.mavg200 = btind.MovingAverageSimple(self.data.close, period=200)
self.mavg50 = btind.MovingAverageSimple(self.data.close, period=50)
self.crossover = btind.CrossOver(self.mavg50, self.mavg200)
self.size = 0
self.order_percentage = 0.5
def __init__(self, store):
self.buy_order = None
self.live_data = False
# Attach and retrieve values from the MT5 indicator "Examples/Custom Moving Average"
self.mt5cma = getMTraderIndicator(
# MTraderStorestore instance
store,
# Data feed to run the indicator calculations on
self.datas[0],
# Set accessor(s) for the indicator output lines
(
"cma", ),
# MT5 inidicator name
indicator="Examples/Custom Moving Average",
# Indicator parameters.
# Any omitted values will use the defaults as defind by the indicator.
# The parameter "params" must exist. If you want to use only the indicator defaults,
# pass an empty list: params=[],
params=[13, 0, "MODE_SMMA"],
)()
# Instantiating backtrader indicator Bollinger Bands and Moving Averages
# Important: This needs to come before instantiating a chart window
# with backtradermql5.mt5indicator.MTraderChart. Otherwise backtrader will fail.
self.bb = btind.BollingerBands(self.datas[0])
self.sma = btind.MovingAverageSimple(self.datas[0])
# -----> Experimental feature BEGIN
# The feaure to plot data to MT5 chart windows WILL plot false data at this point in time. More work is needed.
# Plot the backtrader BollingerBand and SMA indicators to a chart window in MT5
def addChart(chart, bb, sma):
# Instantiate new indicator and draw to the main window. The parameter idx=0 specifies wether to plot to the
# main window (idx=0) or a subwindow (idx=1 for the first subwindow, idx=2 for the second etc.).
indi0 = ChartIndicator(idx=0, shortname="Bollinger Bands")
# # Add line buffers
indi0.addline(
bb.top,
style={
"linelabel": "Top",
"color": "clrBlue",
},
)
indi0.addline(
bb.mid,
style={
"linelabel": "Middle",
"color": "clrYellow",
},
)
indi0.addline(
bb.bot,
style={
"linelabel": "Bottom",
"color": "clrGreen",
},
)
# Add the indicator to the chart and draw the line buffers.
chart.addchartindicator(indi0)
# # Instantiate second indicator to draw to the first sub-window and add line buffers
indi1 = ChartIndicator(idx=1, shortname="Simple Moving Average")
indi1.addline(
sma.sma,
style={
"linelabel": "SMA",
"color": "clrBlue",
"linestyle": "STYLE_DASH",
"linewidth": 2
},
)
chart.addchartindicator(indi1)
# Instantiate a new chart window and plot
chart = MTraderChart(self.datas[0], realtime=False)
addChart(chart, self.bb, self.sma)
def __init__(self):
super().__init__(self)
ma = btind.MovingAverageSimple(self.data.volume * self.datas[0].close , period = self.params.period) / btind.MovingAverageSimple(self.data.volume, period = self.params.period)
self.lines.vwma = ma
def __init__(self):
super().__init__()
self.ma1 = btind.MovingAverageSimple(self.data, period = self.params.ma1)
self.ma2 = btind.MovingAverageSimple(self.data, period = self.params.ma2)
self.ma3 = btind.MovingAverageSimple(self.data1, period = self.params.ma3)
self.ma4 = btind.MovingAverageSimple(self.data1, period = self.params.ma4)
def __init__(self):
self.sma = btind.MovingAverageSimple(period=8)
def __init__(self):
for d in self.datas:
d.slowma = btind.MovingAverageSimple(d, period=self.p.longperiod)
d.fastma = btind.MovingAverageSimple(d, period=self.p.shortperiod)
def __init__(self):
super().__init__()
self.ma1 = btind.MovingAverageSimple(self.datas[0], period = self.params.ma1)
self.ma2 = btind.MovingAverageSimple(self.datas[0], period = self.params.ma2)
self.stoch = btind.Stochastic(self.datas[0], period = self.params.period)
