def __init__(self):
self.sma5 = btind.SimpleMovingAverage(period=5) # 5日均线
self.sma10 = btind.SimpleMovingAverage(period=10) # 10日均线
# bt.And 中所有条件都满足时返回 1；有一个条件不满足就返回 0
self.And = bt.And(self.data > self.sma5, self.data > self.sma10,
self.sma5 > self.sma10)
# bt.Or 中有一个条件满足时就返回 1；所有条件都不满足时返回 0
self.Or = bt.Or(self.data > self.sma5, self.data > self.sma10,
self.sma5 > self.sma10)
# bt.If(a, b, c) 如果满足条件 a，就返回 b，否则返回 c
self.If = bt.If(self.data > self.sma5, 1000, 5000)
# bt.All,同 bt.And
self.All = bt.All(self.data > self.sma5, self.data > self.sma10,
self.sma5 > self.sma10)
# bt.Any，同 bt.Or
self.Any = bt.Any(self.data > self.sma5, self.data > self.sma10,
self.sma5 > self.sma10)
# bt.Max，返回同一时刻所有指标中的最大值
self.Max = bt.Max(self.data, self.sma10, self.sma5)
# bt.Min，返回同一时刻所有指标中的最小值
self.Min = bt.Min(self.data, self.sma10, self.sma5)
# bt.Sum，对同一时刻所有指标进行求和
self.Sum = bt.Sum(self.data, self.sma10, self.sma5)
# bt.Cmp(a,b), 如果 a>b ，返回 1；否则返回 -1
self.Cmp = bt.Cmp(self.data, self.sma5)
def __init__(self):
self.ma = bt.ind.EMA(period=10)
self.cross = bt.ind.CrossOver(self.datas[0].close, self.ma)
# Single logic
self.lg = bt.Log(self.datas[0].close)
self.cl = bt.Ceiling(self.datas[0].close)
self.fl = bt.Floor(self.datas[0].close)
self.cross_abs = bt.Abs(self.cross)
# Check Multi still works
self.mx = bt.Max(self.datas[0].close, self.datas[0].open)
def __init__(self):
o = self.data.open
h = self.data.high
l = self.data.low
c = self.data.close
self.l.ha_close = ha_close = (o + h + l + c) / 4.0
self.l.ha_open = ha_open = (self.l.ha_open(-1) + ha_close(-1)) / 2.0
self.l.ha_high = bt.Max(h, ha_open, ha_close)
self.l.ha_low = bt.Min(l, ha_open, ha_close)
super(HeikinAshi, self).__init__()
def __init__(self):
h0l1 = abs(self.data.high(0) - self.data.low(-1))
vm_plus = bt.ind.SumN(h0l1, period=self.p.period)
l0h1 = abs(self.data.low(0) - self.data.high(-1))
vm_minus = bt.ind.SumN(l0h1, period=self.p.period)
h0c1 = abs(self.data.high(0) - self.data.close(-1))
l0c1 = abs(self.data.low(0) - self.data.close(-1))
h0l0 = abs(self.data.high(0) - self.data.low(0))
tr = bt.ind.SumN(bt.Max(h0l0, h0c1, l0c1), period=self.p.period)
self.l.vi_plus = vm_plus / tr
self.l.vi_minus = vm_minus / tr
def __init__(self):
wick_range = self.data.high - self.data.low
body_high = bt.Max(self.data.close, self.data.open)
body_low = bt.Min(self.data.close, self.data.open)
body_range = body_high - body_low
wick_buy = (body_low - self.data.low) >= (
self.p.wick_multiplier_min * body_range)
wick_sell = (self.data.high - body_high) >= (
self.p.wick_multiplier_min * body_range)
# be careful, if wick range = 0 then close-low = 0 ; so avoiding divide
# by zero list this is correct
close_percent = (self.data.close - self.data.low) / bt.If(
wick_range == 0.0, 0.1, wick_range)
close_buy = (close_percent >= (1 - self.p.close_percent_max))
close_sell = (close_percent <= self.p.close_percent_max)
self.lines.wick = bt.If(bt.And(wick_buy, close_buy),
self.data.low,
bt.If(bt.And(wick_sell, close_sell),
self.data.high,
np.NaN)
)
def __init__(self):
self.strat = self._owner # alias for clarity
self.smaShort = bt.ind.SMA(self.data, period=self.p.period_short)
self.smaMid = bt.ind.SMA(self.data, period=self.p.period_middle)
self.smaLong = bt.ind.SMA(self.data, period=self.p.period_long)
self.emaShort = bt.ind.EMA(self.data, period=self.p.period_short)
self.emaMid = bt.ind.EMA(self.data, period=self.p.period_middle)
self.emaLong = bt.ind.EMA(self.data, period=self.p.period_long)
self.boll = bt.ind.BollingerBands(self.data)
self.bollDiff = self.boll.top - self.boll.bot
self.bollSignal = bt.ind.EMA(self.bollDiff, period=self.p.period_short)
self.l.BollRange = bt.If(bt.And(self.bollDiff/self.p.boll_range_ThresholdValue > self.bollSignal, self.data > self.boll.mid), 1, 0)
self.l.BollRange = bt.If(
bt.And(self.bollDiff / self.p.boll_range_ThresholdValue > self.bollSignal, self.data < self.boll.mid), -1, self.l.BollRange)
self.bollHisto = self.bollDiff - self.bollSignal
jxmj_cs = abs(self.data / self.smaShort - 1)*100
jxmj_sm = abs(self.smaShort / self.smaMid - 1) * 100
jxmj_ml = abs(self.smaMid / self.smaLong - 1) * 100
self.JXMJ = JXMJDayFsumIndicator(bt.Max(jxmj_cs,jxmj_sm,jxmj_ml), period=self.p.period_jxmj).l.JXMJFsum
self.l.JXMJ = bt.If( bt.And(self.JXMJ > self.p.jxmj_ThresholdValue, self.smaMid > self.smaLong), 1, 0)
self.l.JXMJHoldState = self.data - self.data
self.l.JXMJBuySellPoint = self.data - self.data
self.lastClosePrice = 0
dfgl_cs = self.data - self.emaShort
dfgl_sm = self.emaShort - self.emaMid
dfgl_ml = self.emaMid - self.emaLong
self.dfgl = bt.ind.PercentRank(abs(dfgl_sm), period=self.p.period_dfgl)
self.l.DFGL = bt.If( bt.And(self.dfgl > self.p.dfgl_ThresholdValue, dfgl_sm > 0), 1, 0)
self.holdStateLow = 9999
self.holdStateHigh = 0
def __init__(self):
hl2 = (self.data.high + self.data.low) / 2
#ttr = bt.indicators.TrueRange(self.data)
#ttr = bt.Max(self.data.high- self.data.low,
# bt.Max(abs(self.data.high(0) - self.data.close(-1)),
# abs(self.data.low(0) - self.data.close(-1))))
#atr2 = RelativeMovingAverage(ttr, period=self.p.ATRPeriod)
#atr30 = bt.ind.SMA(ttr, period=30)
#atr20 = bt.ind.SMA(ttr, period=20)
#atr2 = atr30 - atr20 + bt.ind.SMA(ttr, period=self.p.ATRPeriod)
#atr2 = bt.ind.EMA(ttr, period=self.p.ATRPeriod)
atr2 = bt.indicators.AverageTrueRange(self.data,
period=self.p.ATRPeriod)
upSrc = hl2 - (self.p.Multiplier * atr2)
#up := close[1] > up1 ? max(up,up1) : up
self.lines.up = btind.If(
self.data.close(-1) > upSrc(-1), bt.Max(upSrc, upSrc(-1)), upSrc)
dnSrc = hl2 + (self.p.Multiplier * atr2)
#dn := close[1] < dn1 ? min(dn, dn1) : dn
self.lines.dn = btind.If(
self.data.close(-1) < dnSrc(-1), bt.Min(dnSrc, dnSrc(-1)), dnSrc)
"""
trd = self.data.close - self.data.close + 1
trd2 = btind.If(trd(-1) < 0,
btind.If(self.data.close > dn,1,trd2(-1)),
btind.If(self.data.close < up, -1, trd2(-1)))
#trd2 = btind.If((trd(-1) < 0) and (self.data.close(0) > dn(0)),
#1, btind.If(trd(-1) > 0 and self.data.close(0) < up(0), -1, 0))
self.lines.trend = trd2
#btind.If((trd(-1) < 0) and (self.data.close > dn),
# 1, btind.If(trd(-1) > 0 and self.data.close < up, -1, 0))
"""
super(AtrTrend, self).__init__()
def __init__(self):
self.lines.mlli = bt.Max(-1.0, self.lag_index())
super(MlLagIndicator, self).__init__()
def __init__(self):
# __init__() 中是对 line 进行运算，最终也以 line 的形式返回，所以运算结果直接赋值给了 self.l.dummyline；
self.l.dummyline = bt.Max(0.0, self.p.value)
def __init__(self):
self.lines.dummyline = bt.Max(0.0, self.params.value)
