A
how i solved the problem (just used next method to calculate the SMMA explicitly in each step):
class RelativeVolatility(bt.Indicator):
lines = ('rel_vol', 'signal', 'nU', 'nD',)
plotlines = dict(nU=dict(_plotskip=True), nD=dict(_plotskip=True))
params = (('period', 10), ('signal_line_top', 80), ('signal_line_bottom', 20),)
def _plotinit(self):
self.plotinfo.plothylines = [self.p.signal_line_top, self.p.signal_line_bottom]
def __init__(self):
std_dev = bt.ind.StdDev(self.data.close, period=self.p.period)
self.u = bt.If(self.data.close > self.data.close(-1), std_dev, 0)
self.d = bt.If(self.data.close < self.data.close(-1), std_dev, 0)
def nextstart(self):
self.l.nU[0] = 0
self.l.nD[0] = 0
def next(self):
self.l.nU[0] = (13. * self.l.nU[-1] + self.u[0]) / 14.
self.l.nD[0] = (13. * self.l.nD[-1] + self.d[0]) / 14.
self.l.rel_vol[0] = 100. * self.l.nU[0] / (self.l.nU[0] + self.l.nD[0])
I tried again to directly switch SMA to SMMA.. but it really doesn't work for me:
def __init__(self):
std_dev = bt.ind.StdDev(self.data.close, period=self.p.period)
u = bt.If(self.data.close > self.data.close(-1), std_dev, 0)
d = bt.If(self.data.close < self.data.close(-1), std_dev, 0)
nU = btind.SMMA(u, period=14)
nD = btind.SMMA(d, period=14)
self.l.rel_vol = 100. * nU / (nU + nD)
gives me lists full of nan's in nU and nD...