def BollingerBands(price):
from math import sqrt
MA = lambda p, n: sum(p[-n:])/len(p[-n:])
ma = obs.aggregate(price, lambda p: MA(p, 20), window=20, name="MA20")
std_dev = obs.aggregate([price, ma], lambda x: sqrt(sum([(v[1]-v[0])**2 for v in x])/len(x)), name="MA20sd", window=20)
STDhi = indicator([ma, std_dev], lambda (m, s): m + 2*s, name="bollingerHI")
STDmi = indicator(ma, name="bollingerMI")
STDlo = indicator([ma, std_dev], lambda (m, s): m - 2*s, name="bollingerLO")
return [STDhi, STDmi, STDlo]
def MACD(price):
EWMA = lambda alpha: (lambda p: reduce(lambda x, y: x + (y-x)*alpha, p, 0))
ewma12 = obs.aggregate(price, EWMA(2./13), window=12, name="EWMA12")
ewma26 = obs.aggregate(price, EWMA(2./27), window=26, name="EWMA26")
macd_signal = obs.aggregate([ewma12, ewma26], lambda (x, y): x-y, name="MACDsignal")
macd_line = obs.OnEveryDt(1, macd_signal)
signal_line = indicator(macd_signal, EWMA(2./10), window=9, name="signal_line")
MACD = [macd_line, signal_line]
return MACD
def indicator(sources, f=(lambda x: x), window=1, name=None):
return obs.OnEveryDt(1, obs.aggregate(sources, f, window, name))