def step(data, draw):
# take one step through time
# value of p in previous period
pLag1 = fs.recall(data, "p", lag=1)
eps = 0.0
# update all intermediate variables
pNew = gbm(s0=pLag1, dt=1.0 / 12.0, mu=0.05, sig=0.10, eps=eps)
cNew = max(0.0, pNew - 1.0)
# return updated price history
dataNew = fs.chron(data, {"p": pNew, "c": cNew})
return dataNew
def step(data, draw):
# take one step through time
# value of p in previous period
pLag1 = fs.recall(data, "p", lag=1)
# uniform draw --> standard normal draw
u = next(draw)
eps = stats.norm.ppf(u)
# update all intermediate variables
pNew = gbm(s0=pLag1, dt=1.0 / 12.0, mu=0.01, sig=0.10, eps=eps)
cNew = max(0.0, pNew - 1.0)
# return updated price history
dataNew = fs.chron(data, {"p": pNew, "c": cNew})
return dataNew