def run_sim(self,
stm=3,
ns=15,
min_fast=0.,
min_slow=0.,
max_z=1.,
fast=True,
fundamental=False):
s1 = -1. * cross.get_stock_mom(self.rm, stm)
s2 = cross.get_stock_mom(self.rm, 52).shift(stm)
s3 = cross.get_stock_mom(self.rm, 52)
holding = 0
input1 = s1 if fast else s2
if fundamental:
input2 = self.score
else:
input2 = s2 if fast else s1
f = 1. * (s1 >= min_fast) * (s3 >= min_slow) * (self.z <=
max_z) * (self.z >= 0)
ans = cross.get_step_positions(input1,
input2,
self.vol,
ns,
f,
None,
holding=holding)
ra = cross.get_portfolio_returns(ans, self.rtn)
return ans, ra
def get_fast_fundamental_signal(rtn, rm, vol, score, stm=3, ns=8, min_fast=1.5, min_slow=.4):
'''
1st Gen fast fundamental signal
'''
s1 = -1. * cross.get_stock_mom(rm, stm)
s3 = cross.get_stock_mom(rm, 52)
base = 1. * (s1 >= min_fast) * (s3 >= min_slow)
ans = cross.get_step_positions(s1, score, vol, ns, base, None, holding=0)
return ans
def get_slow_signal(rtn, rm, vol, stm=3, ns=7, min_fast=1.5, min_slow=.4):
'''
1st Gen slow signal
'''
s1 = -1. * cross.get_stock_mom(rm, stm)
s2 = cross.get_stock_mom(rm, 52).shift(stm)
s3 = cross.get_stock_mom(rm, 52)
base = 1. * (s1 >= min_fast) * (s3 >= min_slow)
ans = cross.get_step_positions(s2, s1, vol, ns, base, None, holding=0)
return ans
def get_good_signal(rtn, rm, vol, stm=3, ns=10, min_fast=1.5, min_slow=.4):
'''
1st Gen good signal
'''
s1 = -1. * cross.get_stock_mom(rm, stm)
s2 = cross.get_stock_mom(rm, 52).shift(stm)
s3 = cross.get_stock_mom(rm, 52)
good = s3.subtract(s3.median(axis=1), axis=0)
base = 1. * (s1 >= min_fast) * (s3 >= min_slow) * (good >= 0.)
ans = cross.get_step_positions(s1, s2, vol, ns, base, None, holding=0)
return ans