def test(self):
from ppf.core import swap_rate
from ppf.market import curve
from ppf.math import loglinear
from ppf.date_time \
import date \
, shift \
, shift_convention \
, months \
, years \
, basis_act_360 \
, basis_act_365
May = ppf.date_time.May
modified_following = shift_convention.modified_following
t = date(2005, May, 01)
spot = date(2005, May, 03)
maturity = shift(spot + years(10), modified_following)
attributes = {}
attributes["fixed-pay-period"] = 1
attributes["fixed-pay-period-duration"] = years
attributes["fixed-pay-basis"] = basis_act_360
attributes["fixed-pay-holiday-centers"] = None
attributes["fixed-shift-convention"] = modified_following
attributes["float-pay-period"] = 6
attributes["float-pay-period-duration"] = months
attributes["float-pay-basis"] = basis_act_365
attributes["float-pay-holiday-centers"] = None
attributes["float-shift-convention"] = modified_following
attributes["index-basis"] = basis_act_365
attributes["index-holiday-centers"] = None
attributes["index-shift-convention"] = modified_following
#10y swap rate
rate = swap_rate(
attributes
, 0 #flow id
, 0 #reset id
, spot #reset date
, "GBP" #reset ccy
, spot #proj start
, maturity #proj end
, None #fixing
)
times = range(0, 13)#12 years on the curve
P = curve(times, [math.exp(-0.05*T) for T in times], loglinear)
assert(math.fabs(0.0495099316847 - rate.forward(t, P)) < 1.0E-4)
def test_libor(self):
from ppf.date_time \
import date, shift, modified_following, basis_act_360, months
pd = date(2008, 01, 01)
env = ppf.market.environment(pd)
times = numpy.linspace(0, 2, 5)
factors = numpy.array([math.exp(-0.05*t) for t in times])
env.add_curve("zc.disc.eur"
, ppf.market.curve(times, factors, ppf.math.interpolation.loglinear))
expiries, tenors = [0.1, 0.5, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0], [0, 90]
env.add_surface("ve.term.eur.hw"
, ppf.market.surface(expiries, tenors, numpy.zeros((8, 2))))
env.add_constant("cv.mr.eur.hw", 0.0)
rd = date(2008, 07, 01)
libor_obs = \
ppf.core.libor_rate( \
None #attributes
, 0 #flow-id
, 0 #reset-id
, rd #reset-date
, "eur"#reset-currency
, rd #projection-start-date
, shift(rd + months(6), modified_following)#projection-end-date
, basis_act_360#projection-basis
, ppf.core.fixing(False))# fixing (and no spread)
r = ppf.model.hull_white.requestor()
s = ppf.model.hull_white.lattice.state("eur", 11, 3.5)
sx = s.fill(0.25, r, env)
f = ppf.model.hull_white.fill(2.0)
libortT = f.libor(0.25, libor_obs, env, r, sx)
exp = \
[0.0499418283138
,0.0499418283138
,0.0499418283138
,0.0499418283138
,0.0499418283138
,0.0499418283138
,0.0499418283138
,0.0499418283138
,0.0499418283138
,0.0499418283138
,0.0499418283138
]
_assert_seq_close(exp, libortT)
def test_discounted_libor_rollback(self):
from ppf.date_time \
import date, shift, modified_following, basis_act_360, months
pd = date(2008, 01, 01)
env = ppf.market.environment(pd)
times = numpy.linspace(0, 6, 10)
factors = numpy.array([math.exp(-0.05*t) for t in times])
env.add_curve("zc.disc.eur"
, ppf.market.curve(times, factors, ppf.math.interpolation.loglinear))
expiries, tenors = [0.0, 0.5, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 6.0], [0, 90]
values = numpy.zeros((9, 2))
values.fill(0.001)
env.add_surface("ve.term.eur.hw"
, ppf.market.surface(expiries, tenors, values))
env.add_constant("cv.mr.eur.hw", 0.01)
r = ppf.model.hull_white.requestor()
s = ppf.model.hull_white.lattice.state("eur", 41, 4.5)
f = ppf.model.hull_white.fill(5.0)
rd = date(2011, 01, 01)
libor_obs = \
ppf.core.libor_rate( \
None #attributes
, 0 #flow-id
, 0 #reset-id
, rd #reset-date
, "eur"#reset-currency
, rd #projection-start-date
, shift(rd + months(6), modified_following)#projection-end-date
, basis_act_360#projection-basis
, ppf.core.fixing(False))# fixing (and no spread)
t = env.relative_date(libor_obs.proj_start_date())/365.0
T = env.relative_date(libor_obs.proj_end_date())/365.0
sx = s.fill(t, r, env)
libort = f.libor(t, libor_obs, env, r, sx)
ptT = f.numeraire_rebased_bond(t, T, "eur", env, r, sx)
pv = libort*ptT*libor_obs.year_fraction()
roll = ppf.model.hull_white.lattice.rollback("eur")
intermediate_pv = roll.rollback(0.5*t, t, s, r, env, pv)
actual = roll.rollback(0.0, 0.5*t, s, r, env, intermediate_pv).mean()
expected = r.discount_factor(t, "eur", env)-r.discount_factor(T, "eur", env)
_assert_seq_close([expected],[actual],1.0e-6)
