diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/analytics/tranche_functions.py | 11 | ||||
| -rw-r--r-- | python/tests/test_dates.py | 14 |
2 files changed, 17 insertions, 8 deletions
diff --git a/python/analytics/tranche_functions.py b/python/analytics/tranche_functions.py index ab975a55..3355a887 100644 --- a/python/analytics/tranche_functions.py +++ b/python/analytics/tranche_functions.py @@ -30,9 +30,7 @@ def wrapped_ndpointer(*args, **kwargs): return type(base.__name__, (base,), {"from_param": classmethod(from_param)}) -libloss = np.ctypeslib.load_library( - "lossdistrib", Path(__file__).parent -) +libloss = np.ctypeslib.load_library("lossdistrib", Path(__file__).parent) libloss.fitprob.restype = None libloss.fitprob.argtypes = [ @@ -455,9 +453,9 @@ def credit_schedule(tradedate, coupon, yc, enddate=None, tenor=None, rule=CDS201 DC = Actual360() start_date = tradedate + 1 sched = Schedule.from_rule( - start_date, enddate, Period("3M"), cal, ModifiedFollowing, Unadjusted, rule + tradedate, enddate, Period("3M"), cal, ModifiedFollowing, Unadjusted, rule ) - payment_dates = [pydate_from_qldate(cal.adjust(d)) for d in sched[1:]] + payment_dates = [pydate_from_qldate(cal.adjust(d)) for d in sched if d > start_date] df = [yc.discount_factor(d) for d in payment_dates] coupons = [ DC.year_fraction(d1, d2) * coupon for d1, d2 in zip(sched[:-2], sched[1:-1]) @@ -490,9 +488,8 @@ def credit_schedule_pyisda( stub = "f/l" else: stub = "f/s" - print(stub) if rule is CDS2015: - start_date = previous_twentieth(start_date) + start_date = previous_twentieth(pydate_from_qldate(tradedate)) fl = FeeLeg(start_date, pydate_from_qldate(enddate), True, 1.0, coupon, stub=stub) df = pd.DataFrame({"coupons": [t[1] for t in fl.cashflows], **fl.inspect()}) df["df"] = [yc.discount_factor(d) for d in df.pay_dates] diff --git a/python/tests/test_dates.py b/python/tests/test_dates.py index 0a4078ba..054a0ee1 100644 --- a/python/tests/test_dates.py +++ b/python/tests/test_dates.py @@ -6,7 +6,7 @@ import sys sys.path.append("..") from analytics.utils import roll_date -from analytics.tranche_functions import cds_accrued +from analytics.tranche_functions import cds_accrued, credit_schedule from pyisda.date import ( roll_date as roll_date_c, cds_accrued as cds_accrued_c, @@ -15,6 +15,7 @@ from pyisda.date import ( TDate_to_pydate, ) from dates import days_accrued +from yieldcurve import get_curve class TestStartDate(unittest.TestCase): @@ -173,5 +174,16 @@ class TestDaysAccrued(unittest.TestCase): self.assertEqual(days_accrued(date), days) +class TestCdsSchedule(unittest.TestCase): + def setUp(self): + self.trade_date = datetime.date(2020, 6, 19) + self.yc = get_curve(self.trade_date, "USD") + + def test_credit_schedule(self): + """ tests when IMM date falls on a week-end""" + df = credit_schedule(self.trade_date, 1.0, self.yc, datetime.date(2022, 12, 20)) + self.assertEqual(df.index[0], pd.Timestamp("2020-06-22")) + + if __name__ == "__main__": unittest.main() |