1 files changed, 15 insertions, 16 deletions
diff --git a/python/tranche_functions.py b/python/tranche_functions.py
index 28481130..a92044e3 100644
--- a/python/tranche_functions.py
+++ b/python/tranche_functions.py
@@ -1,8 +1,8 @@
 import numpy as np
 from ctypes import *
 from numpy.ctypeslib import ndpointer
-from quantlib.time.schedule import Schedule, CDS
-from quantlib.time.api import Actual360, Period, UnitedStates, Following, today
+from quantlib.time.schedule import Schedule, CDS2015
+from quantlib.time.api import Actual360, Period, WeekendsOnly, ModifiedFollowing, Unadjusted, today
 from quantlib.util.converter import qldate_to_pydate, pydate_to_qldate
 import pandas as pd
 from scipy.special import h_roots
@@ -284,33 +284,32 @@ def tranche_pl(L, cs, K1, K2, scaled=False):
 def tranche_pv(L, R, cs, K1, K2):
     return tranche_pl(L, cs, K1, K2) + tranche_cl(L, R, cs, K2, K2)
 
-def creditSchedule(tradedate, tenor, coupon, yc, enddate = None):
+def credit_schedule(tradedate, tenor, coupon, yc, enddate=None):
     tradedate = pydate_to_qldate(tradedate)
-    start = tradedate - Period('4Mo')
-    enddate = pydate_to_qldate(enddate)
     if enddate is None:
         enddate = tradedate + Period(tenor)
-    cal = UnitedStates()
+    else:
+        enddate = pydate_to_qldate(enddate)
+    cal = WeekendsOnly()
     DC = Actual360()
-    sched = Schedule(start, enddate, Period('3Mo'), cal, date_generation_rule=CDS)
-    prevpaydate = sched.previous_date(tradedate)
-    sched = [d for d in sched if d>=prevpaydate]
-    df = [yc.discount(d) for d in sched if d > tradedate]
-
-    dates = pd.to_datetime([str(d) for d in sched if d > tradedate], "%m/%d/%Y")
-    coupons = np.diff([DC.year_fraction(prevpaydate, d) * coupon for d in sched])
+    sched = Schedule.from_rule(tradedate, enddate, Period('3M'), cal,
+                               ModifiedFollowing, Unadjusted, CDS2015)
+    dates = sched.to_npdates()
+    pydates = dates.astype('O')
+    df = [yc.discount_factor(d) for d in pydates if d > tradedate]
+    coupons = [DC.year_fraction(d1, d2) * coupon for d1, d2 in zip(sched[:-2], sched[1:-1])]
+    coupons.append(Actual360(True).year_fraction(sched[-2], sched[-1]) * coupon)
 
-    return pd.DataFrame({"df":df, "coupons":coupons}, dates)
+    return pydates[0], pd.DataFrame({"df": df, "coupons": coupons}, dates[1:])
 
 def cdsAccrued(tradedate, coupon):
     tradedate = pydate_to_qldate(tradedate)
-    start = tradedate - Period('3Mo')
     end = tradedate + Period('3Mo')
 
     start_protection = tradedate + 1
     DC = Actual360()
     cal = UnitedStates()
-    sched = Schedule(start, end, Period('3Mo'), cal, date_generation_rule=CDS)
+    sched = Schedule(start, end, Period('3Mo'), cal, date_generation_rule=CDS2015)
     prevpaydate = sched.previous_date(tradedate)
     return DC.year_fraction(prevpaydate, start_protection) * coupon