diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/analytics/tranche_basket.py | 44 |
1 files changed, 27 insertions, 17 deletions
diff --git a/python/analytics/tranche_basket.py b/python/analytics/tranche_basket.py index b75559ab..b7039d1c 100644 --- a/python/analytics/tranche_basket.py +++ b/python/analytics/tranche_basket.py @@ -5,6 +5,8 @@ from .tranche_functions import ( GHquad, BCloss_recov_dist, BCloss_recov_trunc, + CDS2015, + OldCDS, tranche_cl, tranche_pl, tranche_pl_trunc, @@ -19,6 +21,7 @@ from copy import deepcopy from dateutil.relativedelta import relativedelta from lru import LRU from math import log +from pandas.tseries.offsets import Day from pyisda.date import cds_accrued from scipy.optimize import brentq from scipy.interpolate import CubicSpline, PchipInterpolator @@ -162,10 +165,15 @@ class DualCorrTranche: self.rho = [corr_attach, corr_detach] self.tranche_running = tranche_running self.notional = notional + if index_type == "BS": + rule = OldCDS + self._accrued = 0.0 + else: + rule = CDS2015 + self._accrued = cds_accrued(value_date, tranche_running * 1e-4) self.cs = credit_schedule( - value_date, None, 1.0, self._index.yc, self._index.maturities[0] + value_date, 1.0, self._index.yc, self._index.maturities[0], rule=rule ) - self._accrued = cds_accrued(value_date, tranche_running * 1e-4) self.use_trunc = use_trunc self._tranche_id = None self._ignore_hash = set(["_Z", "_w", "cs", "_cache", "_Legs", "_ignore_hash"]) @@ -177,7 +185,14 @@ class DualCorrTranche: @maturity.setter def maturity(self, m): self._index.maturities = [m] - self.cs = credit_schedule(self.value_date, None, 1.0, self._index.yc, m) + start_date = pd.Timestamp(self.value_date) + Day() + self.cs = credit_schedule( + start_date, + 1.0, + self._index.yc, + m, + rule=OldCDS if self.index_type == "BS" else CDS2015, + ) def _default_prob(self, epsilon=0.0): return ( @@ -241,10 +256,14 @@ class DualCorrTranche: @value_date.setter def value_date(self, d: pd.Timestamp): self._index.value_date = d - self.cs = credit_schedule( - d, None, 1.0, self._index.yc, self._index.maturities[0] + start_date = pd.Timestamp(d) + Day() + self.cs = self.cs[self.cs.index > start_date] + self._accrued = ( + (start_date - self.cs.start_dates[0]).days + / 360 + * self.tranche_running + * 1e-4 ) - self._accrued = cds_accrued(d, self.tranche_running * 1e-4) if ( self._index.index_type == "XO" and self._index.series == 22 @@ -329,13 +348,6 @@ class DualCorrTranche: def pv(self): pl, cl = self._pv() _pv = -self.notional * self.tranche_factor * (pl + cl) - if self.index_type == "BS": - if self.value_date < next_twentieth(self._trade_date): - stub = ( - cds_accrued(self._trade_date, self.tranche_running * 1e-4) - * self.notional - ) - _pv -= stub return _pv @property @@ -733,9 +745,7 @@ class TrancheBasket(BasketIndex): self._Ngrid = 301 self._Z, self._w = GHquad(self._Ngh) self.rho = np.full(self.K.size, np.nan) - self.cs = credit_schedule( - value_date, self.tenor[:-1], 1, self.yc, self.maturity - ) + self.cs = credit_schedule(value_date, 1.0, self.yc, self.maturity) def _get_tranche_quotes(self, value_date): if isinstance(value_date, datetime.datetime): @@ -788,7 +798,7 @@ class TrancheBasket(BasketIndex): @value_date.setter def value_date(self, d: pd.Timestamp): BasketIndex.value_date.__set__(self, d) - self.cs = credit_schedule(d, self.tenor[:-1], 1, self.yc, self.maturity) + self.cs = credit_schedule(d, 1.0, self.yc, self.maturity) self.K = adjust_attachments(self.K_orig, self.cumloss, self.factor) try: self._get_tranche_quotes(d) |