diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/analytics/tranche_basket.py | 47 |
1 files changed, 38 insertions, 9 deletions
diff --git a/python/analytics/tranche_basket.py b/python/analytics/tranche_basket.py index 6681b53f..c97598d0 100644 --- a/python/analytics/tranche_basket.py +++ b/python/analytics/tranche_basket.py @@ -5,6 +5,7 @@ from .tranche_functions import ( from .index_data import get_tranche_quotes from cityhash import CityHash64 from collections import namedtuple +from db import dbconn from copy import deepcopy from lru import LRU from pyisda.date import cds_accrued @@ -15,7 +16,10 @@ import datetime import pandas as pd import numpy as np + _cache = LRU(64) + + def BCloss_recov_dist_cached(default_prob, weights, recovery_rates, @@ -33,6 +37,8 @@ def BCloss_recov_dist_cached(default_prob, Z, w, Ngrid) return _cache[h] + + class DualCorrTranche(BasketIndex): def __init__(self, index_type: str, series: int, tenor: str, *, attach: float, detach: float, corr_attach: float, @@ -53,19 +59,39 @@ class DualCorrTranche(BasketIndex): self._direction = -1. if notional > 0 else 1. self.start_date, self.cs = credit_schedule(value_date, self.tenor[:-1], 1., self.yc) - self.default_prob, _ = super().survival_matrix(self.cs.index.values.astype('M8[D]'). - view('int') + 134774) + self.default_prob = 1 - super().survival_matrix(self.cs.index.values.astype('M8[D]'). + view('int') + 134774)[0] self._accrued = cds_accrued(value_date, self.tranche_running * 1e-4) value_date = property(BasketIndex.value_date.__get__) + @classmethod + def from_tradeid(cls, trade_id): + with dbconn('dawndb') as conn: + with conn.cursor() as c: + c.execute("SELECT * FROM cds LEFT JOIN index_desc " + "ON security_id = redindexcode AND " + "cds.maturity = index_desc.maturity " + "WHERE id=%s", (trade_id,)) + rec = c.fetchone() + instance = cls(rec['index'], rec['series'], rec['tenor'], + attach=rec['attach'], + detach=rec['detach'], + corr_attach=np.nan, + corr_detach=np.nan, + notional=rec['notional'], + tranche_running=rec['coupon'], + value_date=rec['trade_date']) + instance.direction = rec['protection'] + return instance + @value_date.setter def value_date(self, d: pd.Timestamp): BasketIndex.value_date.__set__(self, d) self.start_date, self.cs = credit_schedule(d, self.tenor[:-1], 1., self.yc) - self.default_prob, _ = super().survival_matrix(self.cs.index.values.astype('M8[D]'). - view('int') + 134774) + self.default_prob= 1 - super().survival_matrix(self.cs.index.values.astype('M8[D]'). + view('int') + 134774)[0] self._accrued = cds_accrued(d, self.tranche_running * 1e-4) def tranche_legs(self, K, rho): @@ -136,6 +162,8 @@ class DualCorrTranche(BasketIndex): def shock(self, params=['pnl'], *, corr_shock, kwargs): pass + + class TrancheBasket(BasketIndex): def __init__(self, index_type: str, series: int, tenor: str, *, value_date: pd.Timestamp=pd.Timestamp.today().normalize()): @@ -226,7 +254,8 @@ class TrancheBasket(BasketIndex): @property def default_prob(self): - sm, tickers = super().survival_matrix(self.cs.index.values.astype('M8[D]').view('int') + 134774) + sm, tickers = super().survival_matrix(self.cs.index.values. + astype('M8[D]').view('int') + 134774) return pd.DataFrame(1 - sm, index=tickers, columns=self.cs.index) def tranche_legs(self, K, rho, complement=False, shortened=0): @@ -238,7 +267,7 @@ class TrancheBasket(BasketIndex): raise ValueError("rho needs to be a real number between 0. and 1.") else: if shortened > 0: - default_prob = self.default_prob.values[:,:-shortened] + default_prob = self.default_prob.values[:, :-shortened] cs = self.cs[:-shortened] else: default_prob = self.default_prob.values @@ -302,7 +331,7 @@ class TrancheBasket(BasketIndex): def expected_loss(self, discounted=True, shortened=0): if shortened > 0: - DP = self.default_prob.values[:,:-shortened] + DP = self.default_prob.values[:, :-shortened] df = self.cs.df.values[:-shortened] else: DP = self.default_prob.values @@ -318,7 +347,7 @@ class TrancheBasket(BasketIndex): if rho is None: rho = expit(self._skew(logit(K))) if shortened > 0: - DP = self.default_prob.values[:,:-shortened] + DP = self.default_prob.values[:, :-shortened] df = self.cs.df.values[:-shortened] else: DP = self.default_prob.values @@ -453,7 +482,7 @@ class TrancheBasket(BasketIndex): def aux2(x, index1, index2, K2, shortened): newrho = expit(index1._skew(logit(x))) - assert newrho >= 0 and newrho <=1, "Something went wrong" + assert newrho >= 0 and newrho <= 1, "Something went wrong" return np.log(self.probability_trunc(x, newrho)) - \ np.log(index2.probability_trunc(K2, newrho, shortened)) |