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Diffstat (limited to 'python/analytics/index.py')
| -rw-r--r-- | python/analytics/index.py | 313 |
1 files changed, 313 insertions, 0 deletions
diff --git a/python/analytics/index.py b/python/analytics/index.py new file mode 100644 index 00000000..85ba3474 --- /dev/null +++ b/python/analytics/index.py @@ -0,0 +1,313 @@ +import array +import datetime +import math +import pandas as pd + +from pyisda.legs import ContingentLeg, FeeLeg +from quantlib.settings import Settings +from quantlib.time.api import ( + Date, Schedule, WeekendsOnly, CDS, Following, + Unadjusted, Period, pydate_from_qldate ) +from termcolor import colored +from pandas.tseries.offsets import BDay +from dates import prev_immdate +from db import dbconn +from psycopg2 import DataError +from pyisda.curve import SpreadCurve +from yieldcurve import YC, ql_to_jp, roll_yc, rate_helpers +from quantlib.time.api import Actual365Fixed + +serenitasdb = dbconn('serenitasdb') + +class Index(): + """ minimal class to represent a credit index """ + def __init__(self, start_date, end_date, recovery, fixed_rate, + notional = 10e6): + """ + start_date : :class:`datetime.date` + index start_date (Could be issue date, or last imm date) + end_date : :class:`datetime.date` + index last date + recovery : + recovery rate (between 0 and 1) + fixed_rate : + fixed coupon (in bps) + """ + self.fixed_rate = fixed_rate + self.notional = notional + self._sched = Schedule(Date.from_datetime(start_date), + Date.from_datetime(end_date), + Period("3M"), + WeekendsOnly(), + Following, + Unadjusted, + CDS) + self._start_date = start_date + self._end_date = end_date + self.recovery = recovery + + self._fee_leg = FeeLeg(self._start_date, end_date, True, 1, 1) + self._default_leg = ContingentLeg(self._start_date, end_date, 1) + self._trade_date = None + self._yc = None + self._risky_annuity = None + self._spread = None + self.name = None + + @property + def start_date(self): + return self._start_date + + @property + def end_date(self): + return self._end_date + + @start_date.setter + def start_date(self, d): + self._fee_leg = FeeLeg(d, self.end_date, True, 1, 1) + self._default_leg = ContingentLeg(d, self.end_date, 1) + self._start_date = d + self._sched = Schedule(Date.from_datetime(d), + Date.from_datetime(self.end_date), + Period("3M"), + WeekendsOnly(), + Following, + Unadjusted, + CDS) + + @end_date.setter + def end_date(self, d): + self._fee_leg = FeeLeg(self.start_date, d, True, 1, 1) + self._default_leg = ContingentLeg(self.start_date, d, 1) + self._end_date = d + self._sched = Schedule(self.start_date, + d, + Period("3M"), + WeekendsOnly(), + Following, + Unadjusted, + CDS) + + def survival_probability(self, d): + if d > self.trade_date: + return 1 + else: + return math.exp( - self.flat_hazard * (d - self.trade_date)/365) + + def forward_pv(self, exercise_date): + """This is default adjusted forward price at time exercise_date""" + step_in_date = exercise_date + datetime.timedelta(days=1) + a = self._fee_leg.pv(self.trade_date, step_in_date, self._value_date, + self._yc, self._sc, False) + Delta = self._fee_leg.accrued(step_in_date) + value_date = (pd.Timestamp(exercise_date) + 3* BDay()).date() + df = self._yc.discount_factor(value_date) + q = self.survival_probability(exercise_date) + clean_forward_annuity = a - Delta * df * q + dl_pv = self._default_leg.pv( + self.trade_date, step_in_date, self._value_date, + self._yc, self._sc, self.recovery) + forward_price = self.notional * (dl_pv - clean_forward_annuity * self.fixed_rate*1e-4) + fep = self.notional * (1 - self.recovery) * (1 - q) + return forward_price * self._yc.discount_factor(self._value_date) / df + fep + + @property + def spread(self): + return self._spread * 1e4 + + def _update(self): + self._sc = SpreadCurve(self.trade_date, self._yc, self.start_date, + self._step_in_date, self._value_date, + [self.end_date], array.array('d', [self._spread]), + self.recovery) + self._risky_annuity = self._fee_leg.pv(self.trade_date, self._step_in_date, + self._value_date, self._yc, + self._sc, False) + self._dl_pv = self._default_leg.pv( + self.trade_date, self._step_in_date, self._value_date, + self._yc, self._sc, self.recovery) + self._pv = self._dl_pv - self._risky_annuity * self.fixed_rate * 1e-4 + self._clean_pv = self._pv + self._accrued * self.fixed_rate * 1e-4 + self._price = 100 * (1 - self._clean_pv) + + @spread.setter + def spread(self, s: float): + """ s: spread in bps """ + self._spread = s * 1e-4 + self._update() + + @property + def flat_hazard(self): + sc_data = self._sc.inspect()['data'] + ## conversion to continuous compounding + return math.log(1 + sc_data[0][1]) + + @property + def pv(self): + return self.notional * self._pv + + @property + def accrued(self): + return - self.notional * self._accrued * self.fixed_rate * 1e-4 + + @property + def days_accrued(self): + return int(self._accrued * 360) + + @property + def clean_pv(self): + return self.notional * self._clean_pv + + @property + def price(self): + return self._price + + @price.setter + def price(self, val): + pass + + @property + def DV01(self): + old_pv = self.pv + self.spread += 1 + dv01 = self.pv - old_pv + self.spread -= 1 + return dv01 + + @property + def IRDV01(self): + old_pv = self.pv + old_yc = self._yc + for rh in self._helpers: + rh.quote += 1e-4 + self._yc = ql_to_jp(self._ql_yc) + self._update() ## to force recomputation + new_pv = self.pv + for r in self._helpers: + r.quote -= 1e-4 + self._yc = old_yc + self._update() + return new_pv - old_pv + + @property + def rec_risk(self): + old_pv = self.pv + old_recovery = self.recovery + self.recovery = old_recovery - 0.01 + self._update() + pv_minus = self.pv + self.recovery = old_recovery + 0.01 + self._update() + pv_plus = self.pv + self.recovery = old_recovery + self._update() + return (pv_plus - pv_minus)/2 + + @property + def jump_to_default(self): + return self.notional * (1 - self.recovery) - self.clean_pv + + @property + def risky_annuity(self): + return self._risky_annuity - self._accrued + + @property + def trade_date(self): + if self._trade_date is None: + raise AttributeError('Please set trade_date first') + else: + return self._trade_date + + @trade_date.setter + def trade_date(self, d): + settings = Settings() + settings.evaluation_date = Date.from_datetime(d) + self.start_date = pydate_from_qldate( + self._sched.previous_date(settings.evaluation_date)) + self._helpers = rate_helpers(self.currency) + self._ql_yc = YC(self._helpers) + self._yc = ql_to_jp(self._ql_yc) + self._trade_date = d + self._step_in_date = self.trade_date + datetime.timedelta(days=1) + self._accrued = self._fee_leg.accrued(self._step_in_date) + self._value_date = (pd.Timestamp(self._trade_date) + 3* BDay()).date() + if self._spread is not None: + self._update() + + @classmethod + def from_name(cls, index, series, tenor, trade_date = datetime.date.today(), + notional = 10e6): + try: + with serenitasdb.cursor() as c: + c.execute("SELECT maturity, coupon FROM index_maturity " \ + "WHERE index=%s AND series=%s AND tenor = %s", + (index.upper(), series, tenor)) + maturity, coupon = next(c) + except DataError as e: + raise + else: + recovery = 0.4 if index.lower() == "ig" else 0.3 + instance = cls(trade_date, maturity, recovery, coupon) + instance.name = "MARKIT CDX.NA.{}.{} {:%m/%y} ".format( + index.upper(), + series, + maturity) + if index.upper() in ["IG", "HY"]: + instance.currency = "USD" + else: + instance.currency = "EUR" + instance.notional = notional + instance.trade_date = trade_date + return instance + + def __repr__(self): + if self.days_accrued > 1: + accrued_str = "Accrued ({} Days)".format(self.days_accrued) + else: + accrued_str = "Accrued ({} Day)".format(self.days_accrued) + s = ["{:<20}\t{:>15}".format("CDS Index", colored(self.name, attrs = ['bold'])), + "", + "{:<20}\t{:>15}".format("Trade Date", ('{:%m/%d/%y}'. + format(self.trade_date))), + "{:<20}\t{:>15.2f}\t\t{:<20}\t{:>10,.2f}".format("Trd Sprd (bp)", + self.spread, + "Coupon (bp)", + self.fixed_rate), + "{:<20}\t{:>15.2f}\t\t{:<20}\t{:>10}".format("1st Accr Start", + self.spread, + "Payment Freq", + "Quarterly"), + "{:<20}\t{:>15}\t\t{:<20}\t{:>10.2f}".format("Maturity Date", + ('{:%m/%d/%y}'. + format(self.end_date)), + "Rec Rate", + self.recovery), + "{:<20}\t{:>15}\t\t{:<20}\t{:>10}".format("Bus Day Adj", + "Following", + "Day Count", + "ACT/360"), + "", + colored("Calculator", attrs = ['bold']), + "{:<20}\t{:>15}".format("Valuation Date", ('{:%m/%d/%y}'. + format(self.trade_date))), + "{:<20}\t{:>15}".format("Cash Settled On", ('{:%m/%d/%y}'. + format(self._value_date))), + "", + "{:<20}\t{:>15.8f}\t\t{:<20}\t{:>10,.2f}".format("Price", + self.price, + "Spread DV01", + self.DV01), + "{:<20}\t{:>15,.0f}\t\t{:<20}\t{:>10,.2f}".format("Principal", + self.clean_pv, + "IR DV01", + self.IRDV01), + "{:<20}\t{:>15,.0f}\t\t{:<20}\t{:>10,.2f}".format(accrued_str, + self.accrued, + "Rec Risk (1%)", + self.rec_risk), + "{:<20}\t{:>15,.0f}\t\t{:<20}\t{:>10,.0f}".format("Cash Amount", + self.pv, + "Def Exposure", + self.jump_to_default) + ] + return "\n".join(s) |