def zbt_libor_yield(instruments,
yields,
pricing_date,
basis='Actual/Actual (Bond)',
compounding_freq='Continuous',
maturity_dates=None):
"""
Bootstrap a zero-coupon curve from libor rates and swap yields
Args:
instruments: list of instruments, of the form Libor?M for Libor rates
and Swap?Y for swap rates
yields: market rates
pricing_date: the date where market data is observed. Settlement
is by default 2 days after pricing_date
Optional:
compounding_frequency: ... of zero-coupon rates. By default:
'Continuous'
Returns:
zero_rate: zero-coupon rate
maturity_date: ... of corresponding rate
"""
calendar = TARGET()
settings = Settings()
# must be a business day
eval_date = calendar.adjust(pydate_to_qldate(pricing_date))
settings.evaluation_date = eval_date
rates = dict(zip(instruments, yields))
ts = make_term_structure(rates, pricing_date)
cnt = DayCounter.from_name(basis)
if maturity_dates is None:
# schedule of maturity dates from settlement date to last date on
# the term structure
s = Schedule(effective_date=ts.reference_date,
termination_date=ts.max_date,
tenor=Period(1, Months),
calendar=TARGET())
maturity_dates = [qldate_to_pydate(dt) for dt in s.dates()]
cp_freq = Compounding[compounding_freq]
zc = [
ts.zero_rate(pydate_to_qldate(dt),
day_counter=cnt,
compounding=cp_freq).rate for dt in maturity_dates
]
return (maturity_dates, zc)
def zero_rate(term_structure, days, dt_settlement, calendar=TARGET()):
"""
Compute zero-coupon rate, continuous ACT/365 from settlement date to given
maturity expressed in calendar days
Return
- array of maturity dates
- array of zero-coupon rates
"""
dtMat = [calendar.advance(pydate_to_qldate(dt_settlement), d, Days)
for d in days]
df = np.array([term_structure.discount(dt) for dt in dtMat])
dtMat = [qldate_to_pydate(dt) for dt in dtMat]
dtToday = qldate_to_pydate(dt_settlement)
dt = np.array([(d - dtToday).days / 365.0 for d in dtMat])
zc = -np.log(df) / dt
return (dtMat, zc)
def zero_rate(term_structure, days, dt_settlement, calendar=TARGET()):
"""
Compute zero-coupon rate, continuous ACT/365 from settlement date to given
maturity expressed in calendar days
Return
- array of maturity dates
- array of zero-coupon rates
"""
dtMat = [calendar.advance(pydate_to_qldate(dt_settlement), d, Days)
for d in days]
df = np.array([term_structure.discount(dt) for dt in dtMat])
dtMat = [qldate_to_pydate(dt) for dt in dtMat]
dtToday = qldate_to_pydate(dt_settlement)
dt = np.array([(d - dtToday).days / 365.0 for d in dtMat])
zc = -np.log(df) / dt
return (dtMat, zc)
def zbt_libor_yield(instruments, yields, pricing_date,
basis='Actual/Actual (Bond)',
compounding_freq='Continuous',
maturity_dates=None):
"""
Bootstrap a zero-coupon curve from libor rates and swap yields
Args:
insruments: list of instruments, of the form Libor?M for Libor rates
and Swap?Y for swap rates
yields: market rates
pricing_date: the date where market data is observed. Settlement
is by default 2 days after pricing_date
Optional:
compounding_frequency: ... of zero-coupon rates. By default:
'Continuous'
Returns:
zero_rate: zero-coupon rate
maturity_date: ... of corresponding rate
"""
calendar = TARGET()
settings = Settings()
# must be a business day
eval_date = calendar.adjust(pydate_to_qldate(pricing_date))
settings.evaluation_date = eval_date
rates = dict(zip(instruments, yields))
ts = make_term_structure(rates, pricing_date)
cnt = DayCounter.from_name(basis)
if maturity_dates is None:
# schedule of maturity dates from settlement date to last date on
# the term structure
s = Schedule(effective_date=ts.reference_date,
termination_date=ts.max_date,
tenor=Period(1, Months),
calendar=TARGET())
maturity_dates = [qldate_to_pydate(dt) for dt in s.dates()]
cp_freq = compounding_from_name(compounding_freq)
zc = [ts.zero_rate(date=pydate_to_qldate(dt),
day_counter=cnt,
compounding=cp_freq).rate for dt in maturity_dates]
return (maturity_dates, zc)
