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from contextlib import closing
from itertools import islice
import datetime
import os
import pandas as pd
from quantlib.settings import Settings
from quantlib.time.api import (WeekendsOnly, Date, Period, Days, Schedule, Annual,
Semiannual, today, Actual360, Months, Years,
ModifiedFollowing, Thirty360, Actual365Fixed,
calendar_from_name)
from quantlib.currency.api import USDCurrency, EURCurrency
from quantlib.indexes.ibor_index import IborIndex
from quantlib.termstructures.yields.api import (
PiecewiseYieldCurve, DepositRateHelper, SwapRateHelper, BootstrapTrait, Interpolator)
from quantlib.time.date import pydate_from_qldate
import numpy as np
from quantlib.quotes import SimpleQuote
from db import dbconn, dbengine
from pyisda.curve import YieldCurve, BadDay
import warnings
from db import dbengine, dbconn
def get_curves(currency="USD", date=None):
"""load the prebuilt curve from the database"""
if date:
sql_str = "SELECT curve FROM {}_curves WHERE effective_date=%s".format(currency)
else:
sql_str = "SELECT * FROM {}_curves".format(currency)
with closing(dbconn('serenitasdb')) as conn:
with conn.cursor() as c:
if date:
c.execute(sql_str, (date,))
if c:
curve, = c.fetchone()
return YieldCurve.from_bytes(curve)
else:
c.execute(sql_str)
return {d: YieldCurve.from_bytes(curve)
for d, curve in c}
_USD_curves = get_curves("USD")
_EUR_curves = get_curves("EUR")
def getMarkitIRData(effective_date = datetime.date.today(),
currency = "USD"):
conn = dbconn("serenitasdb")
sql_str = "SELECT * FROM {}_rates WHERE effective_date <= %s " \
"ORDER BY effective_date DESC LIMIT 1".format(currency)
with conn.cursor() as c:
c.execute(sql_str, (effective_date,))
col_names = [col[0] for col in c.description]
r = c.fetchone()
MarkitData = {'effectiveasof': r[0],
'deposits': [(t, r[i]) for i, t in \
enumerate(col_names[1:7], 1) if r[i] is not None],
'swaps': [(t, r[i]) for i, t in enumerate(col_names[7:], 7)]}
return MarkitData
def get_futures_data(date = datetime.date.today()):
futures_file = os.path.join(os.environ['DATA_DIR'], "Yield Curves",
"futures-{0:%Y-%m-%d}.csv".format(date))
with open(futures_file) as fh:
quotes = [float(line.split(",")[1]) for line in fh]
return quotes
def rate_helpers(currency="USD", MarkitData=None):
"""Util function to build a list of RateHelpers
Parameters
----------
currency : str, optional
One of `USD`, `EUR` at the moment, defaults to `USD`
MarkitData : dict, optional
MarkitData for the current evaluation_date
Returns
-------
helpers : list
List of QuantLib RateHelpers
"""
settings = Settings()
if not MarkitData:
MarkitData = getMarkitIRData(pydate_from_qldate(settings.evaluation_date), currency)
if MarkitData['effectiveasof'] != pydate_from_qldate(settings.evaluation_date):
warnings.warn("Yield curve effective date: {0} doesn't " \
"match the evaluation date: {1}".format(
MarkitData['effectiveasof'],
pydate_from_qldate(settings.evaluation_date)),
RuntimeWarning)
settings.evaluation_date = Date.from_datetime(MarkitData['effectiveasof'])
calendar = WeekendsOnly()
if currency == "USD":
isda_ibor = IborIndex("IsdaIbor", Period(3, Months), 2, USDCurrency(), calendar,
ModifiedFollowing, False, Actual360())
fix_freq = Semiannual
elif currency == "EUR":
isda_ibor = IborIndex("IsdaIbor", Period(6, Months), 2, EURCurrency(), calendar,
ModifiedFollowing, False, Actual360())
fix_freq = Annual
# we use SimpleQuotes, rather than just float to make it updateable
deps = [DepositRateHelper(SimpleQuote(q), Period(t), 2, calendar, ModifiedFollowing, False, Actual360())
for t, q in MarkitData['deposits']]
# this matches with bloomberg, but according to Markit, maturity should be unadjusted
swaps = [SwapRateHelper.from_tenor(SimpleQuote(q), Period(t), calendar, fix_freq, ModifiedFollowing,
Thirty360(), isda_ibor) for t, q in MarkitData['swaps']]
return deps + swaps
def get_dates(date, currency="USD"):
"""computes the list of curve dates on a given date"""
if currency == "USD":
month_periods = [1, 2, 3, 6, 12]
year_periods = [2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 20, 25, 30]
calendar = WeekendsOnly()
settle_date = calendar.advance(Date.from_datetime(date), 2, 0)
deposit_dates = [calendar.advance(settle_date, period = Period(m, Months),
convention=ModifiedFollowing) \
for m in month_periods]
swap_dates = [calendar.advance(settle_date, period = Period(y, Years),
convention=ModifiedFollowing) \
for y in year_periods]
dates = deposit_dates + swap_dates
return [pydate_from_qldate(d) for d in dates]
def roll_yc(yc, forward_date):
"""returns the expected forward yield cuve on a forward_date"""
dates = get_dates(forward_date)
dfs = np.array([yc.discount_factor(d, forward_date) for d in dates])
return YieldCurve.from_discount_factors(forward_date, dates, dfs, 'ACT/365F')
def YC(helpers = None, currency="USD", MarkitData=None):
if helpers is None:
helpers = rate_helpers(currency, MarkitData)
calendar = WeekendsOnly()
return PiecewiseYieldCurve(BootstrapTrait.Discount, Interpolator.LogLinear,
0, calendar, helpers, Actual365Fixed())
def jpYC(effective_date, currency="USD", MarkitData=None):
if MarkitData is None:
markit_data = getMarkitIRData(effective_date,
currency)
periods, rates = zip(*markit_data['deposits'])
periods_swaps, rate_swaps = zip(*markit_data['swaps'])
types = 'M'*len(periods) + 'S'*len(periods_swaps)
rates = np.array(rates + rates_swaps)
periods = list(period + periods_swaps)
if currency == "USD":
fixed_period = '6M'
float_period = '3M'
elif currency == 'EUR':
fixed_period = '12M'
float_period = '6M'
return YieldCurve(effective_date, types, periods, rates, 'ACT/360',\
fixed_period, float_period, '30/360', 'ACT/360',
BadDay.MODIFIED)
def ql_to_jp(ql_yc):
"""convert a QuantLib yield curve to a JP's one"""
if ql_yc._trait == BootstrapTrait.Discount:
dfs = np.array(ql_yc.data[1:])
dates = [pydate_from_qldate(d) for d in ql_yc.dates[1:]]
trade_date = pydate_from_qldate(ql_yc.dates[0])
return YieldCurve.from_discount_factors(trade_date, dates, dfs, 'ACT/365F')
else:
raise RuntimeErrror('QuantLib curve needs to use Discount trait')
def build_curves(currency="USD"):
settings = Settings()
calendar = WeekendsOnly()
if currency == "USD":
isda_ibor = IborIndex("IsdaIbor", Period(3, Months), 2, USDCurrency(), calendar,
ModifiedFollowing, False, Actual360())
fix_freq = Semiannual
elif currency == "EUR":
isda_ibor = IborIndex("IsdaIbor", Period(6, Months), 2, EURCurrency(), calendar,
ModifiedFollowing, False, Actual360())
fix_freq = Annual
engine = dbengine('serenitasdb')
rates = pd.read_sql_table('{}_rates'.format(currency.lower()), engine, index_col='effective_date')
quotes = [SimpleQuote() for c in rates.columns]
gen = zip(quotes, rates.columns)
deps = [DepositRateHelper(q, Period(t), 2, calendar, ModifiedFollowing,
False, Actual360()) for q, t in islice(gen, 6)]
swaps = [SwapRateHelper.from_tenor(q, Period(t), calendar,
fix_freq, ModifiedFollowing,
Thirty360(), isda_ibor) for q, t in gen]
sql_str = "INSERT INTO {}_curves VALUES(%s, %s) ON CONFLICT DO NOTHING".format(currency)
conn = dbconn('serenitasdb')
for effective_date, curve_data in rates.iterrows():
print(effective_date)
settings.evaluation_date = Date.from_datetime(effective_date)
for q, val in zip(quotes, curve_data):
q.value = val
valid_deps = [d for d in deps if not np.isnan(d.quote)]
valid_swaps = [s for s in swaps if not np.isnan(s.quote)]
ql_yc = PiecewiseYieldCurve(BootstrapTrait.Discount, Interpolator.LogLinear,
0, calendar, valid_deps + valid_swaps, Actual365Fixed())
jp_yc = ql_to_jp(ql_yc)
with conn.cursor() as c:
c.execute(sql_str, (effective_date, jp_yc.__getstate__()))
conn.commit()
if __name__=="__main__":
#evaluation_date = Date(29, 4, 2014)
Settings.instance().evaluation_date = today()
import matplotlib.pyplot as plt
ts = YC()
cal = calendar_from_name('USA')
p1 = Period('1Mo')
p2 = Period('2Mo')
p3 = Period('3Mo')
p6 = Period('6Mo')
p12 = Period('12Mo')
sched = Schedule(ts.reference_date, ts.reference_date+Period('5Yr'), Period('3Mo'), cal)
days = [pydate_from_qldate(d) for d in sched]
f3 = [ts.forward_rate(d, d+p3, Actual360(), 0).rate for d in sched]
f6 = [ts.forward_rate(d, d+p6, Actual360(), 0).rate for d in sched]
f2 = [ts.forward_rate(d, d+p2, Actual360(), 0).rate for d in sched]
plt.plot(days, f2, days, f3, days, f6)
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