def setUp(self):
self.settings = Settings()
self.calendar = NullCalendar()
self.todays_date = Date(15, May, 1998)
self.settlement_date = Date(17, May, 1998)
self.settings.evaluation_date = self.todays_date
# options parameters
self.dividend_yield = 0.00
self.risk_free_rate = 0.06
self.volatility = 0.25
self.spot = SimpleQuote(100)
self.maturity = Date(17, May, 1999)
self.daycounter = Actual365Fixed()
self.tol = 1e-2
# bootstrap the yield/dividend/vol curves
dates = [self.settlement_date] + \
[self.settlement_date + Period(i + 1, Years)
for i in range(40)]
rates = [0.01] + \
[0.01 + 0.0002 * np.exp(np.sin(i / 4.0)) for i in range(40)]
divRates = [0.02] + \
[0.02 + 0.0001 * np.exp(np.sin(i / 5.0)) for i in range(40)]
self.r_ts = ZeroCurve(dates, rates, self.daycounter)
self.q_ts = ZeroCurve(dates, divRates, self.daycounter)
self.vol_ts = BlackConstantVol(
self.settlement_date,
self.calendar,
self.volatility,
self.daycounter
)
self.black_scholes_merton_process = BlackScholesMertonProcess(
self.spot,
self.q_ts,
self.r_ts,
self.vol_ts
)
self.dates = dates
def setUp(self):
self.calendar = TARGET()
self.today = Date(9, 6, 2009)
settlement_date = self.calendar.advance(self.today, 2, Days)
Settings().evaluation_date = self.today
rates = [0.035, 0.035, 0.033, 0.034, 0.034, 0.036, 0.037, 0.039, 0.04]
ts = [13, 41, 75, 165, 256, 345, 524, 703]
dates = [settlement_date] + [self.calendar.advance(self.today, d, Days) for d in ts]
self.day_counter = Actual360()
self.term_structure = ZeroCurve(dates, rates, self.day_counter)
self.spreads = [SimpleQuote(0.02), SimpleQuote(0.03)]
self.spread_dates = [self.calendar.advance(self.today, 8, Months),
self.calendar.advance(self.today, 15, Months)]
self.spreaded_term_structure = PiecewiseZeroSpreadedTermStructure(
self.term_structure,
self.spreads,
self.spread_dates)
self.spreaded_term_structure.extrapolation = True
def test_zanette(self):
"""
From paper by A. Zanette et al.
"""
dc = Actual365Fixed()
todays_date = today()
settings = Settings()
settings.evaluation_date = todays_date
# constant yield and div curves
dates = [todays_date + Period(i, Years) for i in range(3)]
rates = [0.04 for i in range(3)]
divRates = [0.03 for i in range(3)]
r_ts = ZeroCurve(dates, rates, dc)
q_ts = ZeroCurve(dates, divRates, dc)
s0 = SimpleQuote(100)
# Heston model
v0 = .1
kappa_v = 2
theta_v = 0.1
sigma_v = 0.3
rho_sv = -0.5
hestonProcess = HestonProcess(risk_free_rate_ts=r_ts,
dividend_ts=q_ts,
s0=s0,
v0=v0,
kappa=kappa_v,
theta=theta_v,
sigma=sigma_v,
rho=rho_sv)
hestonModel = HestonModel(hestonProcess)
# Hull-White
kappa_r = 1
sigma_r = .2
hullWhiteProcess = HullWhiteProcess(r_ts, a=kappa_r, sigma=sigma_r)
strike = 100
maturity = 1
type = Call
maturity_date = todays_date + Period(maturity, Years)
exercise = EuropeanExercise(maturity_date)
payoff = PlainVanillaPayoff(type, strike)
option = VanillaOption(payoff, exercise)
def price_cal(rho, tGrid):
fd_hestonHwEngine = FdHestonHullWhiteVanillaEngine(
hestonModel, hullWhiteProcess, rho, tGrid, 100, 40, 20, 0,
True, FdmSchemeDesc.Hundsdorfer())
option.set_pricing_engine(fd_hestonHwEngine)
return option.npv
calc_price = []
for rho in [-0.5, 0, .5]:
for tGrid in [50, 100, 150, 200]:
tmp = price_cal(rho, tGrid)
print("rho (S,r): %f Ns: %d Price: %f" % (rho, tGrid, tmp))
calc_price.append(tmp)
expected_price = [
11.38,
] * 4 + [
12.79,
] * 4 + [
14.06,
] * 4
np.testing.assert_almost_equal(calc_price, expected_price, 2)
def test_compare_BsmHW_HestonHW(self):
"""
From Quantlib test suite
"""
print("Comparing European option pricing for a BSM " +
"process with one-factor Hull-White model...")
dc = Actual365Fixed()
todays_date = today()
settings = Settings()
settings.evaluation_date = todays_date
tol = 1.e-2
spot = SimpleQuote(100)
dates = [todays_date + Period(i, Years) for i in range(40)]
rates = [0.01 + 0.0002 * np.exp(np.sin(i / 4.0)) for i in range(40)]
divRates = [0.02 + 0.0001 * np.exp(np.sin(i / 5.0)) for i in range(40)]
s0 = SimpleQuote(100)
r_ts = ZeroCurve(dates, rates, dc)
q_ts = ZeroCurve(dates, divRates, dc)
vol = SimpleQuote(0.25)
vol_ts = BlackConstantVol(todays_date, NullCalendar(), vol.value, dc)
bsm_process = BlackScholesMertonProcess(spot, q_ts, r_ts, vol_ts)
variance = vol.value * vol.value
hestonProcess = HestonProcess(risk_free_rate_ts=r_ts,
dividend_ts=q_ts,
s0=s0,
v0=variance,
kappa=5.0,
theta=variance,
sigma=1e-4,
rho=0.0)
hestonModel = HestonModel(hestonProcess)
hullWhiteModel = HullWhite(r_ts, a=0.01, sigma=0.01)
bsmhwEngine = AnalyticBSMHullWhiteEngine(0.0, bsm_process,
hullWhiteModel)
hestonHwEngine = AnalyticHestonHullWhiteEngine(hestonModel,
hullWhiteModel, 128)
tol = 1e-5
strikes = [0.25, 0.5, 0.75, 0.8, 0.9, 1.0, 1.1, 1.2, 1.5, 2.0, 4.0]
maturities = [1, 2, 3, 5, 10, 15, 20, 25, 30]
types = [Put, Call]
for type in types:
for strike in strikes:
for maturity in maturities:
maturity_date = todays_date + Period(maturity, Years)
exercise = EuropeanExercise(maturity_date)
fwd = strike * s0.value * \
q_ts.discount(maturity_date) / \
r_ts.discount(maturity_date)
payoff = PlainVanillaPayoff(type, fwd)
option = VanillaOption(payoff, exercise)
option.set_pricing_engine(bsmhwEngine)
calculated = option.npv
option.set_pricing_engine(hestonHwEngine)
expected = option.npv
if ((np.abs(expected - calculated) > calculated * tol)
and (np.abs(expected - calculated) > tol)):
cp = PAYOFF_TO_STR[type]
print("Failed to reproduce npv")
print("strike : %f" % strike)
print("maturity : %d" % maturity)
print("type : %s" % cp)
self.assertAlmostEqual(expected, calculated, delta=tol)
def test_compare_bsm_bsmhw_hestonhw(self):
dc = Actual365Fixed()
todays_date = today()
settings = Settings()
settings.evaluation_date = todays_date
tol = 1.e-2
spot = SimpleQuote(100)
dates = [todays_date + Period(i, Years) for i in range(40)]
rates = [0.01 + 0.0002 * np.exp(np.sin(i / 4.0)) for i in range(40)]
divRates = [0.02 + 0.0001 * np.exp(np.sin(i / 5.0)) for i in range(40)]
s0 = SimpleQuote(100)
r_ts = ZeroCurve(dates, rates, dc)
q_ts = ZeroCurve(dates, divRates, dc)
vol = SimpleQuote(0.25)
vol_ts = BlackConstantVol(todays_date, NullCalendar(), vol.value, dc)
bsm_process = BlackScholesMertonProcess(spot, q_ts, r_ts, vol_ts)
payoff = PlainVanillaPayoff(Call, 100)
exercise = EuropeanExercise(dates[1])
option = VanillaOption(payoff, exercise)
analytic_european_engine = AnalyticEuropeanEngine(bsm_process)
option.set_pricing_engine(analytic_european_engine)
npv_bsm = option.npv
variance = vol.value * vol.value
hestonProcess = HestonProcess(risk_free_rate_ts=r_ts,
dividend_ts=q_ts,
s0=s0,
v0=variance,
kappa=5.0,
theta=variance,
sigma=1e-4,
rho=0.0)
hestonModel = HestonModel(hestonProcess)
hullWhiteModel = HullWhite(r_ts, a=0.01, sigma=0.01)
bsmhwEngine = AnalyticBSMHullWhiteEngine(0.0, bsm_process,
hullWhiteModel)
hestonHwEngine = AnalyticHestonHullWhiteEngine(hestonModel,
hullWhiteModel, 128)
hestonEngine = AnalyticHestonEngine(hestonModel, 144)
option.set_pricing_engine(hestonEngine)
npv_heston = option.npv
option.set_pricing_engine(bsmhwEngine)
npv_bsmhw = option.npv
option.set_pricing_engine(hestonHwEngine)
npv_hestonhw = option.npv
print("calculated with BSM: %f" % npv_bsm)
print("BSM-HW: %f" % npv_bsmhw)
print("Heston: %f" % npv_heston)
print("Heston-HW: %f" % npv_hestonhw)
self.assertAlmostEqual(npv_bsm, npv_bsmhw, delta=tol)
self.assertAlmostEqual(npv_bsm, npv_hestonhw, delta=tol)
forward=SimpleQuote(forward),
daycounter=daycounter)
dc = Actual365Fixed()
todays_date = today()
settings = Settings()
settings.evaluation_date = todays_date
# constant yield and div curves
dates = [todays_date + Period(i, Years) for i in range(3)]
rates = [0.04 for i in range(3)]
divRates = [0.03 for i in range(3)]
r_ts = ZeroCurve(dates, rates, dc)
q_ts = ZeroCurve(dates, divRates, dc)
s0 = SimpleQuote(100)
# Heston model
v0 = .1
kappa_v = 2
theta_v = 0.1
sigma_v = 0.3
rho_sv = -0.5
hestonProcess = HestonProcess(risk_free_rate_ts=r_ts,
dividend_ts=q_ts,
s0=s0,
def test_compare_BsmHW_HestonHW(self):
"""
From Quantlib test suite
"""
print("Comparing European option pricing for a BSM " +
"process with one-factor Hull-White model...")
dc = Actual365Fixed()
todays_date = today()
settings = Settings()
settings.evaluation_date = todays_date
tol = 1.e-2
spot = SimpleQuote(100)
dates = [todays_date + Period(i, Years) for i in range(40)]
rates = [0.01 + 0.0002 * np.exp(np.sin(i / 4.0)) for i in range(40)]
divRates = [0.02 + 0.0001 * np.exp(np.sin(i / 5.0)) for i in range(40)]
s0 = SimpleQuote(100)
r_ts = ZeroCurve(dates, rates, dc)
q_ts = ZeroCurve(dates, divRates, dc)
vol = SimpleQuote(0.25)
vol_ts = BlackConstantVol(
todays_date,
NullCalendar(),
vol.value, dc)
bsm_process = BlackScholesMertonProcess(
spot, q_ts, r_ts, vol_ts)
variance = vol.value * vol.value
hestonProcess = HestonProcess(
risk_free_rate_ts=r_ts,
dividend_ts=q_ts,
s0=s0,
v0=variance,
kappa=5.0,
theta=variance,
sigma=1e-4,
rho=0.0)
hestonModel = HestonModel(hestonProcess)
hullWhiteModel = HullWhite(r_ts, a=0.01, sigma=0.01)
bsmhwEngine = AnalyticBSMHullWhiteEngine(
0.0, bsm_process, hullWhiteModel)
hestonHwEngine = AnalyticHestonHullWhiteEngine(
hestonModel, hullWhiteModel, 128)
tol = 1e-5
strikes = [0.25, 0.5, 0.75, 0.8, 0.9,
1.0, 1.1, 1.2, 1.5, 2.0, 4.0]
maturities = [1, 2, 3, 5, 10, 15, 20, 25, 30]
types = [Put, Call]
for option_type in types:
for strike in strikes:
for maturity in maturities:
maturity_date = todays_date + Period(maturity, Years)
exercise = EuropeanExercise(maturity_date)
fwd = strike * s0.value * \
q_ts.discount(maturity_date) / \
r_ts.discount(maturity_date)
payoff = PlainVanillaPayoff(option_type, fwd)
option = VanillaOption(payoff, exercise)
option.set_pricing_engine(bsmhwEngine)
calculated = option.npv
option.set_pricing_engine(hestonHwEngine)
expected = option.npv
if ((np.abs(expected - calculated) > calculated * tol) and
(np.abs(expected - calculated) > tol)):
print("Failed to reproduce npv")
print("strike : %f" % strike)
print("maturity : %d" % maturity)
print("type : %s" % option_type.name)
self.assertAlmostEqual(expected, calculated,
delta=tol)
class TestPiecewiseZeroSpreadedTermStructure(unittest.TestCase):
def setUp(self):
self.calendar = TARGET()
self.today = Date(9, 6, 2009)
settlement_date = self.calendar.advance(self.today, 2, Days)
Settings().evaluation_date = self.today
rates = [0.035, 0.035, 0.033, 0.034, 0.034, 0.036, 0.037, 0.039, 0.04]
ts = [13, 41, 75, 165, 256, 345, 524, 703]
dates = [settlement_date] + [self.calendar.advance(self.today, d, Days) for d in ts]
self.day_counter = Actual360()
self.term_structure = ZeroCurve(dates, rates, self.day_counter)
self.spreads = [SimpleQuote(0.02), SimpleQuote(0.03)]
self.spread_dates = [self.calendar.advance(self.today, 8, Months),
self.calendar.advance(self.today, 15, Months)]
self.spreaded_term_structure = PiecewiseZeroSpreadedTermStructure(
self.term_structure,
self.spreads,
self.spread_dates)
self.spreaded_term_structure.extrapolation = True
def test_flat_interpolation_left(self):
interpolation_date = self.calendar.advance(self.today, 6, Months)
t = self.day_counter.year_fraction(self.today, interpolation_date)
interpolated_zero_rate = (self.spreaded_term_structure.
zero_rate(t, compounding=Continuous).rate)
expected_rate = self.term_structure.zero_rate(t, compounding=Continuous).rate + \
self.spreads[0].value
self.assertAlmostEqual(interpolated_zero_rate, expected_rate)
def test_flat_interpolation_right(self):
interpolation_date = self.calendar.advance(self.today, 20, Months)
t = self.day_counter.year_fraction(self.today, interpolation_date)
interpolated_zero_rate = (self.spreaded_term_structure.
zero_rate(t, compounding=Continuous).rate)
expected_rate = self.term_structure.zero_rate(t, compounding=Continuous).rate + \
self.spreads[1].value
self.assertAlmostEqual(interpolated_zero_rate, expected_rate)
def test_linear_interpolation(self):
interpolation_date = self.calendar.advance(self.today, 12, Months)
t = self.term_structure.time_from_reference(interpolation_date)
t1 = self.term_structure.time_from_reference(self.spread_dates[0])
t2 = self.term_structure.time_from_reference(self.spread_dates[1])
interpolated_zero_rate = (self.spreaded_term_structure.
zero_rate(t, compounding=Continuous).rate)
zero_rate = (self.term_structure.
zero_rate(t, compounding=Continuous, frequency=NoFrequency))
expected_rate = zero_rate.rate + \
(t - t1) / (t2 - t1 ) * self.spreads[1].value + \
(t2 - t) / (t2 - t1) * self.spreads[0].value
spreaded_rate = InterestRate(expected_rate,
zero_rate.day_counter,
zero_rate.compounding,
zero_rate.frequency)
self.assertAlmostEqual(interpolated_zero_rate,
spreaded_rate.equivalent_rate(Continuous, NoFrequency, t).rate)