def test_reference_evaluation_data_changed(self):
"""Testing term structure against evaluation date change... """
quote = SimpleQuote()
term_structure = FlatForward(settlement_days=self.settlement_days,
forward=quote, calendar=NullCalendar(), daycounter=Actual360())
quote.value = 0.03
expected = []
for days in [10, 30, 60, 120, 360, 720]:
expected.append(
term_structure.discount(self.adjusted_today + days)
)
Settings().evaluation_date = self.adjusted_today + 30
calculated = []
for days in [10, 30, 60, 120, 360, 720]:
calculated.append(
term_structure.discount(self.adjusted_today+ 30 + days)
)
for i, val in enumerate(expected):
self.assertAlmostEqual(val, calculated[i])
def test_reference_evaluation_data_changed(self):
"""Testing term structure against evaluation date change... """
quote = SimpleQuote()
term_structure = FlatForward(settlement_days=self.settlement_days,
forward=quote, calendar=NullCalendar(), daycounter=Actual360())
quote.value = 0.03
expected = []
for days in [10, 30, 60, 120, 360, 720]:
expected.append(
term_structure.discount(self.adjusted_today + days)
)
Settings().evaluation_date = self.adjusted_today + 30
calculated = []
for days in [10, 30, 60, 120, 360, 720]:
calculated.append(
term_structure.discount(self.adjusted_today+ 30 + days)
)
for i, val in enumerate(expected):
self.assertAlmostEqual(val, calculated[i])
def test_flat_hazard_with_quote(self):
Settings.instance().evaluation_date = self.todays_date
hazard_rate = SimpleQuote()
flat_curve = FlatHazardRate(2, self.calendar, hazard_rate, Actual365Fixed())
for h in [0.01, 0.02, 0.03]:
hazard_rate.value = h
self.assertAlmostEqual(flat_curve.survival_probability(self.d),
math.exp(-h * flat_curve.time_from_reference(self.d)))
def test_quote_observability(self):
self.count = 0
q = SimpleQuote(0.1)
def counter():
self.count += 1
obs = Observer(counter)
obs.register_with(q)
self.assertEqual(self.count, 0)
q.value = 0.2
self.assertEqual(self.count, 1)
q.value = 0.3
self.assertEqual(self.count, 2)
obs.unregister_with(q)
q.value = 0.4
self.assertEqual(self.count, 2)
def test_flat_hazard_with_quote(self):
Settings.instance().evaluation_date = self.todays_date
hazard_rate = SimpleQuote()
flat_curve = FlatHazardRate(2, self.calendar, hazard_rate, Actual365Fixed())
for h in [0.01, 0.02, 0.03]:
hazard_rate.value = h
self.assertAlmostEqual(flat_curve.survival_probability(self.d),
math.exp(-h * flat_curve.time_from_reference(self.d)))
def test_using_simple_quote(self):
quote = SimpleQuote(10)
self.assertEqual(10, quote.value)
quote.value = 15
self.assertEqual(15, quote.value)
self.assertTrue(quote.is_valid)
def test_using_simple_quote(self):
quote = SimpleQuote(10)
self.assertEquals(10, quote.value)
quote.value = 15
self.assertEquals(15, quote.value)
self.assertTrue(quote.is_valid)
def test_empty_constructor(self):
quote = SimpleQuote()
self.assertFalse(quote.is_valid)
with self.assertRaisesRegexp(RuntimeError, 'invalid SimpleQuote'):
x = quote.value
# test quote reset
quote.value = 1.
quote.reset()
self.assertFalse(quote.is_valid)
with self.assertRaisesRegexp(RuntimeError, 'invalid SimpleQuote'):
x = quote.value
def test_empty_constructor(self):
quote = SimpleQuote()
self.assertFalse(quote.is_valid)
with self.assertRaisesRegexp(RuntimeError, 'invalid SimpleQuote'):
x = quote.value
# test quote reset
quote.value = 1.
quote.reset()
self.assertFalse(quote.is_valid)
with self.assertRaisesRegexp(RuntimeError, 'invalid SimpleQuote'):
x = quote.value
date_payment = Date(6,10,2011)
settlement_days = 2
settings.evaluation_date = date_today
quote = SimpleQuote(value=0.03)
term_structure = FlatForward(
settlement_days = settlement_days,
quote = quote,
calendar = NullCalendar(),
daycounter = Actual360()
)
df_1 = term_structure.discount(date_payment)
date_today = Date(19,9,2011)
settings.evaluation_date = date_today
date_payment = Date(19,10,2011)
df_2 = term_structure.discount(date_payment)
# df_1 and df_2 should be identical:
print('rate: %f df_1: %f df_2 %f difference: %f' % (quote.value, df_1, df_2, df_2-df_1))
# the term structure registers a listener on the quote: a change in quote
# triggers a lazy recalculation of the discount factor
quote.value = .05
df_2 = term_structure.discount(date_payment)
print('rate: %f df_2: %f' % (quote.value, df_2))
date_payment = Date(6,10,2011)
settlement_days = 2
settings.evaluation_date = date_today
quote = SimpleQuote(value=0.03)
term_structure = FlatForward(
settlement_days = settlement_days,
quote = quote,
calendar = NullCalendar(),
daycounter = Actual360()
)
df_1 = term_structure.discount(date_payment)
date_today = Date(19,9,2011)
settings.evaluation_date = date_today
date_payment = Date(19,10,2011)
df_2 = term_structure.discount(date_payment)
# df_1 and df_2 should be identical:
print('rate: %f df_1: %f df_2 %f difference: %f' % (quote.value, df_1, df_2, df_2-df_1))
# the term structure registers a listener on the quote: a change in quote
# triggers a lazy recalculation of the discount factor
quote.value = .05
df_2 = term_structure.discount(date_payment)
print('rate: %f df_2: %f' % (quote.value, df_2))
def test_analytic_cont_geo_av_price_greeks(self):
tolerance = {}
tolerance["delta"] = 1.0e-5
tolerance["gamma"] = 1.0e-5
# tolerance["theta"] = 1.0e-5
tolerance["rho"] = 1.0e-5
tolerance["divRho"] = 1.0e-5
tolerance["vega"] = 1.0e-5
opt_types = [Call, Put]
underlyings = [100.0]
strikes = [90.0, 100.0, 110.0]
q_rates = [0.04, 0.05, 0.06]
r_rates = [0.01, 0.05, 0.15]
lengths = [1, 2]
vols = [0.11, 0.50, 1.20]
spot = SimpleQuote(0.0)
q_rate = SimpleQuote(0.0)
r_rate = SimpleQuote(0.0)
vol = SimpleQuote(0.0)
q_ts = flat_rate(q_rate, self.daycounter)
r_ts = flat_rate(r_rate, self.daycounter)
vol_ts = BlackConstantVol(self.today, self.calendar, vol, self.daycounter)
process = BlackScholesMertonProcess(spot, q_ts, r_ts, vol_ts)
calculated = {}
expected = {}
for opt_type, strike, length in product(opt_types, strikes, lengths):
maturity = EuropeanExercise(self.today + length*Years)
payoff = PlainVanillaPayoff(opt_type, strike)
engine = AnalyticContinuousGeometricAveragePriceAsianEngine(process)
option = ContinuousAveragingAsianOption(Geometric, payoff, maturity)
option.set_pricing_engine(engine)
for u, m, n, v in product(underlyings, q_rates, r_rates, vols):
q = m
r = n
spot.value = u
q_rate.value = q
r_rate.value = r
vol.value = v
value = option.npv
calculated["delta"] = option.delta
calculated["gamma"] = option.gamma
# calculated["theta"] = option.theta
calculated["rho"] = option.rho
calculated["divRho"] = option.dividend_rho
calculated["vega"] = option.vega
if (value > spot.value*1.0e-5):
# perturb spot and get delta and gamma
du = u*1.0e-4
spot.value = u + du
value_p = option.npv
delta_p = option.delta
spot.value = u - du
value_m = option.npv
delta_m = option.delta
spot.value = u
expected["delta"] = (value_p - value_m)/(2*du)
expected["gamma"] = (delta_p - delta_m)/(2*du)
# perturb rates and get rho and dividend rho
dr = r*1.0e-4
r_rate.value = r + dr
value_p = option.npv
r_rate.value = r - dr
value_m = option.npv
r_rate.value = r
expected["rho"] = (value_p - value_m)/(2*dr)
dq = q*1.0e-4
q_rate.value = q + dq
value_p = option.npv
q_rate.value = q - dq
value_m = option.npv
q_rate.value = q
expected["divRho"] = (value_p - value_m)/(2*dq)
# perturb volatility and get vega
dv = v*1.0e-4
vol.value = v + dv
value_p = option.npv
vol.value = v - dv
value_m = option.npv
vol.value = v
expected["vega"] = (value_p - value_m)/(2*dv)
# perturb date and get theta
dt = self.daycounter.year_fraction(self.today - 1, self.today + 1)
self.settings.evaluation_date = self.today - 1
value_m = option.npv
self.settings.evaluation_date = self.today + 1
value_p = option.npv
self.settings.evaluation_date = self.today
expected["theta"] = (value_p - value_m)/dt
# compare
for greek, calcl in calculated.items():
expct = expected[greek]
tol = tolerance[greek]
error = relative_error(expct, calcl, u)
self.assertTrue(error < tol)
