本文整理汇总了Python中quantlib.instruments.option.VanillaOption.implied_volatility方法的典型用法代码示例。如果您正苦于以下问题：Python VanillaOption.implied_volatility方法的具体用法？Python VanillaOption.implied_volatility怎么用？Python VanillaOption.implied_volatility使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类quantlib.instruments.option.VanillaOption的用法示例。
在下文中一共展示了VanillaOption.implied_volatility方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_bsm_hw
# 需要导入模块: from quantlib.instruments.option import VanillaOption [as 别名]
# 或者: from quantlib.instruments.option.VanillaOption import implied_volatility [as 别名]
def test_bsm_hw(self):
print("Testing European option pricing for a BSM process" +
" with one-factor Hull-White model...")
dc = Actual365Fixed()
todays_date = today()
maturity_date = todays_date + Period(20, Years)
settings = Settings()
settings.evaluation_date = todays_date
spot = SimpleQuote(100)
q_ts = flat_rate(todays_date, 0.04, dc)
r_ts = flat_rate(todays_date, 0.0525, dc)
vol_ts = BlackConstantVol(todays_date, NullCalendar(), 0.25, dc)
hullWhiteModel = HullWhite(r_ts, 0.00883, 0.00526)
bsm_process = BlackScholesMertonProcess(spot, q_ts,
r_ts, vol_ts)
exercise = EuropeanExercise(maturity_date)
fwd = spot.value * q_ts.discount(maturity_date) / \
r_ts.discount(maturity_date)
payoff = PlainVanillaPayoff(Call, fwd)
option = VanillaOption(payoff, exercise)
tol = 1e-8
corr = [-0.75, -0.25, 0.0, 0.25, 0.75]
expectedVol = [0.217064577, 0.243995801, 0.256402830,
0.268236596, 0.290461343]
for c, v in zip(corr, expectedVol):
bsm_hw_engine = AnalyticBSMHullWhiteEngine(c, bsm_process,
hullWhiteModel)
option = VanillaOption(payoff, exercise)
option.set_pricing_engine(bsm_hw_engine)
npv = option.npv
compVolTS = BlackConstantVol(todays_date, NullCalendar(),
v, dc)
bs_process = BlackScholesMertonProcess(spot, q_ts,
r_ts, compVolTS)
bsEngine = AnalyticEuropeanEngine(bs_process)
comp = VanillaOption(payoff, exercise)
comp.set_pricing_engine(bsEngine)
impliedVol = comp.implied_volatility(npv, bs_process,
1e-10, 500,
min_vol=0.1,
max_vol=0.4)
if (abs(impliedVol - v) > tol):
print("Failed to reproduce implied volatility cor: %f" % c)
print("calculated: %f" % impliedVol)
print("expected : %f" % v)
if abs((comp.npv - npv) / npv) > tol:
print("Failed to reproduce NPV")
print("calculated: %f" % comp.npv)
print("expected : %f" % npv)
self.assertAlmostEqual(impliedVol, v, delta=tol)
self.assertAlmostEqual(comp.npv / npv, 1, delta=tol)