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<p>我想从Quantlib BachelierSwaptionEngine计算的交换期权价格中检索一个黑色的Vol。这看起来可以在Quantlib中通过优化器(比如牛顿法)或者直接通过impliedVolatility方法来实现。
我无法在Quantlib Python中使用Quantlib优化器或impliedVolatility方法。在</p>
<p>下面的代码显示了如何计算Quantlib中的互换期权价格。从那里我需要检索一个基于代码中计算的交换期权价格的黑色卷</p>
<pre><code>import Quantlib as ql
from scipy import optimize
calc_date = ql.Date(29,3,2019)
rate = ql.SimpleQuote(0.01)
rate_handle = ql.QuoteHandle(rate)
dc = ql.Actual365Fixed()
spot_curve = ql.FlatForward(calc_date, rate_handle, dc)
start = 10
length = 10
start_date = ql.TARGET().advance(calc_date, start, ql.Years)
maturity_date = start_date + ql.Period(length, ql.Years)
fixed_schedule = ql.Schedule(start_date, maturity_date,
ql.Period(1, ql.Years), ql.TARGET(), ql.Unadjusted,
ql.Unadjusted,ql.DateGeneration.Forward, False)
floating_schedule = ql.Schedule(start_date, maturity_date,
ql.Period(6, ql.Months), ql.TARGET(),
ql.ModifiedFollowing, ql.ModifiedFollowing,
ql.DateGeneration.Forward, True)
index6m = ql.Euribor6M(ql.YieldTermStructureHandle(spot_curve))
rate = 1.45 / 100
swap = ql.VanillaSwap(ql.VanillaSwap.Receiver, 10000000,
fixed_schedule, rate, ql.Thirty360(ql.Thirty360.BondBasis),
floating_schedule, index6m, 0.0, index6m.dayCounter())
swap.setPricingEngine(ql.DiscountingSwapEngine(
ql.YieldTermStructureHandle(spot_curve)))
swaption_normal_model = ql.Swaption(swap,
ql.EuropeanExercise(swap.startDate()))
normal_vol = ql.SimpleQuote(0.005266)
swaption_normal_model.setPricingEngine
(ql.BachelierSwaptionEngine(ql.YieldTermStructureHandle(spot_curve),
ql.QuoteHandle(normal_vol)))
swaption_normal_model_value = swaption_normal_model.NPV()
</code></pre>