,可以通过以下步骤实现:
在此背景下,如果需要从Quantlib BachelierSwaption价格中检索黑色vol,可以采取以下步骤:
import QuantLib as ql
calendar = ql.TARGET()
todaysDate = ql.Date(1, 1, 2022)
ql.Settings.instance().evaluationDate = todaysDate
index = ql.Euribor6M()
forwardCurve = ql.YieldTermStructureHandle(ql.FlatForward(todaysDate, 0.05, ql.Actual360()))
volatility = 0.2 # 设置初始的波动率
engine = ql.BachelierSwaptionEngine(forwardCurve, ql.QuoteHandle(ql.SimpleQuote(volatility)))
start_date = ql.Date(1, 7, 2022)
end_date = ql.Date(1, 7, 2027)
tenor = ql.Period(ql.Annual)
calendar.advance(start_date, tenor)
schedule = ql.Schedule(start_date, end_date, tenor, calendar, ql.ModifiedFollowing, ql.ModifiedFollowing,
ql.DateGeneration.Forward, False)
strike = 0.02 # 设置行权价
swaption = ql.Swaption(ql.VanillaSwap(ql.VanillaSwap.Receiver, 1000000.0, schedule, strike, index), ql.EuropeanExercise(start_date))
swaption.setPricingEngine(engine)
swaption_price = swaption.NPV()
black_volatility = swaption.impliedVolatility(swaption_price, forwardCurve, 0.001, 100, 0.0001, 0.50)
综上所述,以上是使用Quantlib计算BachelierSwaption价格,并从中检索黑色volatility的步骤。注意,这只是一个简单的示例,实际情况中可能涉及更复杂的模型和参数设置。此外,腾讯云没有特定的产品或链接与这个问题相关。
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