我正在使用SpreadedLinearZeroInterpolatedTermStructure类为债券定价。我有35个关键率，从1M到30Y。我也有一条每日曲线。因此，我想输入从每日现货曲线提取的35个关键利率到班级，然后更改关键利率以查看债券价格是什么。
感谢GB，他的文章在这里： http://gouthamanbalaraman.com/blog/bonds-with-spreads-quantlib-python.html
我遵循他的方法，效果很好，由于关键利率设置不同，债券价格正在变化。
然后，我用他的每日曲线代替他的平面曲线，用我的手柄（其中有35个手柄）代替他的手柄列表，并用我的35个日期代替他的两个日期。
我在NPV保持不变的同时将值设置为某些关键利率（即使我感到震惊）。我还尝试在零曲线上仅给出两个关键利率，并且它起作用了。所以我想这是因为35个关键利率太高了吗？感谢您的帮助
import QuantLib as ql
# =============================================================================
# normal yc term structure
# =============================================================================
todaysDate = ql.Date(24,5,2019)
ql.Settings.instance().evaluationDate = todaysDate
KR1 = [0, 1, 3, 6, 9] # KR in month unit
KR2 = [x for x in range(1,31)] # KR in year unit
spotDates = [] # starting from today
for kr in KR1:
p = ql.Period(kr,ql.Months)
spotDates.append(todaysDate+p)
for kr in KR2:
p = ql.Period(kr,ql.Years)
spotDates.append(todaysDate+p)
spotRates = [0.02026,
0.021569,
0.02326,
0.025008,
0.026089,
0.026679,
0.028753,
0.029376,
0.030246,
0.031362,
0.033026,
0.034274,
0.033953,
0.033474,
0.033469,
0.033927,
0.03471,
0.035596,
0.036396,
0.036994,
0.037368,
0.037567,
0.037686,
0.037814,
0.037997,
0.038247,
0.038562,
0.038933,
0.039355,
0.039817,
0.040312,
0.040832,
0.041369,
0.041922,
0.042487] # matching points
dayCount = ql.Thirty360()
calendar = ql.China()
interpolation = ql.Linear()
compounding = ql.Compounded
compoundingFrequency = ql.Annual
spotCurve = ql.ZeroCurve(spotDates, spotRates, dayCount, calendar,
interpolation,compounding, compoundingFrequency)
spotCurveHandle = ql.YieldTermStructureHandle(spotCurve)
# =============================================================================
# bond settings
# =============================================================================
issue_date = ql.Date(24,5,2018)
maturity_date = ql.Date(24,5,2023)
tenor = ql.Period(ql.Semiannual)
calendar = ql.China()
business_convention = ql.Unadjusted
date_generation = ql.DateGeneration.Backward
month_end = False
schedule = ql.Schedule(issue_date,maturity_date,tenor,calendar,
business_convention, business_convention,
date_generation,month_end)
settlement_days = 0
day_count = ql.Thirty360()
coupon_rate = 0.03
coupons = [coupon_rate]
face_value = 100
fixed_rate_bond = ql.FixedRateBond(settlement_days,
face_value,
schedule,
coupons,
day_count)
#bond_engine = ql.DiscountingBondEngine(spotCurveHandle)
#fixed_rate_bond.setPricingEngine(bond_engine)
#print(fixed_rate_bond.NPV())
# =============================================================================
# non-parallel shift of yc
# =============================================================================
#def KRshocks(kr0=0.0, kr_1M=0.0, kr_3M=0.0, kr_6M=0.0, kr_9M=0.0,
# kr_1Y=0.0,kr_2Y=0.0, kr_3Y=0.0, kr_4Y=0.0, kr_5Y=0.0, kr_6Y=0.0,
# kr_7Y=0.0, kr_8Y=0.0, kr_9Y=0.0, kr_10Y=0.0, kr_11Y=0.0, kr_12Y=0.0,
# kr_13Y=0.0, kr_14Y=0.0, kr_15Y=0.0, kr_16Y=0.0, kr_17Y=0.0, kr_18Y=0.0,
# kr_19Y=0.0, kr_20Y=0.0, kr_21Y=0.0, kr_22Y=0.0, kr_23Y=0.0, kr_24Y=0.0,
# kr_25Y=0.0, kr_26Y=0.0, kr_27Y=0.0, kr_28Y=0.0, kr_29Y=0.0, kr_30Y=0.0):
# '''
#
# Parameters:
# Input shocks for each key rate.
# kr0 = today's spot rate shock;
# kr_1M = 0.083 year(1 month) later spot rate shock;
# kr_1Y = 1 year later spot rate shock;
# .
# .
# .
#
# '''
#
# krs = list(locals().keys())
# KRHandles = {}
# for k in krs:
# KRHandles['{}handle'.format(k)] = ql.QuoteHandle(ql.SimpleQuote(locals()[k]))
# return list(KRHandles.values())
#handles = KRshocks()
kr = ['kr0', 'kr_1M', 'kr_3M', 'kr_6M', 'kr_9M', 'kr_1Y','kr_2Y', 'kr_3Y',
'kr_4Y', 'kr_5Y', 'kr_6Y','kr_7Y', 'kr_8Y', 'kr_9Y', 'kr_10Y', 'kr_11Y',
'kr_12Y', 'kr_13Y', 'kr_14Y', 'kr_15Y', 'kr_16Y', 'kr_17Y', 'kr_18Y',
'kr_19Y', 'kr_20Y', 'kr_21Y', 'kr_22Y', 'kr_23Y', 'kr_24Y','kr_25Y',
'kr_26Y', 'kr_27Y', 'kr_28Y', 'kr_29Y', 'kr_30Y']
#KRQuotes = {}
handles = []
#for k in range(len(kr)):
# KRQuotes['{}'.format(kr[k])] = ql.SimpleQuote(spotRates[k])
# handles.append(ql.QuoteHandle(ql.SimpleQuote(spotRates[k])))
kr0 = ql.SimpleQuote(spotRates[0])
kr_1M = ql.SimpleQuote(spotRates[1])
kr_3M = ql.SimpleQuote(spotRates[2])
kr_6M = ql.SimpleQuote(spotRates[3])
kr_9M = ql.SimpleQuote(spotRates[4])
kr_1Y = ql.SimpleQuote(spotRates[5])
kr_2Y = ql.SimpleQuote(spotRates[6])
kr_3Y = ql.SimpleQuote(spotRates[7])
kr_4Y = ql.SimpleQuote(spotRates[8])
kr_5Y = ql.SimpleQuote(spotRates[9])
kr_6Y = ql.SimpleQuote(spotRates[10])
kr_7Y = ql.SimpleQuote(spotRates[11])
kr_8Y = ql.SimpleQuote(spotRates[12])
kr_9Y = ql.SimpleQuote(spotRates[13])
kr_10Y = ql.SimpleQuote(spotRates[14])
kr_11Y = ql.SimpleQuote(spotRates[15])
kr_12Y = ql.SimpleQuote(spotRates[16])
kr_13Y = ql.SimpleQuote(spotRates[17])
kr_14Y = ql.SimpleQuote(spotRates[18])
kr_15Y = ql.SimpleQuote(spotRates[19])
kr_16Y = ql.SimpleQuote(spotRates[20])
kr_17Y = ql.SimpleQuote(spotRates[21])
kr_18Y = ql.SimpleQuote(spotRates[22])
kr_19Y = ql.SimpleQuote(spotRates[23])
kr_20Y = ql.SimpleQuote(spotRates[24])
kr_21Y = ql.SimpleQuote(spotRates[25])
kr_22Y = ql.SimpleQuote(spotRates[26])
kr_23Y = ql.SimpleQuote(spotRates[27])
kr_24Y = ql.SimpleQuote(spotRates[28])
kr_25Y = ql.SimpleQuote(spotRates[29])
kr_26Y = ql.SimpleQuote(spotRates[30])
kr_27Y = ql.SimpleQuote(spotRates[31])
kr_28Y = ql.SimpleQuote(spotRates[32])
kr_29Y = ql.SimpleQuote(spotRates[33])
kr_30Y = ql.SimpleQuote(spotRates[34])
handles.append(ql.QuoteHandle(kr0))
handles.append(ql.QuoteHandle(kr_1M))
handles.append(ql.QuoteHandle(kr_3M))
handles.append(ql.QuoteHandle(kr_6M))
handles.append(ql.QuoteHandle(kr_9M))
handles.append(ql.QuoteHandle(kr_1Y))
handles.append(ql.QuoteHandle(kr_2Y))
handles.append(ql.QuoteHandle(kr_3Y))
handles.append(ql.QuoteHandle(kr_4Y))
handles.append(ql.QuoteHandle(kr_5Y))
handles.append(ql.QuoteHandle(kr_6Y))
handles.append(ql.QuoteHandle(kr_7Y))
handles.append(ql.QuoteHandle(kr_8Y))
handles.append(ql.QuoteHandle(kr_9Y))
handles.append(ql.QuoteHandle(kr_10Y))
handles.append(ql.QuoteHandle(kr_11Y))
handles.append(ql.QuoteHandle(kr_12Y))
handles.append(ql.QuoteHandle(kr_13Y))
handles.append(ql.QuoteHandle(kr_14Y))
handles.append(ql.QuoteHandle(kr_15Y))
handles.append(ql.QuoteHandle(kr_16Y))
handles.append(ql.QuoteHandle(kr_17Y))
handles.append(ql.QuoteHandle(kr_18Y))
handles.append(ql.QuoteHandle(kr_19Y))
handles.append(ql.QuoteHandle(kr_20Y))
handles.append(ql.QuoteHandle(kr_21Y))
handles.append(ql.QuoteHandle(kr_22Y))
handles.append(ql.QuoteHandle(kr_23Y))
handles.append(ql.QuoteHandle(kr_24Y))
handles.append(ql.QuoteHandle(kr_25Y))
handles.append(ql.QuoteHandle(kr_26Y))
handles.append(ql.QuoteHandle(kr_27Y))
handles.append(ql.QuoteHandle(kr_28Y))
handles.append(ql.QuoteHandle(kr_29Y))
handles.append(ql.QuoteHandle(kr_30Y))
ts_spreaded2 = ql.SpreadedLinearZeroInterpolatedTermStructure(spotCurveHandle,
handles,
spotDates)
ts_spreaded_handle2 = ql.YieldTermStructureHandle(ts_spreaded2)
bond_engine = ql.DiscountingBondEngine(ts_spreaded_handle2)
fixed_rate_bond.setPricingEngine(bond_engine)
#print(fixed_rate_bond.NPV())
kr0.setValue(0.1)
kr_10Y.setValue(0.2)
kr_12Y.setValue(0.2)
print(fixed_rate_bond.NPV())
没有出现错误，但债券价格与添加价差之前的价格相同