Swap Curve Construction · Python 量化交易教程

# Swap Curve Construction > 来源：https://uqer.io/community/share/55c2d440f9f06c91fc18c648 在这个示例中，我们将指导用户如何使用平台的功能，完成从利率互换的市场报价完成收益率曲线的构造。 ```py from CAL.PyCAL import * SetEvaluationDate(Date(2015, 8, 6)) ``` ## 1. 构造收益率曲线我们从一组市场标准化互换的市场报价中获取收益率曲线的信息： + `swap_rates`：标准互换对应的固定端利率 + `swap_tenor`：标准互换对应的期限 ```py swap_rates = [0.02, 0.03, 0.04 ,0.05, 0.055, 0.06, 0.065, 0.07] swap_tenor = ['6M', '1Y', '2Y', '3Y', '4Y', '5Y', '7Y', '10Y'] shiborIndex = Shibor('3M') instruments = [] for rate, tenor in zip(swap_rates, swap_tenor): print('{0:3s} benchmark Shibor Swap fixed at: {1:.2f}%'.format(tenor, rate*100)) rateHelper = ShiborSwapRateHelper(rate, Period(tenor), Frequency.Quarterly, shiborIndex) instruments.append(rateHelper) 6M benchmark Shibor Swap fixed at: 2.00% 1Y benchmark Shibor Swap fixed at: 3.00% 2Y benchmark Shibor Swap fixed at: 4.00% 3Y benchmark Shibor Swap fixed at: 5.00% 4Y benchmark Shibor Swap fixed at: 5.50% 5Y benchmark Shibor Swap fixed at: 6.00% 7Y benchmark Shibor Swap fixed at: 6.50% 10Y benchmark Shibor Swap fixed at: 7.00% ``` 通过标准互换校正（calibration）收益率曲线： ```py calibratedCurve = CalibratedYieldCurve(EvaluationDate(), instruments, 'Actual/365 (Fixed)') ``` 收益率曲线的基本信息： + `discount`：折现因子 + `forward(%)`：远期利率 + `zero(%)`：零息利率 ```py calibratedCurve.curveProfile().head(10) ``` | | date | discount | forward(%) | zero(%) | | --- | --- | | 2015-08-06 | 2015-08-06 | 1.000000 | 1.994947 | 2.014979 | | 2015-09-06 | 2015-09-06 | 0.998307 | 1.994947 | 2.014979 | | 2015-10-06 | 2015-10-06 | 0.996672 | 1.994947 | 2.014979 | | 2015-11-06 | 2015-11-06 | 0.994984 | 1.994947 | 2.014979 | | 2015-12-06 | 2015-12-06 | 0.993354 | 1.994947 | 2.014979 | | 2016-01-06 | 2016-01-06 | 0.991672 | 1.994947 | 2.014979 | | 2016-02-06 | 2016-02-06 | 0.989994 | 1.994947 | 2.014979 | | 2016-03-06 | 2016-03-06 | 0.986950 | 4.014304 | 2.276446 | | 2016-04-06 | 2016-04-06 | 0.983591 | 4.014304 | 2.505840 | | 2016-05-06 | 2016-05-06 | 0.980351 | 4.014304 | 2.678750 | 我们可以画图来看： ```py calibratedCurve.curveProfile()['zero(%)'].plot(figsize=(16,8)) <matplotlib.axes.AxesSubplot at 0x6bbabd0> ``` ![](https://box.kancloud.cn/2016-07-30_579cbdb897fb5.png) ## 2. 测试首先可以看这条收益率曲线是否真的可以完美定价基准互换（perfectly pricing）： ```py cal = Calendar('China.IB') startDate = cal.advanceDate(Date(2015, 8, 6), '1B', BizDayConvention.Following) shiborIndex = Shibor('3M', calibratedCurve) nominal = 100000000. pricingEngine = DiscountingSwapEngine(calibratedCurve) for rate, tenor in zip(swap_rates, swap_tenor): benchmarkSwap = ShiborSwap(SwapLegType.Payer, nominal, startDate, Period(tenor), Period('3M'), rate, shiborIndex) benchmarkSwap.setPricingEngine(pricingEngine) print('{0:3s} benchmark Shibor Swap NPV: {1:>8.4f}'.format(tenor, benchmarkSwap.NPV())) 6M benchmark Shibor Swap NPV: 0.0000 1Y benchmark Shibor Swap NPV: -0.0000 2Y benchmark Shibor Swap NPV: 0.0000 3Y benchmark Shibor Swap NPV: 0.0000 4Y benchmark Shibor Swap NPV: -0.0000 5Y benchmark Shibor Swap NPV: 0.0000 7Y benchmark Shibor Swap NPV: 0.0000 10Y benchmark Shibor Swap NPV: 0.0000 ``` 然后我们取一个假设已经存在的互换（seasoned swap），通过这条收益率曲线估计它的现值： ```py startDate = Date(2015, 7, 15) shiborIndex.addFixing(Date(2015, 7, 14), 0.045) customizeSwap = ShiborSwap(SwapLegType.Receiver, nominal, startDate, Period('9Y'), Period('3M'), 0.06, shiborIndex) customizeSwap.setPricingEngine(pricingEngine) print('{0:3s} Shibor Swap fixed at {1:.2f}% NPV: {2:15.4f}'.format('9Y',6.00, customizeSwap.NPV())) 9Y Shibor Swap fixed at 6.00% NPV: -6308510.5573 ``` ```py customizeSwap.legAnalysis(0).head(10) ``` | | AMOUNT | NOMINAL | ACCRUAL_START_DATE | ACCRUAL_END_DATE | ACCRUAL_DAYS | INDEX | FIXING_DAYS | FIXING_DATES | INDEX_FIXING | DAY_COUNTER | ACCRUAL_PERIOD | EFFECTIVE_RATE | | --- | --- | | PAYMENT_DATE | | | | | | | | | | | | | | 2015-10-15 | 1512329 | 1e+08 | 2015-07-15 | 2015-10-15 | 92 | #NA | #NA | #NA | #NA | Actual/365 (Fixed) | 0.2520548 | 0.06 | | 2016-01-15 | 1512329 | 1e+08 | 2015-10-15 | 2016-01-15 | 92 | #NA | #NA | #NA | #NA | Actual/365 (Fixed) | 0.2520548 | 0.06 | | 2016-04-15 | 1495890 | 1e+08 | 2016-01-15 | 2016-04-15 | 91 | #NA | #NA | #NA | #NA | Actual/365 (Fixed) | 0.2493151 | 0.06 | | 2016-07-15 | 1495890 | 1e+08 | 2016-04-15 | 2016-07-15 | 91 | #NA | #NA | #NA | #NA | Actual/365 (Fixed) | 0.2493151 | 0.06 | | 2016-10-17 | 1545205 | 1e+08 | 2016-07-15 | 2016-10-17 | 94 | #NA | #NA | #NA | #NA | Actual/365 (Fixed) | 0.2575342 | 0.06 | | 2017-01-16 | 1495890 | 1e+08 | 2016-10-17 | 2017-01-16 | 91 | #NA | #NA | #NA | #NA | Actual/365 (Fixed) | 0.2493151 | 0.06 | | 2017-04-17 | 1495890 | 1e+08 | 2017-01-16 | 2017-04-17 | 91 | #NA | #NA | #NA | #NA | Actual/365 (Fixed) | 0.2493151 | 0.06 | | 2017-07-17 | 1495890 | 1e+08 | 2017-04-17 | 2017-07-17 | 91 | #NA | #NA | #NA | #NA | Actual/365 (Fixed) | 0.2493151 | 0.06 | | 2017-10-16 | 1495890 | 1e+08 | 2017-07-17 | 2017-10-16 | 91 | #NA | #NA | #NA | #NA | Actual/365 (Fixed) | 0.2493151 | 0.06 | | 2018-01-15 | 1495890 | 1e+08 | 2017-10-16 | 2018-01-15 | 91 | #NA | #NA | #NA | #NA | Actual/365 (Fixed) | 0.2493151 | 0.06 | ```py customizeSwap.legAnalysis(1).head(10) ``` | | AMOUNT | NOMINAL | ACCRUAL_START_DATE | ACCRUAL_END_DATE | ACCRUAL_DAYS | INDEX | FIXING_DAYS | FIXING_DATES | INDEX_FIXING | DAY_COUNTER | ACCRUAL_PERIOD | EFFECTIVE_RATE | | --- | --- | | PAYMENT_DATE | | | | | | | | | | | | | | 2015-10-15 | 1150000 | 1e+08 | 2015-07-15 | 2015-10-15 | 92 | Shibor3M Actual/360 | 1 | 2015-07-14 | 0.045 | Actual/360 | 0.2555556 | 0.045 | | 2016-01-15 | 504102.3 | 1e+08 | 2015-10-15 | 2016-01-15 | 92 | Shibor3M Actual/360 | 1 | 2015-10-14 | 0.01972574 | Actual/360 | 0.2555556 | 0.01972574 | | 2016-04-15 | 871825.4 | 1e+08 | 2016-01-15 | 2016-04-15 | 91 | Shibor3M Actual/360 | 1 | 2016-01-14 | 0.03448979 | Actual/360 | 0.2527778 | 0.03448979 | | 2016-07-15 | 1005852 | 1e+08 | 2016-04-15 | 2016-07-15 | 91 | Shibor3M Actual/360 | 1 | 2016-04-14 | 0.03979193 | Actual/360 | 0.2527778 | 0.03979193 | | 2016-10-17 | 1234864 | 1e+08 | 2016-07-15 | 2016-10-17 | 94 | Shibor3M Actual/360 | 1 | 2016-07-14 | 0.04729266 | Actual/360 | 0.2611111 | 0.04729266 | | 2017-01-16 | 1260227 | 1e+08 | 2016-10-17 | 2017-01-16 | 91 | Shibor3M Actual/360 | 1 | 2016-10-14 | 0.04985512 | Actual/360 | 0.2527778 | 0.04985512 | | 2017-04-17 | 1260227 | 1e+08 | 2017-01-16 | 2017-04-17 | 91 | Shibor3M Actual/360 | 1 | 2017-01-13 | 0.04985512 | Actual/360 | 0.2527778 | 0.04985512 | | 2017-07-17 | 1260227 | 1e+08 | 2017-04-17 | 2017-07-17 | 91 | Shibor3M Actual/360 | 1 | 2017-04-14 | 0.04985512 | Actual/360 | 0.2527778 | 0.04985512 | | 2017-10-16 | 1668056 | 1e+08 | 2017-07-17 | 2017-10-16 | 91 | Shibor3M Actual/360 | 1 | 2017-07-14 | 0.06598904 | Actual/360 | 0.2527778 | 0.06598904 | | 2018-01-15 | 1790725 | 1e+08 | 2017-10-16 | 2018-01-15 | 91 | Shibor3M Actual/360 | 1 | 2017-10-13 | 0.07084187 | Actual/360 | 0.2527778 | 0.07084187 |