Euribor index(depositData[i].n*depositData[i].units,curveHandle);
Rate expectedRate = depositData[i].rate/100,
estimatedRate = index.fixing(vars.today);
In my code the pricing date is equivalent to "today" here. The sample driver program seems to suggest using pricing date to index fixing. Your change is not exactly in accordance with the sample code, is it? As a result, the 1M and 3M estimated rates are quite off.
Thanks!
Guan
Hi Guan,
The deposit check is requesting a rate for the zerodate and hence getting a negative time of 1 day in years (for 360 days). Change the deposit check to this so you are actually asking for a rate on the deposit data point.
for (Size i = 0; i<libors; i++) {
//USDLibor index(depositData[i].n*depositData[i].units, ycHandle);
Libor index("USDLibor", depositData[i].n*depositData[i].units, 2,
USDCurrency(),
calendar,
Actual360(), ycHandle);
Rate inputRate = depositData[i].rate / 100;
Date l_DateToUse = pricingDate + (depositData[i].n*depositData[i].units);
Rate estimatedRate = index.fixing(l_DateToUse);
//if (std::fabs(estimatedRate - inputRate) > tolerance)
cout << depositData[i].n*depositData[i].units << " (" << l_DateToUse << ") "
<< " Deposit:"
<< setprecision(8)
<< "\n\t estimated rate: " << estimatedRate
<< "\n\t input rate: " << inputRate
<< endl;
}
I get the following output – the deposit rates for 1M and 3M are off although the zero yield rates for 0M and 3M look better – I’m not sure why at the moment.
Thanks
Ed
zero date is January 22nd, 2014
Checking estimated rates against input...
1M (February 17th, 2014) Deposit:
estimated rate: 0.0020672531
input rate: 0.00157
3M (April 17th, 2014) Deposit:
estimated rate: 0.0021845006
input rate: 0.002366
5Y Swap :
estimated rate: 0.0173377
input rate: 0.0173377
6Y Swap :
estimated rate: 0.02074532
input rate: 0.02074532
7Y Swap :
estimated rate: 0.0236113
input rate: 0.0236113
8Y Swap :
estimated rate: 0.02592213
input rate: 0.02592213
9Y Swap :
estimated rate: 0.02781181
input rate: 0.02781181
10Y Swap :
estimated rate: 0.02937271
input rate: 0.02937271
15Y Swap :
estimated rate: 0.03418712
input rate: 0.03418712
30Y Swap :
estimated rate: 0.03742963
input rate: 0.03742963
35Y Swap :
estimated rate: 0.03742963
input rate: 0.03742963
40Y Swap :
estimated rate: 0.03742963
input rate: 0.03742963
45Y Swap :
estimated rate: 0.03742963
input rate: 0.03742963
50Y Swap :
estimated rate: 0.03742963
input rate: 0.03742963
Zero-yield Rates...
Zero 0M: January 22nd, 2014 0.001569887 discount factor 1
Zero 3M: April 22nd, 2014 0.0023653005 discount factor 0.99940885
Zero 6M: July 22nd, 2014 0.0022751584 discount factor 0.99885675
Zero 9M: October 22nd, 2014 0.0026115489 discount factor 0.99802154
Zero 12M: January 22nd, 2015 0.002851819 discount factor 0.99711275
Zero 15M: April 22nd, 2015 0.003226952 discount factor 0.9959298
Zero 18M: July 22nd, 2015 0.003708467 discount factor 0.99439128
Zero 21M: October 22nd, 2015 0.0043166678 discount factor 0.99237909
Zero 24M: January 22nd, 2016 0.0050454544 discount factor 0.9898211
Zero 27M: April 22nd, 2016 0.0058911916 discount factor 0.98665466
Zero 30M: July 22nd, 2016 0.006853368 discount factor 0.98278798
Zero 33M: October 22nd, 2016 0.0078990854 discount factor 0.97821121
Zero 36M: January 22nd, 2017 0.0089884804 discount factor 0.9730061
Zero 39M: April 22nd, 2017 0.010082293 discount factor 0.96733002
Zero 42M: July 22nd, 2017 0.011174645 discount factor 0.9611364
Zero 45M: October 22nd, 2017 0.012259943 discount factor 0.95444826
Zero 48M: January 22nd, 2018 0.013324237 discount factor 0.94736181
Zero 51M: April 22nd, 2018 0.014343294 discount factor 0.94007493
Zero 54M: July 22nd, 2018 0.015349671 discount factor 0.93238305
Zero 57M: October 22nd, 2018 0.016340753 discount factor 0.92430982
Zero 60M: January 22nd, 2019 0.017303495 discount factor 0.91597412
Zero 63M: April 22nd, 2019 0.018216268 discount factor 0.90760046
Zero 66M: July 22nd, 2019 0.019109012 discount factor 0.89894562
Zero 69M: October 22nd, 2019 0.019979907 discount factor 0.89003548
Zero 72M: January 22nd, 2020 0.02081814 discount factor 0.8809966
Zero 75M: April 22nd, 2020 0.02161429 discount factor 0.871961
Zero 78M: July 22nd, 2020 0.02237673 discount factor 0.86286249
Zero 81M: October 22nd, 2020 0.02311232 discount factor 0.85363191
Zero 84M: January 22nd, 2021 0.023811523 discount factor 0.84440085
Zero 87M: April 22nd, 2021 0.02446009 discount factor 0.83539584
Zero 90M: July 22nd, 2021 0.025082903 discount factor 0.82632311
Zero 93M: October 22nd, 2021 0.025682361 discount factor 0.81718326
Zero 96M: January 22nd, 2022 0.026254993 discount factor 0.80807288
Zero 99M: April 22nd, 2022 0.026792146 discount factor 0.79918649
Zero 102M: July 22nd, 2022 0.027312938 discount factor 0.79023702
Zero 105M: October 22nd, 2022 0.027816886 discount factor 0.78123845
Zero 108M: January 22nd, 2023 0.028298407 discount factor 0.77230157
Zero 111M: April 22nd, 2023 0.028748215 discount factor 0.76362822
Zero 114M: July 22nd, 2023 0.029182995 discount factor 0.75493055
Zero 117M: October 22nd, 2023 0.029603684 discount factor 0.7462105
Zero 120M: January 22nd, 2024 0.030007023 discount factor 0.73756241
Zero 123M: April 22nd, 2024 0.030390789 discount factor 0.72907418
Zero 126M: July 22nd, 2024 0.030760488 discount factor 0.7206518
Zero 129M: October 22nd, 2024 0.031120285 discount factor 0.71220891
Zero 132M: January 22nd, 2025 0.031466383 discount factor 0.70384311
Zero 135M: April 22nd, 2025 0.03179203 discount factor 0.69573782
Zero 138M: July 22nd, 2025 0.032108624 discount factor 0.68762516
Zero 141M: October 22nd, 2025 0.032416082 discount factor 0.67951111
Zero 144M: January 22nd, 2026 0.032711196 discount factor 0.67148821
Zero 147M: April 22nd, 2026 0.03298828 discount factor 0.66373031
Zero 150M: July 22nd, 2026 0.03325709 discount factor 0.65597933
Zero 153M: October 22nd, 2026 0.033517587 discount factor 0.6482401
Zero 156M: January 22nd, 2027 0.033767097 discount factor 0.64059972
Zero 159M: April 22nd, 2027 0.034000878 discount factor 0.63322212
Zero 162M: July 22nd, 2027 0.034227224 discount factor 0.62586052
Zero 165M: October 22nd, 2027 0.034446139 discount factor 0.61851863
Zero 168M: January 22nd, 2028 0.034655422 discount factor 0.6112781
Zero 171M: April 22nd, 2028 0.034853289 discount factor 0.60421592
Zero 174M: July 22nd, 2028 0.035042398 discount factor 0.59725252
Zero 177M: October 22nd, 2028 0.035225017 discount factor 0.59031249
Zero 180M: January 22nd, 2029 0.035399364 discount factor 0.58347209
Zero 183M: April 22nd, 2029 0.035563263 discount factor 0.57686678
Zero 186M: July 22nd, 2029 0.035723509 discount factor 0.57026567
Zero 189M: October 22nd, 2029 0.035880014 discount factor 0.56367193
Zero 192M: January 22nd, 2030 0.036031083 discount factor 0.55715903
Zero 195M: April 22nd, 2030 0.0361737 discount factor 0.5508663
Zero 198M: July 22nd, 2030 0.036312798 discount factor 0.54458294
Zero 201M: October 22nd, 2030 0.036448302 discount factor 0.53831177
Zero 204M: January 22nd, 2031 0.036578751 discount factor 0.53212234
Zero 207M: April 22nd, 2031 0.036701566 discount factor 0.52614657
Zero 210M: July 22nd, 2031 0.036821012 discount factor 0.52018385
Zero 213M: October 22nd, 2031 0.036937028 discount factor 0.51423665
Zero 216M: January 22nd, 2032 0.03704837 discount factor 0.50837069
Zero 219M: April 22nd, 2032 0.037153998 discount factor 0.50264808
Zero 222M: July 22nd, 2032 0.037255241 discount factor 0.49700425
Zero 225M: October 22nd, 2032 0.037353234 discount factor 0.49137804
Zero 228M: January 22nd, 2033 0.037446935 discount factor 0.48583137
Zero 231M: April 22nd, 2033 0.037534539 discount factor 0.4804817
Zero 234M: July 22nd, 2033 0.037619126 discount factor 0.47514882
Zero 237M: October 22nd, 2033 0.037700659 discount factor 0.46983458
Zero 240M: January 22nd, 2034 0.037778282 discount factor 0.46459728
Zero 243M: April 22nd, 2034 0.037850526 discount factor 0.45954754
Zero 246M: July 22nd, 2034 0.037919953 discount factor 0.454515
Zero 249M: October 22nd, 2034 0.037986539 discount factor 0.44950125
Zero 252M: January 22nd, 2035 0.038049596 discount factor 0.4445611
Zero 255M: April 22nd, 2035 0.038107959 discount factor 0.43979867
Zero 258M: July 22nd, 2035 0.038163723 discount factor 0.4350531
Zero 261M: October 22nd, 2035 0.038216873 discount factor 0.43032573
Zero 264M: January 22nd, 2036 0.038266876 discount factor 0.42566807
Zero 267M: April 22nd, 2036 0.038313333 discount factor 0.42112858
Zero 270M: July 22nd, 2036 0.038356897 discount factor 0.41665523
Zero 273M: October 22nd, 2036 0.038398095 discount factor 0.41219887
Zero 276M: January 22nd, 2037 0.038436527 discount factor 0.4078079
Zero 279M: April 22nd, 2037 0.03847154 discount factor 0.40357457
Zero 282M: July 22nd, 2037 0.038504436 discount factor 0.39935562
Zero 285M: October 22nd, 2037 0.038535227 discount factor 0.39515195
Zero 288M: January 22nd, 2038 0.038563634 discount factor 0.39100908
Zero 291M: April 22nd, 2038 0.038589209 discount factor 0.38701395
Zero 294M: July 22nd, 2038 0.038612933 discount factor 0.38303127
Zero 297M: October 22nd, 2038 0.038634831 discount factor 0.37906173
Zero 300M: January 22nd, 2039 0.038654725 discount factor 0.37514819
Zero 303M: April 22nd, 2039 0.038672341 discount factor 0.37137273
Zero 306M: July 22nd, 2039 0.038688389 discount factor 0.36760743
Zero 309M: October 22nd, 2039 0.038702905 discount factor 0.3638528
Zero 312M: January 22nd, 2040 0.038715799 discount factor 0.36014925
Zero 315M: April 22nd, 2040 0.038727052 discount factor 0.35653498
Zero 318M: July 22nd, 2040 0.038736905 discount factor 0.35296826
Zero 321M: October 22nd, 2040 0.038745538 discount factor 0.34940945
Zero 324M: January 22nd, 2041 0.038752931 discount factor 0.34589673
Zero 327M: April 22nd, 2041 0.038759057 discount factor 0.34250378
Zero 330M: July 22nd, 2041 0.038764229 discount factor 0.33911557
Zero 333M: October 22nd, 2041 0.038768509 discount factor 0.33573228
Zero 336M: January 22nd, 2042 0.038771931 discount factor 0.33239012
Zero 339M: April 22nd, 2042 0.03877454 discount factor 0.32915922
Zero 342M: July 22nd, 2042 0.038776529 discount factor 0.32593004
Zero 345M: October 22nd, 2042 0.038777969 discount factor 0.32270261
Zero 348M: January 22nd, 2043 0.038778931 discount factor 0.3195114
Zero 351M: April 22nd, 2043 0.038779504 discount factor 0.31642341
Zero 354M: July 22nd, 2043 0.038779803 discount factor 0.31333398
Zero 357M: October 22nd, 2043 0.038779915 discount factor 0.31024301
Zero 360M: January 22nd, 2044 0.038779931 discount factor 0.3071834
3m Forward Rates...
0 x 3 Fwd : 0.0023653005
3 x 6 Fwd : 0.0021860069
6 x 9 Fwd : 0.0032733606
9 x 12 Fwd : 0.0035647945
12 x 15 Fwd : 0.0047483244
15 x 18 Fwd : 0.0061160423
18 x 21 Fwd : 0.0079262072
21 x 24 Fwd : 0.010099431
24 x 27 Fwd : 0.012675677
27 x 30 Fwd : 0.015534102
30 x 33 Fwd : 0.018265327
33 x 36 Fwd : 0.020877095
36 x 39 Fwd : 0.023402501
39 x 42 Fwd : 0.025411231
42 x 45 Fwd : 0.027324354
45 x 48 Fwd : 0.029161396
48 x 51 Fwd : 0.030885983
51 x 54 Fwd : 0.032502315
54 x 57 Fwd : 0.034029417
57 x 60 Fwd : 0.035449091
60 x 63 Fwd : 0.036735406
63 x 66 Fwd : 0.037905685
66 x 69 Fwd : 0.038978677
69 x 72 Fwd : 0.039942605
72 x 75 Fwd : 0.04078315
75 x 78 Fwd : 0.041496367
78 x 81 Fwd : 0.042085756
81 x 84 Fwd : 0.042545605
84 x 87 Fwd : 0.042886573
87 x 90 Fwd : 0.043199236
90 x 93 Fwd : 0.043522775
93 x 96 Fwd : 0.043869627
96 x 99 Fwd : 0.044231727
99 x 102 Fwd : 0.044550577
102 x 105 Fwd : 0.04481419
105 x 108 Fwd : 0.045020768
108 x 111 Fwd : 0.045176223
111 x 114 Fwd : 0.045317632
114 x 117 Fwd : 0.045461827
117 x 120 Fwd : 0.045614485
120 x 123 Fwd : 0.045792055
123 x 126 Fwd : 0.04596687
126 x 129 Fwd : 0.04611445
129 x 132 Fwd : 0.046235741
132 x 135 Fwd : 0.046330338
135 x 138 Fwd : 0.046400593
138 x 141 Fwd : 0.046448871
141 x 144 Fwd : 0.046475719
144 x 147 Fwd : 0.046482225
147 x 150 Fwd : 0.046470149
150 x 153 Fwd : 0.046440521
153 x 156 Fwd : 0.046394441
156 x 159 Fwd : 0.046334137
159 x 162 Fwd : 0.046260894
162 x 165 Fwd : 0.046174758
165 x 168 Fwd : 0.046077263
168 x 171 Fwd : 0.045970816
171 x 174 Fwd : 0.045856891
174 x 177 Fwd : 0.045735577
177 x 180 Fwd : 0.04560813
180 x 183 Fwd : 0.045541077
183 x 186 Fwd : 0.045530178
186 x 189 Fwd : 0.045508462
189 x 192 Fwd : 0.045476174
192 x 195 Fwd : 0.045434309
195 x 198 Fwd : 0.045383208
198 x 201 Fwd : 0.045322345
201 x 204 Fwd : 0.045252216
204 x 207 Fwd : 0.045174418
207 x 210 Fwd : 0.045089064
210 x 213 Fwd : 0.044995071
213 x 216 Fwd : 0.044893149
216 x 219 Fwd : 0.044784786
219 x 222 Fwd : 0.044670457
222 x 225 Fwd : 0.044549284
225 x 228 Fwd : 0.044421557
228 x 231 Fwd : 0.044289787
231 x 234 Fwd : 0.044153728
234 x 237 Fwd : 0.044011474
237 x 240 Fwd : 0.043864071
240 x 243 Fwd : 0.043714334
243 x 246 Fwd : 0.043561893
246 x 249 Fwd : 0.043404574
249 x 252 Fwd : 0.043243543
252 x 255 Fwd : 0.043081824
255 x 258 Fwd : 0.04291895
258 x 261 Fwd : 0.042752583
261 x 264 Fwd : 0.042583974
264 x 267 Fwd : 0.042415333
267 x 270 Fwd : 0.042247049
270 x 273 Fwd : 0.042077651
273 x 276 Fwd : 0.041907517
276 x 279 Fwd : 0.041739792
279 x 282 Fwd : 0.041573917
282 x 285 Fwd : 0.04140752
285 x 288 Fwd : 0.041241923
288 x 291 Fwd : 0.041080184
291 x 294 Fwd : 0.040921743
294 x 297 Fwd : 0.040764365
297 x 300 Fwd : 0.040609354
300 x 303 Fwd : 0.040459583
303 x 306 Fwd : 0.040314529
306 x 309 Fwd : 0.040172185
309 x 312 Fwd : 0.04003381
312 x 315 Fwd : 0.039901286
315 x 318 Fwd : 0.039774917
318 x 321 Fwd : 0.039653689
321 x 324 Fwd : 0.039538069
324 x 327 Fwd : 0.03943026
327 x 330 Fwd : 0.039329909
330 x 333 Fwd : 0.039235765
333 x 336 Fwd : 0.039148896
336 x 339 Fwd : 0.039071023
339 x 342 Fwd : 0.039001926
342 x 345 Fwd : 0.038940882
345 x 348 Fwd : 0.038888814
348 x 351 Fwd : 0.03884686
351 x 354 Fwd : 0.038814969
354 x 357 Fwd : 0.038793041
357 x 360 Fwd : 0.038781823
360 x 363 Fwd : 0.03858163
From: Guan Wang [mailto:[hidden email]]
Sent: 11 June 2015 21:47
To: [hidden email]
Subject: [Quantlib-users] Piecewise Yield Curve Errors
Hi,
I am trying to build a yield curve using the following inputs:
USD Libor 1m, 3m
EDF prices (12 of them, 3m apart, let's suppose convexity adjustment is zero)
Swap rates (5yr to 50yr)
To be able to interpolate with swap rates, I have to set my calendar to be the joint calendar of US and UK. Theses are the errors I am getting:
For pricing date 1/17/2014:
negative time (-0.00277778) given
For pricing date 2/13/2014:
interpolation range is [0.0777778, 7.10278]: extrapolation at 0.075 not allowed
To avoid out of range errors, I also have to enable extrapolation for the yield curve builder.
Can anybody help me with this? The stand alone code is as follows:
#include <ql/quantlib.hpp>
#include <stdio.h>
#include <iostream>
#include <fstream>
#include <sstream>
#include <ql/termstructures/yield/ratehelpers.hpp>
using namespace std;
using namespace QuantLib;
using namespace boost;
void testPiecewiseCurve(int yyyymmdd);
int main(int argc, char* argv[])
{
int yyyymmdd = 20140117;
try {
testPiecewiseCurve(yyyymmdd);
}
catch (std::exception& e) {
cout << "Couldn't build yield curve: " << e.what() << endl;
}
return 0;
}
struct Datum {
int n;
TimeUnit units;
Rate rate;
};
struct EDFDatum {
Date expiry;
Real price;
Rate convexityAdj;
};
Datum depositData[] = {
{ 1, Months, 0.157 },
{ 3, Months, 0.2366 }
};
EDFDatum edfData[] = {
{ Date(41715), 99.75, 0.00 },
{ Date(41806), 99.71, 0.00 },
{ Date(41897), 99.66, 0.00 },
{ Date(41988), 99.575, 0.00 },
{ Date(42079), 99.445, 0.00 },
{ Date(42170), 99.28, 0.00 },
{ Date(42261), 99.08, 0.00 },
{ Date(42352), 98.84, 0.00 },
{ Date(42443), 98.56, 0.00 },
{ Date(42534), 98.275, 0.00 },
{ Date(42632), 98.00, 0.00 },
{ Date(42723), 97.735, 0.00 }
};
Datum swapData[] = {
{ 5, Years, 1.73377 },
{ 6, Years, 2.074532 },
{ 7, Years, 2.36113 },
{ 8, Years, 2.592213 },
{ 9, Years, 2.781181 },
{ 10, Years, 2.937271 },
{ 15, Years, 3.418712 },
{ 30, Years, 3.742963 },
{ 35, Years, 3.742963 },
{ 40, Years, 3.742963 },
{ 45, Years, 3.742963 },
{ 50, Years, 3.742963 }
};
void testPiecewiseCurve(int yyyymmdd){
Calendar calendar = JointCalendar(UnitedStates(UnitedStates::Settlement), UnitedKingdom(UnitedKingdom::Exchange), JoinHolidays);
int dd = yyyymmdd%100;
int mm = (yyyymmdd/100)%100;
int yyyy = yyyymmdd/10000;
Date pricingDate = calendar.adjust(Date(dd , Month(mm), yyyy));
Date zeroDate = calendar.advance (pricingDate , 2 , Days );
vector<boost::shared_ptr<SimpleQuote> > rates, prices;
vector <boost::shared_ptr < RateHelper >> instruments;
Size libors = 2;
Size edfs = 12 ;
Size swaps = 12;
instruments = std::vector<boost::shared_ptr<RateHelper> >(libors + edfs + swaps);
rates = vector<boost::shared_ptr<SimpleQuote> >(libors + swaps);
prices = vector<boost::shared_ptr<SimpleQuote> >(edfs);
for (Size i=0; i<libors; i++) {
rates[i] = boost::shared_ptr<SimpleQuote>(new SimpleQuote(depositData[i].rate/100));
}
for (Size i=0; i<edfs; i++) {
prices[i] = boost::shared_ptr<SimpleQuote>(new SimpleQuote(edfData[i].price));
}
for (Size i=0; i<swaps; i++) {
rates[i+libors] = boost::shared_ptr<SimpleQuote>(new SimpleQuote(swapData[i].rate/100));
}
Settings::instance().evaluationDate() = pricingDate;
//For USD Libor Swap, the fixed leg frequency is semiannual
Frequency fixedLegFrequency = Semiannual;
//For USD Libor Swap, the fixed leg convention is modified following
//Modified Following: Choose the first business day after the given holiday unless it belongs to a different month,
//in which case choose the first business day before the holiday.
BusinessDayConvention fixedLegConvention = ModifiedFollowing;
//For USD Libor Swap, the fixed leg day counter is 30/360
DayCounter fixedLegDayCounter = Thirty360();
boost::shared_ptr<IborIndex> libor1m(new USDLibor(1*Months));
boost::shared_ptr<IborIndex> libor3m(new USDLibor(3*Months));
boost::shared_ptr<IborIndex> libor6m(new USDLibor(6*Months));
Handle<Quote> r0(rates[0]);
instruments[0] = boost::shared_ptr<RateHelper>(new DepositRateHelper(r0, 1*Months, libor1m->fixingDays(), calendar,
libor1m->businessDayConvention(),
libor1m->endOfMonth(),
libor1m->dayCounter()));
Handle<Quote> r1(rates[1]);
instruments[1] = boost::shared_ptr<RateHelper>(new DepositRateHelper(r1, 3*Months, libor3m->fixingDays(), calendar,
libor3m->businessDayConvention(),
libor3m->endOfMonth(),
libor3m->dayCounter()));
for (Size i=0; i<edfs; i++) {
Handle<Quote> p(prices[i]);
Date immDate = IMM::nextDate(edfData[i].expiry);
//EDF prices should be convexity adjusted
boost::shared_ptr<Quote> convexity(new SimpleQuote(edfData[i].convexityAdj/10000.0));
instruments[i+libors] = boost::shared_ptr<RateHelper>(new FuturesRateHelper(p, immDate, 3, calendar,
libor3m->businessDayConvention(),
libor3m->endOfMonth(),
libor3m->dayCounter(),
Handle<Quote>(convexity)));
}
for (Size i=0; i<swaps; i++) {
Handle<Quote> r(rates[i+libors]);
instruments[i+libors+edfs] = boost::shared_ptr<RateHelper>(new SwapRateHelper(r, swapData[i].n*swapData[i].units, calendar,
fixedLegFrequency, fixedLegConvention, fixedLegDayCounter, libor3m));
}
Cubic myCubic(CubicInterpolation::Spline, true,
CubicInterpolation::SecondDerivative, 0.0,
CubicInterpolation::SecondDerivative, 0.0);
DayCounter dc= Actual360 ();
cout << "zero date is " << zeroDate << endl;
boost::shared_ptr <QuantLib::YieldTermStructure> yieldCurve = boost::shared_ptr < YieldTermStructure >( new PiecewiseYieldCurve < ZeroYield , Cubic, IterativeBootstrap >( zeroDate , instruments , dc, myCubic));
yieldCurve -> enableExtrapolation();
Handle < YieldTermStructure > ycHandle ( yieldCurve );
boost::shared_ptr < IborIndex > libor3m_new ( new USDLibor ( Period (3, Months ), ycHandle ));
cout << "Checking estimated rates against input..." << endl;
Real tolerance = 1.0e-7;
// Check Results
// Check deposits
for (Size i=0; i<libors; i++) {
//USDLibor index(depositData[i].n*depositData[i].units, ycHandle);
Libor index("USDLibor", depositData[i].n*depositData[i].units, 2,
USDCurrency(),
calendar,
Actual360(), ycHandle);
Rate inputRate = depositData[i].rate/100,
estimatedRate = index.fixing(pricingDate);
if (std::fabs(estimatedRate - inputRate) > tolerance)
cout << depositData[i].n*depositData[i].units
<< " Deposit:"
<< setprecision(8)
<< "\n\t estimated rate: " << estimatedRate
<< "\n\t input rate: " << inputRate
<< endl;
}
// Check swap rate
for (Size i=0; i<swaps; i++) {
Period tenor = swapData[i].n*swapData[i].units;
// construct a vanilla swap
VanillaSwap swap = MakeVanillaSwap (tenor, libor3m_new)
. withEffectiveDate (zeroDate)
. withFixedLegConvention (ModifiedFollowing)
. withFixedLegTenor (6*Months);
Rate inputRate = swapData[i].rate/100,
estimatedRate = swap.fairRate();
if (std::fabs(estimatedRate - inputRate) > tolerance)
cout << tenor <<" Swap :" << setprecision(8)
<< "\n\t estimated rate: "<< estimatedRate
<< "\n\t input rate: "<< inputRate
<< endl ;
}
cout << "Zero-yield Rates..."<< endl;
for (int i=0; i<=120; i++){
Rate zeroRate = yieldCurve -> zeroRate ( zeroDate + 3*i* Months ,dc , Continuous );
DiscountFactor discountFactor = yieldCurve -> discount( zeroDate + 3*i* Months );
cout << " Zero " << 3*i << "M: " << zeroDate +3*i* Months<< " " << zeroRate << " discount factor " << discountFactor << endl ;
}
cout << "\n3m Forward Rates..."<< endl;
for (int i=0; i<=120; i++){
Date d1= zeroDate +3*i* Months, d2=d1 +3* Months ;
Rate forwardRate = yieldCurve -> forwardRate (d1 ,d2 ,dc , Continuous );
cout << 3*i << " x " << 3*i + 3 << " Fwd : " << forwardRate<< endl ;
}
}
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