Re: CDS last period
Posted by japari on Nov 19, 2012; 10:03am
URL: http://quantlib.414.s1.nabble.com/CDS-last-period-tp13598p13612.html
Peter, hi, apologies for the long delay, too many hobbies...
The changes you propose on the cds work fine for the bootstrapping of the probabilities but theres a problem when using the cds constructor to instantiate a contract position that way (as opposed to be cds from a helper class): tying a date member at construction time to the (volatile) evaluation date would give problems since the contract characteristics would change on different dates. If we were loading these positions from a database/worksheet that would have undesired results, if the cds were static objects we can only create them on that specific date.
The helpers are already relative date helpers to achieve that behaviour (by recreating the cds).
I have modified the upfront and accrual rebate payments to be separate cashflows and checked for null pointers to determine if they apply.
Have a look and if you want you could merge the changes with yours in your GitHub repo and see what other people here think.
Also, is there a way the 'includeLastDay' option could be set up in the base DayCounter::Impl (false by default) and an extra method 'setToIncludeLastDay' in the concrete dayCtrs (called then at the leg creation). Or something along the lines of moving it to a more generic level, to avoid coding it for every dayCounter
Best regards
Pepe
PS1
These are the tests I run against Mrkit data to check things are working (moving the date up and down a 20thIMM is a good idea). If someone has other test (e.g. Bloombrg) it would be nice to see them.
Testing the curve for US CDS in EUR these are the values in QL and Mrkit for the default probabilities. Some tenors are missing in the bootstrapping of the YTS I have been using:
QL mkit QL(no rebate)
6M 0.0013962 0.001391 0.0015124
1Y 0.0024018 0.002396 0.0025179
2Y 0.0066991 0.006683 0.0068754
3Y 0.0128463 0.012795 0.0130785
4Y 0.0227410 0.022554 0.0230541
5Y 0.0357163 0.035221 0.0361139
7Y 0.0610696 0.059787 0.0615613
10Y 0.1036803 0.100268 0.1042708
15Y 0.1578319 0.152918 0.1584299
20Y 0.1948182 0.192336 0.1953589
As expected the rebate inclusion improves the short term figures (I placed myself on October 10th). Theres still a small discrepancy on the long term tenors; I guess it comes from a different treatment of the YTS
This is using mrkit calculator so these are running only converted quotes ('composite') but another test is to use the tick quotes and, since mrkit gives the conventional alongside the upfront quote on those, test the conventional conversion. The agreement here is within 1bp, this is very good and it is (I believe) because this test has less uncertainty on whether I am doing exactly the same thing.
Yet another test I came about is to compare market composite quotes on bonds, there one has the Zspread from the bond price and the one computed from the CDS. Pricing the risky bond and the composite CDS curve with QL will give you those figures. The agreement I get is within 1% difference, I am not too worried about that since this is more complex a test and I might have done things differently to the way mrkit does.
PS2
Another comment to the cds engines I would make is that they are unable to provide a fair spread for a zero coupon CDS, this would need bypassing the coupon methods when NPV-ing the leg.
Other points for the CDS:
-default lookback not accounted for (the 90 days thing) Important only for risk management, irrelevant for pricing.
-not tied to issuer. Relevant to risk management (no observability mechanism for a jump to default metric).
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URL: http://quantlib.414.s1.nabble.com/CDS-last-period-tp13598p13612.html
Peter, hi, apologies for the long delay, too many hobbies...
The changes you propose on the cds work fine for the bootstrapping of the probabilities but theres a problem when using the cds constructor to instantiate a contract position that way (as opposed to be cds from a helper class): tying a date member at construction time to the (volatile) evaluation date would give problems since the contract characteristics would change on different dates. If we were loading these positions from a database/worksheet that would have undesired results, if the cds were static objects we can only create them on that specific date.
The helpers are already relative date helpers to achieve that behaviour (by recreating the cds).
I have modified the upfront and accrual rebate payments to be separate cashflows and checked for null pointers to determine if they apply.
Have a look and if you want you could merge the changes with yours in your GitHub repo and see what other people here think.
Also, is there a way the 'includeLastDay' option could be set up in the base DayCounter::Impl (false by default) and an extra method 'setToIncludeLastDay' in the concrete dayCtrs (called then at the leg creation). Or something along the lines of moving it to a more generic level, to avoid coding it for every dayCounter
Best regards
Pepe
PS1
These are the tests I run against Mrkit data to check things are working (moving the date up and down a 20thIMM is a good idea). If someone has other test (e.g. Bloombrg) it would be nice to see them.
Testing the curve for US CDS in EUR these are the values in QL and Mrkit for the default probabilities. Some tenors are missing in the bootstrapping of the YTS I have been using:
QL mkit QL(no rebate)
6M 0.0013962 0.001391 0.0015124
1Y 0.0024018 0.002396 0.0025179
2Y 0.0066991 0.006683 0.0068754
3Y 0.0128463 0.012795 0.0130785
4Y 0.0227410 0.022554 0.0230541
5Y 0.0357163 0.035221 0.0361139
7Y 0.0610696 0.059787 0.0615613
10Y 0.1036803 0.100268 0.1042708
15Y 0.1578319 0.152918 0.1584299
20Y 0.1948182 0.192336 0.1953589
As expected the rebate inclusion improves the short term figures (I placed myself on October 10th). Theres still a small discrepancy on the long term tenors; I guess it comes from a different treatment of the YTS
This is using mrkit calculator so these are running only converted quotes ('composite') but another test is to use the tick quotes and, since mrkit gives the conventional alongside the upfront quote on those, test the conventional conversion. The agreement here is within 1bp, this is very good and it is (I believe) because this test has less uncertainty on whether I am doing exactly the same thing.
Yet another test I came about is to compare market composite quotes on bonds, there one has the Zspread from the bond price and the one computed from the CDS. Pricing the risky bond and the composite CDS curve with QL will give you those figures. The agreement I get is within 1% difference, I am not too worried about that since this is more complex a test and I might have done things differently to the way mrkit does.
PS2
Another comment to the cds engines I would make is that they are unable to provide a fair spread for a zero coupon CDS, this would need bypassing the coupon methods when NPV-ing the leg.
Other points for the CDS:
-default lookback not accounted for (the 90 days thing) Important only for risk management, irrelevant for pricing.
-not tied to issuer. Relevant to risk management (no observability mechanism for a jump to default metric).
------------------------------------------------------------------------------
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web console. Get in-depth insight into apps, servers, databases, vmware,
SAP, cloud infrastructure, etc. Download 30-day Free Trial.
Pricing starts from $795 for 25 servers or applications!
http://p.sf.net/sfu/zoho_dev2dev_nov
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