[Quantlib-users] SWIG/examples/isda-cds.py

[Ashwani S. <ash...@gm...>]

Using isda-cds.py
<https://github.com/lballabio/QuantLib-SWIG/blob/master/Python/examples/isda-engine.py>
example to compare with Bloomberg ISDA Standard Upfront Model but the
difference between QL fairUpfront and that from BBG  is much larger than
the precision set. Running just for 40% recovery and 1000 bps case while
looping through 5 maturities (1Y-5Y).

Results (as below):

   Hazard   Upfront  Market Value  Distance  Within tolerance
0    0.17 -1.00e+06      -1003010    554.96             False
1    0.17 -1.68e+06      -1682459    641.48             False
2    0.17 -2.25e+06      -2253350    426.70             False
3    0.17 -2.73e+06      -2727484     62.97             False
4    0.17 -3.12e+06      -3120142    458.70             False
total distance: 2144.81


Anyone who might have tried this, could you please point the obvious
mistake I am committing here? Code attached.

Thanks.