http://quantlib.414.s1.nabble.com/Jamshidian-engine-with-start-delay-tp14252p14259.html
For zero days between option and start date the results are identical up to
1E-14, for example the old engine resp. new engine gives
for a 5y into 5y atm swaption vs. Euribor 6m, 3% forward flat yts, 1% volatility and
a start delay of 2 business days applies. We could maybe produce cached
> I'm ok with your extension provided that the new values collapse back to the
> old ones (with a reasonable tolerance) in the case of expiry date being equal
> the value date.
> Is the data you've posted related to this case?
>
> It's a while now I do not work for a vol desk, but I would never underestimate
> the huge difference of analytic vs numerical methods when it comes to
> calibration.
>
> This said I would also add that I'm always amazed how poor the production setup
> is, even in very sophisticated banks. Old models stick around for very long
> time, just because of the huge effort required to update them in production
> systems. The multi-curve framework updates I've seen so far rival with Mary
> Shelley's Frankenstein approach
>
>
> On Sat, May 11, 2013 at 1:37 PM, Peter Caspers <
[hidden email]> wrote:
>
> Hello,
>
> in the JamshidianSwaptionEngine the option expiry date and the value date
> of the underlying swap are handled a bit simplified assuming both dates
> equal (see the warning in the code). Though the impact is usually not very
> big we might want to improve this detail in the library ? See below for a
> possible approach. Thank you Sebastian for our discussions on the topic.
>
> Aside I would be interested whether the Jamshidian method is still in use
> for model calibration in the world of multi curve enhanced models (where by
> enhanced I mean something simple like a static spread correction) because I
> believe the generalization of the method to this setting is not
> straightforward. Also I feel that numerical integration does nearly a just
> as efficient and accurate job and it directly allows for multiple curve
> computations. Or do you ignore multi curve in the calibration phase and
> only adjust the curves for the actual pricing ?
>
> Back to Jamshidian and the start delay. Some theoretical background and
> numerical examples can be found here
>
>
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2246054>
> A possible implementation goes as follows. First we need to provide an
> extended zerobond option method, which we can add to AffineModel in
> model.hpp
>
>
https://github.com/pcaspers/quantlib/commit/> e16b4ea5ffbfe33bd6acd0ee6cb3ecd8a43f72a4
>
> The default implementation uses the same simplification as mentioned above
> ignoring the bond start delay. To improve the pricing in the
> JamshidianEngine we have to overwrite this method in the model
> implementations for which we want it. For the Hull White model I did it
> here
>
>
https://github.com/pcaspers/quantlib/commit/> e8b5912cac2e236fe59a885e8cd1e2ed9243cc47
>
> Finally we have to modify the Jamshidian engine a bit
>
>
https://github.com/pcaspers/quantlib/commit/> 019f37a498846d9a6e89a897300f126c01d6ef86
>
> (maybe we should keep some warning in the code because you are not forced
> to support the start delay in your model implementations)
>
> Not suprisingly the test suite breaks when comparing computation results to
> cached values computed with the simplified engine, so the cached values
> should be updated (given that we believe in the new engine)
>
> 1> Testing Hull-White calibration against cached values...
> 1> shortratemodels.cpp(126): error in
> "QuantLib::detail::quantlib_test_case(&
> ShortRateModelTest::testCachedHullWhite)": Failed to reproduce cached
> calibration results:
> 1> calculated: a = 0.0464041, sigma = 0.00579912, f(a) = 0.1158,
> 1> expected: a = 0.0488565, sigma = 0.00593662, f(a) = 0.121599,
> 1> difference: a = -0.00245242, sigma = -0.000137495, f(a) = -0.00579896,
> 1> end criteria = StationaryFunctionValue
>
> regards
> Peter
>
>
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