Re: [Quantlib-users] how to calibrate GSR model based on european swaption vol surface

[Peter C. <pca...@gm...>]

Hi

the GSR model operates in the T-forward measure with T=60 by default. You
can overwrite T in the constructor if longer horizons are needed (as it
appears to be the case in your setup).

Best
Peter


Daniel <gr...@gm...> schrieb am Mo. 22. Aug. 2022 um 21:25:

> Thank you Dmitri for your information. Actually I increased the vol
> surface number to more than to be calibration volatility number, now I can
> solve for mean reversion and volatility now.
>
> But  experience another error when I tried to change the yield curve and
> volatility surface to some other type, I got below error.
>
> ---> 14 model.calibrate(swaptions, optimization_method, end_criteria)
>
> ~\.conda\envs\tf-gpu\lib\site-packages\QuantLib\QuantLib.py in calibrate(self, *args)          def calibrate(self, *args):>          return _QuantLib.Gsr_calibrate(self, *args)          def setParams(self, params):
> RuntimeError: G(t,w) should be called with (t,w)=(29.9985,60.0055) in Range [0,60].
>
>
> What does this runtimeError mean?
>
>
> Thanks,
>
> Mark
>
>
>
>
>
>
> On Mon, Aug 22, 2022 at 12:50 PM Dmitri Goloubentsev <dm...@ma...>
> wrote:
>
>> Hi Mark,
>>
>>
>> The error is coming from LM optimiser. You should reduce number of points
>> in your vol surface or add more calibration instruments or add some sort of
>> regularisation.
>>
>> Kind regards,
>> Dmitri.
>>
>> On Mon, 22 Aug 2022, 17:26 Daniel, <gr...@gm...> wrote:
>>
>>> All,
>>>
>>> Please forgive me if someone has answered a similar question before.
>>>
>>> I am trying to calibrate interest rate vol surface using GSR (gaussian
>>> short rate model) based on this post
>>>
>>> http://gouthamanbalaraman.com/blog/short-interest-rate-model-calibration-quantlib.html
>>>
>>> and I found a python example for GSR model calibration.
>>> https://github.com/mlungwitz/notebooks/blob/master/GSR_Example.ipynb
>>>
>>> What I tried to do is to calibrate the same european swaption vol
>>> surface in the 1st python example based on 2nd example gsr model
>>> specification, what I added is:
>>> gsr  = ql.Gsr(term_structure,stepDates, sigmas,reversions);
>>> engine = ql.Gaussian1dSwaptionEngine(gsr, 64, 7.0, True, False,
>>> term_structure)
>>> swaptions = create_swaption_helpers(data, index, term_structure, engine)
>>>
>>> optimization_method = ql.LevenbergMarquardt(1.0e-8,1.0e-8,1.0e-8)
>>> end_criteria = ql.EndCriteria(1000, 100, 1e-6, 1e-8, 1e-8)
>>> model.calibrate(swaptions, optimization_method, end_criteria)
>>>
>>> But this will give me this error:
>>>
>>> RuntimeError: less functions (5) than available variables (12)
>>>
>>> Is the error caused by Gaussian1dSwaptionEngine? Should I proceed with Gaussian1dNonstandardSwaptionEngine? What change should I do to make it work ?
>>>
>>>
>>> Thanks,
>>>
>>> Mark
>>>
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