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

[Daniel <gr...@gm...>]

Peter,
Thank you for your reply.
Just want to make sure overwriting T means I should change below statement
      model  = ql.Gsr(term_structure,stepDates, sigmas,reversions,T=60);
to use some other T value instead, am I right?
Two questions:
1. What is the meaning of T here?
2. What is the unit for T (month, year)?
3. If my calibrated swaption has a maximum 30Y x 30Y matrix, what is the T
value I should use?

Thanks,
Mark


On Tue, Aug 23, 2022 at 1:30 PM Peter Caspers <pca...@gm...>
wrote:

> 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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>>>>
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