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

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

Thank you Peter for your information. I overwrote T to 61, now I can
see runtimeError
is gone.

But I had a new issue of very long calibration time now.
I am calibrating a 13 (maturity) x 13 (tenor) volatility surface, and I am
using constant mean reversions and piecewise constant volatility as below:
stepDates is set at time grid @ [1,2,5,7,10,20] year from the valuation date
reversions = [ql.QuoteHandle(ql.SimpleQuote(0.0001))]
sigmas = [ql.QuoteHandle(ql.SimpleQuote(0.006)) for i in range(0,
len(stepDates)+1)]

In order to expedite calibration, I used low optimization criteria for LM
method and end criteria as below. But I tested below code, the code can
solve low dimension volatility surface(which means the code is working),
but it takes already 6 hours and haven't solved 13X13 volatility surfaces.
Any suggestion to calibrate faster?

model  = ql.Gsr(term_structure,stepDates, sigmas,reversions,61);
engine = ql.Gaussian1dSwaptionEngine(model, 64, 7.0, True, False,
term_structure)
swaptions = create_swaption_helpers(data, index, term_structure, engine)
optimization_method =ql.LevenbergMarquardt(1.0e-2,1.0e-2,1.0e-2)
end_criteria = ql.EndCriteria(1000, 10, 1e-2, 1e-3, 1e-3)
model.calibrate(swaptions, optimization_method, end_criteria)

Thanks,
Mark

On Wed, Aug 24, 2022 at 9:36 AM Peter Caspers <pca...@gm...>
wrote:

> Hi Daniel
>
> yes you'd change T in the ctor call ql.Gsr(...).
>
> 1. T is the maturity of the zero bond P(0, T) used as a numeraire in
> the T-Forward measure
> 2. years
> 3. slightly higher than 60 I'd think to capture day counter /
> convention / lag effects, maybe 61 is sufficient already
>
> Thanks
> Peter
>
>
> On Wed, 24 Aug 2022 at 11:47, Daniel <gr...@gm...> wrote:
> >
> > 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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