Re: [Quantlib-dev] selective model calibration

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

this is even better !
thanks a lot
    Peter


On 24 October 2013 11:30, Luigi Ballabio <lui...@gm...> wrote:

> Yes, it sounds interesting.  I would add the extra vector parameter to
> calculate();
> derived classes might provide functions that return predetermined vectors,
> e.g.,
>
> model->calibrate(helpers, ...,
>  HullWhite::constraints::keep_reversion_fixed())
>
> or
>
> model->calibrate(helpers, ...,
> HullWhite::constraints::move_single_volatility(i));
>
> or something shorter, of course :)
>
> This way, derived classes wouldn't even have to override calibrate().
>
> Later,
>     Luigi
>
>
>
> On Thu, Oct 24, 2013 at 10:36 AM, Roland Lichters
> <rol...@go...> wrote:
> > Hi Peter,
> >
> > that sounds interesting and useful. I keep coming across your first
> case, and I solved it so far by passing a vector of booleans to the model
> constructor and setting up calibration params and indices to them
> accordingly, in each model constructor, without changing QuantLib. It is
> not elegant, but one can select which part of the parameters are calibrated
> and avoid dealing with various copies of the model. I'd be curious to see
> whether this can be achieved with less coding when we change QuantLib as
> you suggest. Your second case didn't even occur to me yet.
> > Can we have a look at a code example? I am also happy to share my
> pedestrian approach if of interest.
> >
> > Regards,
> > Roland
> >
> >
> > On 23 Oct 2013, at 21:37, Peter Caspers <pca...@gm...> wrote:
> >
> >> Hi,
> >>
> >>  I would like to be able to calibrate only a subset of the parameters
> >> of a CalibratedModel instance. Even more I would like to fix a subset of
> >> elements within one multidimensional parameter in some cases. With this
> >> one could e.g.
> >>
> >> - calibrate both reversion and volatilities or fix the reversion and
> >> calibrate only volatilities in a Hull White model
> >>
> >> - calibrate the model volatilities in a Hull White model iteratively to
> >> single interest rate options with ascending option maturities instead
> >> of having to do a global calibration to the whole set (which can be
> >> much slower when you have many options in the calibration basket)
> >>
> >> - easily avoid the redundancy in the piecewise volatlities of a markov
> >> model (multiplying the volatilies by a (non zero) scalar factor does
> >> not change the model up to numeraire recalibration)
> >>
> >> There are probably more use cases. I guess there are workarounds for
> >> most of these cases, but I would like to propose a solution in the
> >> CalibratedModel class itself. Since I am not sure about the design I am
> >> not just sending a pull request but would like to discuss the approach
> >> first. Here is what I would try:
> >>
> >> Add a parameter to the calibrate method specifying the free parameters
> >> in a vector<bool> and defaulting to an empty vector meaning all
> >> parameters are free. Within the method one can make use of the
> >> ProjectedCostFunction then to easily get what we want. One could also
> >> make this calibrate method protected and leave the public interface as
> >> it is, just invoking the new method with the default for the new
> >> parameter. That is probably better because on the level of the
> >> CalibratedModel one does not know the meaning of the parameters and
> >> of their components.
> >>
> >> Again in the protected section, provide an inner class that allows to
> >> construct the above vector<bool> conveniently from specifying parameters
> >> to include or exclude or indices within a parameter to include or
> >> exclude in or from the set of free parameters.
> >>
> >> This does not change anything so far. However derived models can now
> >> easily overwrite the calibrate method (which we would have to make
> >> virtual) and do a specialized calibration as needed / specified in the
> >> concrete models.
> >>
> >> What do you think ?
> >>
> >> regards
> >>  Peter
> >>
> >>
> >>
> >>
> >>
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