Re: [Quantlib-users] LD Path Generator in QL-Python for multi-factor processes

[Jack G <jac...@gm...>]

Luigi,

Thanks for the pointer. It seems as though the only multi-path generator
that is currently exposed via SWIG is for pseudorandoms only (
https://github.com/lballabio/QuantLib-SWIG/blob/master/SWIG/montecarlo.i).

I have the feeling that I should be adding the following to expose a
multi-path generator for low discrepancy numbers, but for some reason this
is upsetting my SWIG build (the error I get is "gcc: fatal error: Killed
signal terminated program cc1plus" which I usually see when I add something
subtly bad)... am I thinking on the right lines here?

*%{*
*typedef
QuantLib::MultiPathGenerator<GaussianLowDiscrepancySequenceGenerator>*
*    GaussianMultiPathSobolGenerator;*
*%}*
*class GaussianMultiPathSobolGenerator {*
*  public:*
*    %extend {*
*      GaussianMultiPathSobolGenerator(*
*                   const ext::shared_ptr<StochasticProcess>& process,*
*                   const std::vector<Time>& times,*
*                   const GaussianLowDiscrepancySequenceGenerator&
generator,*
*                   bool brownianBridge = false) {*
*          return new GaussianMultiPathSobolGenerator(process,*
*                                                     QuantLib::TimeGrid(*
*                                                         times.begin(),*
*                                                         times.end()),*
*                                                     generator,*
*                                                     brownianBridge);*
*      }*
*    }*
*    Sample<MultiPath> next() const;*
*    Sample<MultiPath> antithetic() const;*
*};*

Best,
Jack

On Fri, Nov 27, 2020 at 4:35 PM Luigi Ballabio <lui...@gm...>
wrote:

> Hello Jack,
>     the Heston process is two-dimensional (it models both underlying and
> vol) so you'll need to use a multi-path generator.  The error you're
> getting is the generator trying to cast the process to a one-dimensional
> one and failing.
>
> Luigi
>
>
> On Fri, Nov 27, 2020 at 4:13 AM Jack G <jac...@gm...> wrote:
>
>> Dear QL Users,
>>
>> I'm getting a slightly cryptic error when I try to manually generate
>> paths for Heston using LD numbers in Python.
>>
>> It works fine for BS:
>>
>> *import QuantLib as ql*
>>
>> *initialValue = ql.QuoteHandle(ql.SimpleQuote(100))*
>> *sigma = 0.2*
>>
>> *today = ql.Date().todaysDate()*
>> *riskFreeTS = ql.YieldTermStructureHandle(ql.FlatForward(today, 0.0,
>> ql.Actual365Fixed()))*
>> *dividendTS = ql.YieldTermStructureHandle(ql.FlatForward(today, 0.0,
>> ql.Actual365Fixed()))*
>> *volTS = ql.BlackVolTermStructureHandle(ql.BlackConstantVol(today,
>> ql.NullCalendar(), sigma, ql.Actual365Fixed()))*
>> *process = ql.BlackScholesProcess(initialValue, riskFreeTS, volTS)*
>>
>> *times = ql.TimeGrid(1, 12)*
>>
>> *rng = ql.UniformLowDiscrepancySequenceGenerator(12)*
>> *seq = ql.GaussianLowDiscrepancySequenceGenerator(rng)*
>> *path_gen = ql.GaussianSobolPathGenerator(process, times, seq, False)*
>>
>> *x = path_gen.next()*
>>
>>
>> However, when I try the same with Heston, I get the following error: "
>> RuntimeError: Boost assertion failed: px != 0"
>>
>> *v0 = 0.09 kappa = 0.8 theta = 0.09 rho = 0.4 sigma = 0.1 process =
>> ql.HestonProcess(riskFreeTS, dividendTS, initialValue, v0, kappa, theta,
>> sigma, rho) times = ql.TimeGrid(1, 12) rng =
>> ql.UniformLowDiscrepancySequenceGenerator(12) seq =
>> ql.GaussianLowDiscrepancySequenceGenerator(rng) path_gen =
>> ql.GaussianSobolPathGenerator(process, times, seq, False) x =
>> path_gen.next()*
>>
>>
>> My working hypothesis is that the rng needs to be dimension 24 instead of
>> 12 because of the second vol process that needs to be simulated, but when I
>> change the dimension to 24 I get the following error: "RuntimeError:
>> sequence generator dimensionality (24) != timeSteps (12)"
>>
>> I've looked through the QuantLib-SWIG code but not got too far... any
>> pointers about how I might deal with this? Or have I done something stupid
>> somewhere?
>>
>> Thanks,
>> Jack
>>
>>
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>