QuantLib - Re: Barrier options

Re: Barrier options

Posted by Yannis on Jan 24, 2017; 1:05pm
URL: http://quantlib.414.s1.nabble.com/Barrier-options-tp17983p17990.html

You 're welcome!

I am not the author of BarrierOption, but I believe QuantLib can only price barrier options with european exercise rights, a fact that makes all such products treatable with an analytic solution, to the extent their underlying pays no discrete dividends.

The case where the option's underlying pays discrete dividends is different. In such a case you need to resort to the DividendBarrierOption class and price it using FdBlackScholesBarrierEngine or FdHestonBarrierEngine. Both of these engines are discrete methods based on finite differences and there exist no alternative analytic engine that can do the job.

Hope that helps,

Yannis

Mariano Zeron <[hidden email]> schrieb am 9:37 Dienstag, 24.Januar 2017:

Hi Yannis,

Thanks a lot for your quick response. I've done what you suggested and now I can use the Monte Carlo engine for barrier options using

boost::shared_ptr<PricingEngine> barrierEngineMC = MakeMCBarrierEngine<PseudoRandom, GeneralStatistics>(bsmProcess)

.withSteps(timeSteps)

.withSamples(nSamples);

Ended up using this as MCBarrierEngine needed every single parameter (non seem to be defined by default) and that was giving me problems.

Do you know by any chance which of the barrier options offered in Quantlib cannot be priced using an analytic solution? So far I had been using BarrierOption, but this type of product can be priced using an analytic engine.

All the best

Mariano

2017-01-22 7:39 GMT+00:00 Yannis [via QuantLib] <[hidden email]>:

Hi Mariano,

Try replacing RandomSequenceGenera tor<MersenneTwisterUniformRng> with either PseudoRandom or PoissonPseudoRandom for normally or exponentially distributed random number generator. Both use MersenneTwisterUniformRng since they are defined as follows:

typedef GenericPseudoRandom< MersenneTwisterUniformRng, InverseCumulativeNormal> PseudoRandom;
typedef GenericPseudoRandom< MersenneTwisterUniformRng, Inv erseCumulativePoisson> PoissonPseudoRandom;

Regards
Yannis

Mariano Zeron <[hidden email]> schrieb am 9:35 Sonntag, 22.Januar 2017:

Hi,

I'm interested in pricing a barrier option not using an analytic solution,
for example through a Monte Carlo simulation. I found MCBarrierEngine but so
far I have had problems using it.

I seem to have a problem passing the right template argument list. I tried

boost::shared_ptr< PricingEngine> barrierEngineMC(
new MCBarrierEngine< RandomSequenceGenerator< MersenneTwisterUniformRng>,
GeneralStatistics>(bsmProcess, timeSteps, 24, true, true, nSamples,
0.000001, nSamples + 10000, false, 42));

There are quite a few errors all of them related to the use of

RandomSequenceGenerator< MersenneTwisterUniformRng>

for example (I can pass all if needed):

'rsg_type' : is not a member of
'QuantLib:: RandomSequenceGenerator< QuantLib:: MersenneTwisterUniformRng>'

What is the right way of using this engine? As a side question but directly
related to what I need, can this engine be used to price single barrier
options (which I can price using the analytic pricer) or is this engine
restricted to more exotic barriers?

Thanks in advance!

Mariano

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