http://quantlib.414.s1.nabble.com/Adding-a-payoff-function-tp2939p2945.html
At the risk of selling my new book C++ and patterns, where we apply POSA and GOF patterns in pricing apps
> -----Original Message-----
> From:
[hidden email]
> [mailto:
[hidden email]]On Behalf Of Neil P
> Firth
> Sent: 26 May 2004 12:01
> To:
[hidden email]
> Subject: Re: [Quantlib-users] Adding a payoff function
>
>
>
> On Wed, 26 May 2004, Luigi Ballabio wrote:
>
> > On 2004.05.19 14:50, Daniel J. Duffy wrote:
> > > I am not familiar with pattern Path; it is not a GOF pattern.
> >
> On the subject of patterns I'd recommend Pattern-Oriented Software
> Architecture vols I and II and www.eaipatterns.com is worth a
> look too.
>
> > Hi,
> > I think he meant that since payoffs can be path-dependent,
> > Payoff::operator() should be allowed to take a path, too.
> > At ths time, our take is that e.g., instead of writing
> >
> > AveragePricePayoff payoff(Call, strike);
> > p = payoff(path);
> >
> > one is probably better off writing
> >
> > PlainVanillaPayoff payoff(Call, strike);
> > p = payoff(averagePrice(path));
> >
> > which has the merit of separating the two concerns of averaging and
> > calculating the payoff.
> >
> This is what I have been doing in the basket option payoffs
> that I have
> been working on.
>
> > The fact that a payoff could be intrinsically dependent on time is
> > another matter, though. Maybe we should augment the signature of
> > Payoff::operator() to take a time argument as well...
> >
> In Monte Carlo regression methods to calculate American
> option prices it
> is necessary to regress on time dependent basis functions. e.g.
> \psi_{i} (X_i) where i indicates time, X_i represents the d asset
> prices at time i, and \psi_{i} is a function from R^d -> R.
>
> One thing that I have been thinking about is how to cleanly design MC
> algorithms that follow the pattern:
>
> : Generate paths forward through time
> : Regress rolling backwards through time (e.g. LSMC estimator)
> : Generate independent paths
> : Generate low and high biased estimates proceeding forwards
> through time
>
> Any ideas welcome!
>
> Neil
>
>
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