I need to price an American option on an underlying that follows a rather uncommon stochastic process. To this end, I want to use the StochasticProcess1D class, for which I can specify directly the drift and volatility as a function of the underlying. I have been looking for examples with StochasticProcess1D but I could not find any. Can someone provide me with an example? An example using the Python interface and with a PDE pricing engine would be preferred. Thanks in advance! Sandro PS: I have also posted the question here: http://quant.stackexchange.com/questions/30659/quantlib-stochasticprocess1d-example?noredirect=1#comment41719_30659 |
Hello, writing a specific process in Python is not possible. You can write the process in C++ and add it to the Python interfaces. As for using it in the PDE framework: I don't think that it can translate a generic process into a finite-difference operator automatically (the StochasticProcess interface was designed to use with the Monte Carlo framework instead) so you'll probably be better off writing the operator directly. Unfortunately, there's not a lot of documentation about either the old or the new framework, except my blog posts (search for "Chapter 8" in <http://www.implementingquantlib.com/p/archive.html>). You can start from the examples shown there and post here if you get stuck. Hope this helps, Luigi On Wed, Oct 26, 2016 at 11:51 AM slera <[hidden email]> wrote:
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