Posted by
Ferghil O'Rourke on
URL: http://quantlib.414.s1.nabble.com/Problem-with-impliedVolatility-using-DividendEngine-tp4479p4482.html
Hi, thanks for the reply.
I tried passing 0.0 as the dividend payment but even then I still get
the interpolate error. Might this indicate that the problem is with the
other parameters? That would seem strange as all the other params
except the Date vector work fine with the regular engine. The date
vector is just a regular vector of quantlib Date objects.
Also, in the Quantlib version I have there is no
AnalyticEuropeanDividendEngine or FdEuropeanDividendEngine. How do
I get those? The second one I will need actually, as my client wants
to be able to price European options using Black Scholes but
incorporating dividends.
Again, thanks for the help.
-----Original Message-----
From:
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[mailto:
[hidden email]] On Behalf Of Joseph Wang
Sent: Wednesday, February 15, 2006 12:40 AM
To:
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Cc:
[hidden email]
Subject: [Quantlib-users] Re: Problem with impliedVolatility using
DividendEngine
I'll try to take a look at this this weekend. My guess is that the dividend
engine does a lot of shift of the grid so the pricing might be off the grid
that the dividend engine is expecting.
In the mean time can you try the following
1) Run the experiment with AnalyticEuropeanDividendEngine
if it fails - that probably means that the problem is the in the input
parameters
if it works then
2) Run the experiment with the FdEuropeanDividendEngine
Something else you can do is to vary the size of the dividend (i.e. set the
dividend at zero and see if it works, then increase till it fails)
One thing that you should be aware of is that the FD dividend engine in
0.3.11
does discounting in a way that results in different answers from the
analytic
european engine and most classic treatments (i.e. Hull). 0.3.12 will have
two different dividend engines.
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