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I'm just starting to work with QuantLib and wonder if I'm going down a very wrong path.

I'm working on a site that presents the visitor with a table of streamed real-time options data, including Theoretical Value calculated by the stream provider. The visitor, as I envision it, is a normal-type casual retail customer.

Yesterday I'm thinking: Hey! Wouldn't it be nice to give the guy access to QuantLib so he can select one of the three (as it seems to me at the moment) option-pricing engines that QuantLib offers? I'm excited! I want to put just as much function as I can into an app. I love this!

Today I installed QuantLib on my win32 machine and started to look around. Come to find out (should be no surprise, I guess) that the three pricing engines deliver prices that differ by only miniscule amounts -- tenths or hundredths of pennies.

I don't believe that the visitor I have in mind cares about nickels and dimes per contract. Maybe the value that QuantLib delivers just does not justify its weight in server-side computation time.

Is it worth my while to integrate QuantLib on my server (a huge PITA)? Or should I just forget about it?


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up vote 5 down vote accepted

Numerical methods are only approximations. So binomial trees, Monte Carlo simulations, and finite difference methods should all produce different numbers.

As for whether you should install it for your customers, that can only be answered by what you think your customers want. Do retail customers really want the potential confusion? Are they going to understand the implications of numerical approximations? What kind of visitors do you want anyway?

This is more of a marketing exercise than anything else. Consider what kind of users you want before building your product.

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I meant that the results differed only by small amounts, so it seemed to me that QuantLib is appropriate for academics and professionals, and not really meaningful for the visitors that I plan for. – Pete Wilson Aug 23 '11 at 19:05

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