Back of the Envelope

Observations on the Theory and Empirics of Mathematical Finance

[WP] Derivatives pricing using QuantLib

with 8 comments

My colleague and I have a new paper introducing QuantLib for pricing derivatives in practice. Here is the abstract:

Given the complexity of over-the-counter derivatives and structured products, almost all of derivatives pricing today is based on numerical methods. While large financial institutions typically have their own team of developers who maintain state-of-the-art financial libraries, till a few years ago none of that sophistication was available for use in teaching and research. For the last decade, there is now a reliable C++ open-source library available called QuantLib. This note introduces QuantLib for pricing derivatives and documents our experience using QuantLib in our course on Computational Finance at the Indian Institute of Management Ahmedabad. The fact that it is also available (and extendable) in Python has allowed us to harness the power of C++ with the ease of iPython notebooks in the classroom as well as for student’s projects.

As always, comments welcome.


Written by Vineet

April 3, 2015 at 7:18 pm

8 Responses

Subscribe to comments with RSS.

  1. […] 9. Anaconda for Python: For installing Anaconda for Python, I quote from our recent working paper: […]

  2. Hello,
    thanks for sharing this. The use of QuantLib for teaching and research was one of the original objectives of the library, and we haven’t had much feedback on that. (In fact, I’d be very interested to know how your students reacted to it.) Also, if you don’t mind, I’d like to link to your paper from the QuantLib site. Is there any particular way I should cite it?

    A few notes on the paper, in case you have the occasion to revise it:
    – while we started it, attributing QuantLib to the efforts of just me and Ametrano is hardly fair to all those that contributed: about one hundred people, some of them with substantial contributions. I would reword a bit the introduction and section 3.1 to acknowledge their work.
    – in section 3.1 you report the first package as having been released in 2004. That’s incorrect. The first release, version 0.1.1, was in December 2000, shortly after we started working on the library.
    – The old address still works, but the address of my blog is now just .

    Finally: if you contributed the patch in appendix C, I’d be happy to include it into the next release.



    April 4, 2015 at 9:57 pm

    • Thanks Luigi for your comments. We’ll correct the errors and get the paper updated on the site shortly. Btw, in your comment, the new address of your blog is missed.

      Please feel free to link our paper (no particular way, really), our pleasure 🙂


      April 4, 2015 at 10:31 pm

  3. Thanks Luigi. Paper is now updated on the site and so is the download link in the post. Welcome any other comments.


    April 10, 2015 at 2:29 pm

  4. Hey Vineet
    Thanks for sharing this article. I have been writing a series of blog posts on using QuantLib and IPython:

    Thought this might be of interest to you and your students.



    December 23, 2015 at 8:57 pm

    • Thanks Goutham for the link. That should be useful.


      December 30, 2015 at 7:36 pm

  5. […] program covering topics on derivatives pricing and computational finance using Python and QuantLib. The program begins in the 3rd week of January. If you’d like to join or are interested […]

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )


Connecting to %s

%d bloggers like this: