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After the publication of the first edition of the book, about five years ago,
I have received a fair number of messages from readers, both students and
practitioners, around the world. The recurring keyword, and the most important
thing to me, was useful. The book had, and has, no ambition of
being a very advanced research book. The basic motivation behind this second
edition is the same behind the first one: providing the newcomer with
an easy, but solid, entry point to computational finance, without too much
sophisticated mathematics and avoiding the burden of difficult C++ code,
also covering relatively non-standard optimization topics such as stochastic
and integer programming. See also the excerpt from the preface to the first
edition. However, there are a few new things here:
0 a slightly revised title;
0 completely revised organization of chapters;
0 significantly increased number of pages.
The title mentions both Finance and Economics, rather than just Finance. To
avoid any misunderstanding, it should be made quite clear that this is essentially
a book for students and practitioners working in Finance. Nevertheless,
it can be useful to Ph.D. students in Economics as well, as a complement to
more specific and advanced textbooks. In the last four years, I have been
giving a course on numerical methods within a Ph.D. program in Economics,
and I typically use other available excellent textbooks covering advanced algorithms'
or offering well-thought MATLAB toolboxes2 which can be used
to solve a wide array of problems in Economics. From the point of view of
my students in such a course, the present book has many deficiencies: For
instance, it does not cover ordinary differential equations and it does not
deal with computing equilibria or rational expectations models; furthermore,
practically all of the examples deal with option pricing or portfolio management.
Nevertheless, given my experience, I believe that they can benefit from
a more detailed and elementary treatment of the basics, supported by simple
examples. Moreover, I believe that students in Economics should also get
'K.L. Judd, Numerical Methods in Economics, MIT Press, 1998.
2M. J. Miranda and P.L. Fackler, Applied Computational Economics and Finance, MIT
Press, 2002.
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