Text
Mathematics for finance : an Introduction to financial engineering 2nd ed
True to its title, this book itself is an excellent financial investment. For the price
of one volume it teaches two Nobel Prize winning theories, with plenty more
included for good measure. How many undergraduate mathematics textbooks
can boast such a claim?
Building on mathematical models of bond and stock prices, these two theories lead in different directions: Black–Scholes arbitrage pricing of options and
other derivative securities on the one hand, and Markowitz portfolio optimisation and the Capital Asset Pricing Model on the other hand. Models based on
the principle of no arbitrage can also be developed to study interest rates and
their term structure. These are three major areas of mathematical finance, all
having an enormous impact on the way modern financial markets operate. This
textbook presents them at a level aimed at second or third year undergraduate
students, not only of mathematics but also, for example, business management,
finance or economics.
The contents can be covered in a one-year course of about 100 class hours.
Smaller courses on selected topics can readily be designed by choosing the
appropriate chapters. The text is interspersed with a multitude of worked examples and exercises, complete with solutions, providing ample material for
tutorials as well as making the book ideal for self-study.
Prerequisites include elementary calculus, probability and some linear algebra. In calculus we assume experience with derivatives and partial derivatives,
finding maxima or minima of differentiable functions of one or more variables,
Lagrange multipliers, the Taylor formula and integrals. Topics in probability
include random variables and probability distributions, in particular the binomial and normal distributions, expectation, variance and covariance, conditional probability and independence. Familiarity with the Central Limit Theorem would be a bonus. In linear algebra the reader should be able to solve systems of linear equations, add, multiply, transpose and invert matrices, and
compute determinants. In particular, as a reference in probability theory we
recommend our book: M. Capi´nski and T. Zastawniak, Probability Through
Problems, Springer-Verlag, New York, 2001.
In many numerical examples and exercises it may be helpful to use a computer with a spreadsheet application, though this is not absolutely essential.
Microsoft Excel files with solutions to selected examples and exercises are available on our web page at the addresses below.
We are indebted to Nigel Cutland for prompting us to steer clear of an
inaccuracy frequently encountered in other texts, of which more will be said in
Remark 4.1. It is also a great pleasure to thank our students and colleagues for
their feedback on preliminary versions of various chapters.
Readers of this book are cordially invited to visit the web page below to
check for the latest downloads and corrections, or to contact the authors. Your
comments will be greatly appreciated.
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| Tan 510 Cap m | PSB lt.dasar - Pascasarjana | 4 |
| Penerbit | London Springer., 2003 |
|---|---|
| Edisi | - |
| Subjek | - |
| ISBN/ISSN | 9780857290816 |
| Klasifikasi | NONE |
| Deskripsi Fisik | - |
| Info Detail Spesifik | - |
| Other Version/Related | Tidak tersedia versi lain |
| Lampiran Berkas | Tidak Ada Data |