The book has been tested and refined through years of classroom teaching experience. With an abundance of examples, problems, and fully worked out solutions, the text introduces the financial theory and relevant mathematical methods in a mathematically rigorous yet engaging way.
This textbook provides complete coverage of discrete-time financial models that form the cornerstones of financial derivative pricing theory. Unlike similar texts in the field, this one presents multiple problem-solving approaches, linking related comprehensive techniques for pricing different types of financial derivatives.
Key features:
- In-depth coverage of discrete-time theory and methodology.
- Numerous, fully worked out examples and exercises in every chapter.
- Mathematically rigorous and consistent yet bridging various basic and more advanced concepts.
- Judicious balance of financial theory, mathematical, and computational methods.
- Guide to Material.
This revision contains:
- Almost 200 pages worth of new material in all chapters.
- A new chapter on elementary probability theory.
- An expanded the set of solved problems and additional exercises.
- Answers to all exercises.
This book is a comprehensive, self-contained, and unified treatment of the main theory and application of mathematical methods behind modern-day financial mathematics.
Matt T –
Really recommend
JerryB –
The most valuable service I can provide is to explain what folks should buy this two volume set, and what folks should not.
Do NOT buy these books if you have not had all of the following courses: multi-variable calculus, linear algebra, differential equations, probability/statistics, introductory option pricing. The introductory option pricing course should start with a one period binomial model and end up with deriving the Black-Scholes Partial Differential Equation and the Black-Scholes Formula for pricing a put option and a call option.
Furthermore, these books are more mathematically formal than some market practitioners might like. Those who trade options for a living are more concerned with the intricacies of the Greeks –various partial derivatives of the Black-Scholes Formula – and in constructing options that are combinations of various puts and calls.
In the realm of mathematical physics (of which mathematical finance and quantum mechanics are sub-categories) – any topic worth learning is worth learning four or five times over. The first attempt is to “do or die –not to reason why.” The subsequent relearning’s are to gradually learn the “reasons why” from multiply points of view.
Eventually one most confront rather serious mathematics. Our basic notions of the integral and the derivative come from TAKING THE LIMIT of various things. We cannot merely transfer our knowledge of basic calculus to stochastic calculus. Basic calculus deals with paths (curves) that are smooth. The Mean Value theorem was our friend. In Stochastic Calculus the paths are infinitesimally jagged. This arises because the square root of a number between zero and one is greater than the number itself.
In addition the probability theory has to be more mathematically formal – because we are dealing with an infinite set of outcomes — with each element of this set itself being the result of an infinite number of coin flips. This is far more complex than merely looking at the probability of various combinations from a deck of 52 cards. This is handled by imposing a Borel Algebra on the real number line.
These two volumes are great to increase our mathematical sophistication – because they proceed by baby steps and numerous worked–out examples.
For this reason they are less daunting than Shreve Volume 11.