Product Description

Stochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional Master's program in Computational Finance. The content of this book has been used successfully with students whose mathematics background consists of calculus and calculus-based probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a self-contained treatment of the probability theory needed for stochastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes. This book is being published in two volumes. This second volume develops stochastic calculus, martingales, risk-neutral pricing, exotic options and term structure models, all in continuous time. Master's level students and researchers in mathematical finance and financial engineering will find this book useful.

Product Details

• Amazon Sales Rank: #136993 in Books
• Published on: 2008-06-19
• Original language: English
• Number of items: 2
• Binding: Hardcover
• 550 pages

About the Author
Steven E. Shreve is Co-Founder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education.

Customer Reviews

One of the best books on Financial Mathematics in continuous time
One my friend gave me the book some years ago. Since that, I recommend it as the first book for those who want to deeply understand results in continuous time Finance, but perhaps have no deep knowledge in Probability and Random Processes.

The book gives a short, but sufficient introduction to continuous time stochastic calculus (basics of Probability, sigma fields (needed to model information flow), change of measure, Brownian motion, Ito integral and the famous formula, stochastic differential equations (SDE)) and passes to the results in Finance. It gives both main approaches to pricing: as expectation with respect to a risk-neutral measure and as a solution of an SDE. Moreover, the author considers not only European contingent claims, but also American and exotic options. He gives a very good introduction to the interest rate models. Models with jumps are also included.

It is very comfortable to read the book due to the clarity of the exposition and numerous examples. The exercises at the end of each topic in the most part are computational, what is very good for those who intend to implement the theory, but perhaps is not very good for mathematicians (there is a small number of problems you can solve just in mind during your way to home). I read the book with pleasure and take many things from it for the courses I conduct at the Moscow State University. Many thanks to the author for the book!