Product Description

This book is a final year undergraduate text on stochastic processes, a tool used widely by statisticians and researchers working in the mathematics of finance. The book will give a detailed treatment of conditional expectation and probability, a topic which in principle belongs to probability theory, but is essential as a tool for stochastic processes. Although the book is a final year text, the author has chosen to use exercises as the main means of explanation for the various topics, and the book will have a strong self-study element. The author has concentrated on the major topics within stochastic analysis: Stochastic Processes, Markov Chains, Spectral Theory, Renewal Theory, Martingales and Itô Stochastic Processes.

Product Details

• Amazon Sales Rank: #49073 in Books
• Published on: 1998-10-01
• Original language: English
• Number of items: 1
• Binding: Paperback
• 200 pages

Review
This is probably one of the best books to begin learning about the sometimes complex topic of stochastic calculus and stochastic processes from a more mathematical approach. Some literature are often accused of unnecessarily complicating the subject when applied to areas of finance. With this book you are allowed to explore the rigorous side of stochastic calculus, yet maintain a physical insight of what is going on. The authors have concentrated on the most important and useful topics that are encountered in common physical and financial systems --www.quantnotes.com

Customer Reviews

Solid Introduction to applied probability and stochastics
I have extensively used this book for a course on stochastic analysis...The exercises and examples really helped to fully understand the theory. I suggest to read it in conjunction with D. Williams book or Jacod-Protter. The book assumes, anyway, some prerequistes on applied probability, even if the first two chapters are devoted to fix some of these concepts in view of the later chapters.

Superb support if you know some measure theory
This book is a boon for the non-mathematician financial quant, providing the reader knows some concepts of measure-theoretic probability. The idea of conditional expectation, which is the backbone of the theory of stochastic processes, is developed in considerable detail, which provides an excellent preparation for the study of martingales, Markov chains and Brownian motion in the subsequent chapters. There are numerous exercises scattered all over the chapters with full solutions at chapter ends. Although it does not provide the level of detail that one would get in a book like Oksendal, it certainly reduces the cost of entry into the difficult world of stochastic analysis for the non-mathematician. The only prerequisite is some knowledge of measure-theoretic ideas like Borel sets and Lebesgue measure.

Very good introduction to stochastics
The book fulfils it title - I think it's a very good introduction to this area. It grounds stochastic processes in probability, and is consequently self-contained. The examples and exercises (with worked solutions) really helped me understand the theory.