The Book
This book covers in a leisurely manner all the standard material that one would want in a full year probability course with a slant towards applications in financial analysis at the graduate or senior undergraduate honors level. It contains a fair amount of measure theory and real analysis built in but it introduces sigma-fields, measure theory, and expectation in an especially elementary and intuitive way. A large variety of examples and exercises in each chapter enrich the presentation in the text.
The Author(s)
John B Walsh is Professor Emeritus at the Department of Mathematics, University of British Columbia, Vancouver, Canada.
Table of Contents
Preface
Introduction
Chapter 1. Probability Spaces
Chapter 2. Random Variables
Chapter 3. Expectations II: The General Case
Chapter 4. Convergence
Chapter 5. Laws of Large Numbers
Chapter 6. Convergence in Distribution and the CLT
Chapter 7. Markov Chains and Random Walks
Chapter 8. Conditional Expectations
Chapter 9. Discrete-Parameter Martingales
Chapter 10. Brownian Motion
Bibliography
Index