Probability for Finance (Mastering Mathematical Finance) Paperback – Illustrated, 21 Nov. 2013

Students and instructors alike will benefit from this rigorous, unfussy text, which keeps a clear focus on the basic probabilistic concepts required for an understanding of financial market models, including independence and conditioning. Assuming only some calculus and linear algebra, the text develops key results of measure and integration, which are applied to probability spaces and random variables, culminating in central limit theory. Consequently it provides essential prerequisites to graduate-level study of modern finance and, more generally, to the study of stochastic processes. Results are proved carefully and the key concepts are motivated by concrete examples drawn from financial market models. Students can test their understanding through the large number of exercises and worked examples that are integral to the text. Contents: Preface; 1. Probability space; 2. Probability distributions and random variables; 3. Product measure and independence; 4. Conditional expectation; 5. Sequences of random variables; Index.