Stochastic Financial Models

Developed from the esteemed author’s advanced undergraduate and graduate courses at the University of Cambridge, this text provides a hands-on, sound introduction to mathematical finance. Assuming no prior knowledge of stochastic calculus or measure-theoretic probability, the author includes the relevant mathematical background as well as many exercises with solutions. He first presents the classical topics of utility and the mean-variance approach to portfolio choice. Focusing on derivative pricing, the text then covers the binomial model, the general discrete-time model, Brownian motion, the Black–Scholes model, and various interest-rate models.

Filling the void between surveys of the field with relatively light mathematical content and books with a rigorous, formal approach to stochastic integration and probabilistic ideas, Stochastic Financial Models provides a sound introduction to mathematical finance. The author takes a classical applied mathematical approach, focusing on calculations rather than seeking the greatest generality.

Developed from the esteemed author’s advanced undergraduate and graduate courses at the University of Cambridge, the text begins with the classical topics of utility and the mean-variance approach to portfolio choice. The remainder of the book deals with derivative pricing. The author fully explains the binomial model since it is central to understanding the pricing of derivatives by self-financing hedging portfolios. He then discusses the general discrete-time model, Brownian motion and the Black–Scholes model. The book concludes with a look at various interest-rate models. Concepts from measure-theoretic probability and solutions to the end-of-chapter exercises are provided in the appendices.

By exploring the important and exciting application area of mathematical finance, this text encourages students to learn more about probability, martingales and stochastic integration. It shows how mathematical concepts, such as the Black–Scholes and Gaussian random-field models, are used in financial situations.