This general book on high-performance computing in finance is academically and pragmatically relevant as it is built around real-life challenges. The text covers the newest techniques such as automatic differentiation, dataflow, and large scale computation for Basel III, Solvency II, and stochastic programming. With illustrative success stories in the use of high-performance computing in the finance and insurance industries, the book imparts the wisdom of adopting this method of numbers crunching to achieve business goals.

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...