Although this book has now been published for some two years the methods presented are very relevant to current practices. Indeed, the publishers claim it is the first text book that has been entirely written about this subject.
Such a book needs to discuss optimisation models, methods and software that has been developed to deal with the solution of problems in computational finance.
Readers will find a comprehensive introductory chapter that provides and analysis of the problems to be dealt with and definitions and classifications of them.
Each of the classes given, and there are eight major classes of optimisation presented, has a whole chapter devoted to it. Each chapter deals with the chosen class in some detail. What is helpful is that both the theory and the method of tackling problems are followed by further chapters that aim to apply it to chosen problems.
Both linear and non‐linear programmings are discussed and appropriate application given. The application of linear programming is concerned with cashflow matching, asset pricing and arbitrage detection whilst non‐linear programming is applied to volatility estimation.
The book provides a large number of worked examples and case studies as well as exercises. Computer solutions, available modelling languages are also discussed.
Six types of problem were classified and considered: quadratic programming; conic optimisation; integer programming; dynamic programming stochastic programming; and robust optimisation (used to establish robust profit opportunities in risky portfolios).
A mathematical background is needed to truly appreciate the authors development of a subject which falls into the area of financial management.
