Books in the Mathematics, Finance and Risk series

Using carefully-chosen examples, this book explains how to create well-designed, structured, reusable code, particularly for financial applications. New chapters explain interfacing C++ with EXCEL, designing a generic factory, and improving code design with decoupling. Complete ANSI/ISO compatible C++ source code is hosted on an accompanying web site.

The second edition of a successful text providing the working knowledge needed to become a good quantitative analyst. An ideal introduction to mathematical finance, readers will gain a clear understanding of the intuition behind derivatives pricing, how models are implemented, and how they are used and adapted in practice.

Credit derivatives have enjoyed explosive growth in the last decade, particularly synthetic Collateralised Debt Obligations (synthetic CDOs). This book describes the state-of-the-art in quantitative and computational modelling of CDOs. Beginning with an overview of the structured finance landscape, readers are introduced tothe basic modelling concepts necessary to model and value simple credit derivatives. The modelling, valuation and risk management of synthetic CDOs are described and a detailed picture of the behaviour of these complex instruments is built up. The final chapters introduce more advanced topics such as portfolio management of synthetic CDOs and hedging techniques. Detailing the latest models and techniques, this is essential reading for quantitative analysts, traders and risk managers working in investment banks, hedge funds and other financial institutions, and for graduates intending to enter the industry. It is also ideal for academics who need to keep informed with current best practice in the credit derivatives industry.

Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.