The concepts and practice of mathematical finance

Table of content:
Preface
Acknowledgements
1. Risk
2. Pricing methodologies and arbitrage
3. Trees and option pricing
4. Practicalities
5. The Ito calculus
6. Risk neutrality and martingale measures
7. The practical pricing of a European option
8. Continuous barrier options
9. Multi-look exotic options
10. Static replication
11. Multiple sources of risk
12. Options with early exercise features
13. Interest rate derivatives
14. The pricing of exotic interest rate derivatives
15. Incomplete markets and jump-diffusion processes
16. Stochastic volatility
17. Variance gamma models
18. Smile dynamics and the pricing of exotic options
Appendix A. Financial and mathematical jargon
Appendix B. Computer projects
Appendix C. Elements of probability theory
Appendix D. Hints and answers to exercises
Bibliography
Index.

[https://www.cambridge.org/in/universitypress/subjects/mathematics/mathematical-finance/concepts-and-practice-mathematical-finance-2nd-edition?format=HB&isbn=9780521514088]

DescriptionContentsResourcesCoursesAbout the Authors
An ideal introduction for those starting out as practitioners of mathematical finance, this book provides a clear understanding of the intuition behind derivatives pricing, how models are implemented, and how they are used and adapted in practice. Strengths and weaknesses of different models, e.g. Black–Scholes, stochastic volatility, jump-diffusion and variance gamma, are examined. Both the theory and the implementation of the industry-standard LIBOR market model are considered in detail. Each pricing problem is approached using multiple techniques including the well-known PDE and martingale approaches. This second edition contains many more worked examples and over 200 exercises with detailed solutions. Extensive appendices provide a guide to jargon, a recap of the elements of probability theory, and a collection of computer projects. The author brings to this book a blend of practical experience and rigorous mathematical background and supplies here the working knowledge needed to become a good quantitative analyst.

Covers both martingale and PDE approaches to the subject and discusses multiple approaches to each problem
Spends a lot of time on the underlying ideas and intuition behind the models; includes computer projects
Covers alternative models such as stochastic volatility, jump diffusion and variance gamma as well as the conventional Black–Scholes

(https://www.cambridge.org/in/universitypress/subjects/mathematics/mathematical-finance/concepts-and-practice-mathematical-finance-2nd-edition?format=HB&isbn=9780521514088)