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The long-awaited sequel to the "Concepts and Practice of Mathematical Finance" has now arrived. Taking up where the first volume left off, a range of topics is covered in depth. Extensive sections include portfolio credit derivatives, quasi-Monte Carlo, the calibration and implementation of the LIBOR market model, the acceleration of binomial trees, the Fourier transform in option pricing and much more. Throughout Mark Joshi brings his unique blend of theory, lucidity, practicality and experience to bear on issues relevant to the working quantitative analyst.

"More Mathematical Finance" is Mark Joshi's fourth book. His previous books including "C++ Design Patterns and Derivatives Pricing" and "Quant Job Interview Questions and Answers" have proven to be indispensable for individuals seeking to become quantitative analysts. His new book continues this trend with a clear exposition of a range of models and techniques in the field of derivatives pricing. Each chapter is accompanied by a set of exercises. These are of a variety of types including simple proofs, complicated derivations and computer projects.

Mark S. Joshi is a researcher and consultant in mathematical finance. He obtained a B.A. in mathematics from the University of Oxford in 1990, and a Ph.D. in pure mathematics from the Massachusetts Institute of Technology in 1994 under the supervision of Richard Melrose. He was an assistant lecturer in the department of pure mathematics and mathematical statistics at Cambridge University and a fellow of Darwin college from 1994 to 1999. Following which he worked for the Royal Bank of Scotland[3] from 1999 to 2005 as a quantitative analyst at a variety of levels, finishing as the Head of Quantitative Research for Group Risk Management. He joined the Centre for Actuarial Studies at the University of Melbourne in November 2005 as an associate professor, and he is now a full professor. He lectures the subject Financial Mathematics III and is also a highly sought after honours supervisor in the department. He is a famous quant and known for his guide "On becoming a quant".[

Chapter 1. Optionality, convexity and volatility 1
Chapter 2. Where does the money go? 9
Chapter 3. The Bachelier model 23
Chapter 4. Deriving the Delta 29
Chapter 5. Volatility derivatives and model-free dynamic replication 33
Chapter 6. Credit derivatives 41
Chapter 7. The Monte Carlo pricing of portfolio credit derivatives 53
Chapter 8. Quasi-analytic methods for pricing portfolio credit derivatives 71
Chapter 9. Implied correlation for portfolio credit derivatives 81
Chapter 10. Alternate models for portfolio credit derivatives 93
Chapter 11. The non-commutativity of discretization 113
Chapter 12. What is a factor? 129
Chapter 13. Early exercise and Monte Carlo Simulation 151
Chapter 14. The Brownian bridge 175
Chapter 15. Quasi Monte Carlo Simulation 185
Chapter 16. Pricing continuous barrier options using a jump-diffusion model 207
Chapter 17. The Fourier-Laplace transform and option pricing 219
Chapter 18. The cos method 253
Chapter 19. What are market models? 265
Chapter 20. Discounting in market models 281
Chapter 21. Drifts again 293
Chapter 22. Adjoint and automatic Greeks 307
Chapter 23. Estimating correlation for the LIBOR market model 327
Chapter 24. Swap-rate market models 341
Chapter 25. Calibrating market models 363
Chapter 26. Cross-currency market models 389
Chapter 27. Mixture models 401
Chapter 28. The convergence of binomial trees 407
Chapter 29. Asymmetry in option pricing 433
Chapter 30. A perfect model? 443
Chapter 31. The fundamental theorem of asset pricing. 449
Appendix A. The discrete Fourier transform 457
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