From the book description at amazon
Its motivation and content: quantitative skills are a prerequisite for everyone in quant finance. A thorough grounding in numerical techniques necessary, as is the ability to assess their adequateness, quality, and limitations. The book offers a thorough introduction to each method, revealing to the numerical traps that practitioners frequently fall into. Each method is referenced with practical examples of valuation, risk analysis, and calibration of specific deal types and models. It features a strong emphasis on the robust schemes for the numerical treatment of problems within computational finance. Methods covered include PDE/PIDE using FD or FE, fast and stable solvers for sparse grid systems, stabilization and regularization techniques for inverse problems resulting from the calibration of models to market date, MC and QMC techniques for solving high dimensional systems and global optimization tools to solve the minimization problem.
It is also about how avoiding or mitigating the horror of model risk.
The cover makes it clear, it is also about cross-sectoral math transferred from complex systems in, say, heavy industries to finance - by coal-faced mathematicians. Mathematical schemes that were not common in financial circles.
More details here soon.
