Massimo Morini

The book's content is focused on rigorous and advanced quantitative methods for the pricing and hedging of counterparty credit and funding risk. The new general theory that is required for this methodology is developed from scratch, leading to a consistent and comprehensive framework for counterparty credit and funding risk, inclusive of collateral, netting rules, possible debit valuation adjustments, re-hypothecation and closeout rules. The book however also looks at quite practical problems, linking particular models to particular 'concrete' financial situations across asset classes, including interest rates, FX, commodities, equity, credit itself, and the emerging asset class of longevity. The authors also aim to help quantitative analysts, traders, and anyone else needing to frame and price counterparty credit and funding risk, to develop a 'feel' for applying sophisticated mathematics and stochastic calculus to solve practical problems. The main models are illustrated from theoretical formulation to final implementation with calibration to market data, always keeping in mind the concrete questions being dealt with. The authors stress that each model is suited to different situations and products, pointing out that there does not exist a single model which is uniformly better than all the others, although the problems originated by counterparty credit and funding risk point in the direction of global valuation. Finally, proposals for restructuring counterparty credit risk, ranging from contingent credit default swaps to margin lending, are considered.

An indispensable working resource for any finance professionals concerned with interest rates and pricing models Modern Interest Rate Markets and Models is the first book to cover both the theory and practice of dealing with rate-sensitive financial products in light of the fundamental changes taking place in the market. Classical approaches to interest modelling are reviewed alongside evidence of why these frameworks are no longer consistent with present market evidence, and the authors present a new theoretical explanation of the new patterns that are emerging. Readers gain insight into the new framework and its practical applications, with expert guidance toward constructing multiple interest curves and volatility surfaces, and pricing derivatives coherently with present interest rate market and data. Appendices summarise the mathematical toolkit to support all calculations in the text, and an extensive bibliography points readers toward additional literature on the subject. The on-going financial crisis has triggered a deep evolution of the classical framework for pricing and trading financial instruments, with macroscopic impacts on both vanilla and exotic contracts, particularly within the interest rate market. Yet, these classical approaches remain the focus of standard textbooks, resulting generations of new practitioners approaching the market in an inaccurate manner. This book seeks to rectify the situation with an entirely new approach that more accurately reflects the realities of the modern market. * Examine the ways in which the credit crunch impacted the interest rate market * Learn why classical approaches to interest rate modelling are no longer valid * Discover new patterns and mathematical frameworks that represent the current market * Generalise the most important interest rate models into modern multiple-curve versions With the most consistent, comprehensive approach to the subject, readers will find Modern Interest Rate Markets and Models to be an indispensible resource for building a stronger, more sustainable market strategy.

A guide to the validation and risk management of quantitative models used for pricing and hedging Whereas the majority of quantitative finance books focus on mathematics and risk management books focus on regulatory aspects, this book addresses the elements missed by this literature--the risks of the models themselves. This book starts from regulatory issues, but translates them into practical suggestions to reduce the likelihood of model losses, basing model risk and validation on market experience and on a wide range of real-world examples, with a high level of detail and precise operative indications.