Stress tests are the most innovative regulatory tool to prevent and fight financial crises. Their use has fundamentally changed the modeling of financial systems, financial risk management in the public and private sector, and the policies designed to prevent and mitigate financial crises. When financial crises hit, stress tests take center stage. Despite their centrality to public policy, the optimal design and use of stress tests remains highly contested. Written by an international team of leading thinkers from academia, the public sector, and the private sector, this handbook comprehensively surveys and evaluates the state of play and charts the innovations that will determine the path ahead. It is a comprehensive and interdisciplinary resource that bridges theory and practice and places financial stress testing in its wider context. This guide is essential reading for researchers, practitioners, and policymakers working on financial risk management and financial regulation.

Developed over 20 years of teaching academic courses, the Handbook of Financial Risk Management can be divided into two main parts: risk management in the financial sector; and a discussion of the mathematical and statistical tools used in risk management. This comprehensive text offers readers the chance to develop a sound understanding of financial products and the mathematical models that drive them, exploring in detail where the risks are and how to manage them. Key Features: Written by an author with both theoretical and applied experience Ideal resource for students pursuing a master’s degree in finance who want to learn risk management Comprehensive coverage of the key topics in financial risk management Contains 114 exercises, with solutions provided online at www.crcpress.com/9781138501874

Discover current uses and future development of stress tests, the most innovative regulatory tool to prevent and fight financial crises.

Stress tests are used in risk management by banks in order to determine how certain crisis scenarios would affect the value of their portfolios, and by public authorities for financial stability purposes. Until the first half of 2007, interest in stress-testing was largely restricted to practitioners. Since then, the global financial system has been hit by deep turbulences, including the fallout from sub-prime mortgage lending. Many observers have pointed out that the severity of the crisis has been largely due to its unexpected nature and have claimed that a more extensive use of stress-testing methodologies would have helped to alleviate the repercussions of the crisis. This book analyses the theoretical underpinnings, as well as the practical aspects, of applying such methodologies. Building on the experience gained by the economists of many national and international financial authorities, it provides an updated toolkit for both practitioners and academics.

A practioner’s guide to quantitative reverse stress testing, featuring advanced solutions for better management of financial risks Whether you manage a portfolio, a business unit or a bank, you must ensure that a sudden shock in the markets won’t drive you out of business because of a large loss, a jump in capital utilisation or an increase in funding consumption . In financial risk management, reverse stress testing is the attempt to identify worst case scenarios causing maximum financial loss. Traditional stress testing methods have failed to avert the last financial crisis or highlight financial distress. . Every so often some regulators and risk managers specify stress scenarios with simplifications that create a false sense of safety. To avoid a combinatorial explosion, a number of arbitrary choices are usually made in relation to the level of each shock, their combination and the time horizon. These assumptions, although necessary, limit the effectiveness of this technique. Quantitative Reverse Stress Testing: Hunting for the Black Swan offers a more natural approach to identifying the realistic scenario provoking the largest losses. It also provides a means to understand the impact of extreme events and how to mitigate them while introducing technological advances and the adapted mathematical tools that have made it possible to solve this type of quantitative finance problems. You’ll see how mitigation strategies can be more accurate and better targeted, reducing risk, cost of funding and regulatory capital. With this book, you’ll have access to a comprehensive guide to crucial aspects of reverse stress testing. · Get an introduction to a rigorous mathematical framework to quantitative reverse stress testing · Consider different heuristics, one of them based on annealing, to solve theoptimisation problem · Review solution implementation, system infrastructure design and integration into the financial risk management of a firm · Read related case studies from a variety of industries If it’s time to move your approach to reverse stress testing forward, this guide offers real solutions tooptimisation and cost issues. Get a guide that supports a more informed approach to testing and financial risk management as it helps to protect vital business interests.

In Coherent Stress Testing: A Bayesian Approach, industry expert Riccardo Rebonato presents a groundbreaking new approach to this important but often undervalued part of the risk management toolkit. Based on the author's extensive work, research and presentations in the area, the book fills a gap in quantitative risk management by introducing a new and very intuitively appealing approach to stress testing based on expert judgement and Bayesian networks. It constitutes a radical departure from the traditional statistical methodologies based on Economic Capital or Extreme-Value-Theory approaches. The book is split into four parts. Part I looks at stress testing and at its role in modern risk management. It discusses the distinctions between risk and uncertainty, the different types of probability that are used in risk management today and for which tasks they are best used. Stress testing is positioned as a bridge between the statistical areas where VaR can be effective and the domain of total Keynesian uncertainty. Part II lays down the quantitative foundations for the concepts described in the rest of the book. Part III takes readers through the application of the tools discussed in part II, and introduces two different systematic approaches to obtaining a coherent stress testing output that can satisfy the needs of industry users and regulators. In part IV the author addresses more practical questions such as embedding the suggestions of the book into a viable governance structure.

"Operational Risk Capital Models is a guide for the implementation of state of the art operational risk capital models suitable for regulatory approval. For insurers, Solvency II implementation has created the need, in both highly developed and less developed markets, for the development of these models that help to better understand risks, safe capital and compliance. For the banking industry, regulators in many countries in Africa, Asia and Latin America (as well as Europe) are pressing their local banks to implement advanced operational risk capital models. Banks that have made early implementation are looking to improve their capital models with new advances to match the increasing regulatory requirements. Operational Risk Capital Models enables you to model your operational risk capital to ensure the model meets regulatory standards. It describes the process end to end, from the capture of the required data to the modelling and VaR calculation, as well as the integration of capital results into your institution's daily risk management." --Contratapa.