“Risk management is at a crossroads. The ‘certainty’ provided by statistical analysis of historical data has been shown to be an illusion. The challenge is how to inject a dose of judgment but not revert to pure subjectivity. There is no clear answer, and a reliable guide is required to navigate what can be a minefield. Fortunately Dr. Rebonato has used his unique combination of technical skills and experience to explain what can cannot be done using stress testing. Anyone who is interested in combining the best aspects of statistical analysis and disciplined subjective judgment should read this book.”
—Ian Cooper, Professor Finance, London Business School
“Wall Street goes Bayesian! Theses methods have long been used as a standard technique in reliability engineering and operations research, now this book introduces Bayesian nets as a stress testing tool for the financial industry. Every quantitative risk manager ought to be aware of their potential: this is an excellent start.”
—Paul Embrechts, Department of Mathematics and RiskLab, ETH Zurich
“Stress tests are essential complements to VaR models, which are inadequate for very rare events. In practice, however, scenarios can be difficult to handle because they are typically not associated with a probability. This book shows how to build subjective, yet consistent probabilities for scenarios. Highly recommended.”
—Philippe Jorion, Professor, University of California at Irvine
Based on the author’s extensive work, research and presentation 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 judgment 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 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 applications of the tools discussed in part II, and introduces two different systematic approaches to obtaining a coherent stress testing output that can satisfy the ends 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.
“Riccardo Renato examines the deficiencies of current financial modelling practice and the limitations of the purely statistical approaches to risk quantification that underpin VaR methodology. Taking his cue from Knightian uncertainty – and Rumsfeldian unknown unknowns – the author argues that a program of stress testing carried out within a Bayesian paradigm can offer risk managers a route to redemption after the crisis. Written in his usual lucid and engaging style, Coherent Stress Testing is a thought provoking text on a vitally important issue, and a serious proposal of a workable solution.”
—Alexander J. McNeil, Maxwell Professor, Heriot-Watt University
“Riccardo Rebonato’s book shows how managerial judgments can be combined with analysis to improve the way stress testing is done. The book is well written and very timely. In the aftermath of the 2007&ndash2009 financial crisis risk management groups at all financial institutions are looking for ways they can make stress testing more effective.”
—John Hull, Maple Financial Professor of Derivatives and Risk Management, Joseph L. Rotman School of Management, University of Toronto
“Rebonato’s interesting book provides a refreshingly different and thought-provoking perspective of stress-testing and quantitative risk management – exactly what the field needs in these troubled times.”
—Rüdiger Frey, Professor of Financial Mathematics and Optimization, Universität Leipzig, Co-author of Quantitative Risk Management: Concepts, Techniques, Tools