Risk Revealed: Cautionary Tales, Understanding and Communication

Author:   Paul Embrechts (Swiss Federal University (ETH), Zürich) ,  Marius Hofert (The University of Hong Kong) ,  Valérie Chavez-Demoulin (Université de Lausanne, Switzerland)
Publisher:   Cambridge University Press
ISBN:  

9781009299800


Pages:   384
Publication Date:   11 April 2024
Format:   Hardback
Availability:   In stock   Availability explained
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Risk Revealed: Cautionary Tales, Understanding and Communication


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Overview

Explore the concept of risk through numerous examples and their statistical modeling, traveling from a historical perspective all the way to an up-to-date technical analysis. Written with a wide readership in mind, this book begins with accounts of a selection of major historical disasters, such as the North Sea flood of 1953 and the L'Aquila earthquake. These tales serve to set the scene and to motivate the second part of the book, which describes the mathematical tools required to analyze these events, and how to use them. The focus is on the basic understanding of the mathematical modeling of risk and what types of questions the methods allow one to answer. The text offers a bridge between the world of science and that of everyday experience. It is written to be accessible to readers with only a basic background in mathematics and statistics. Even the more technical discussions are interspersed with historical comments and plentiful examples.

Full Product Details

Author:   Paul Embrechts (Swiss Federal University (ETH), Zürich) ,  Marius Hofert (The University of Hong Kong) ,  Valérie Chavez-Demoulin (Université de Lausanne, Switzerland)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press
Dimensions:   Width: 18.30cm , Height: 2.40cm , Length: 26.10cm
Weight:   0.950kg
ISBN:  

9781009299800


ISBN 10:   1009299808
Pages:   384
Publication Date:   11 April 2024
Audience:   General/trade ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   In stock   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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Reviews

'Everything you always wanted to know about understanding and communicating risks. This book is the ultimate reference at a critical time when scientists and policy-makers have had to work so closely together to handle uncertainty.' Pauline Barrieu, London School of Economics 'This book describes the big risks facing society. These include floods, earthquakes and financial crises. The authors showcase the statistical framework to model these risks. The book is garnished with quirky stories of mathematicians. I enjoyed the book's unique perspective and I found it insightful and ambitious.' Phelim Boyle, University of Waterloo 'We waited a long time for this book. This is the age of Big Risks – we know because we create many of them ourselves. Society can navigate these risks only by becoming much more numerate. This book is for everyone from concerned layman to specialist who wants to raise their risk numeracy. It starts with a highly textured inventory of modern risks, inundation, space flight, financial risks, earthquakes, tsunamis and pandemics. A pas de deux with mathematics ignites an infatuation, which sustains the novice through friendly yet meticulous chapters on probabilistic modeling. In the end the reader is empowered to build extreme value models.' Roger M. Cooke, Resources for the Future, Washington DC 'I very much enjoyed this excursion through a world of risk, as revealed in historical incidents from Dutch tulip mania to the coronavirus pandemic. Written by three experts in quantitative modeling, each episode holds important lessons on risk communication, as well as some accessible maths and a wealth of entertaining detail.' Alexander J. McNeil, University of York Management School


Author Information

Paul Embrechts is Emeritus Professor of Insurance Mathematics in the Department of Mathematics of ETH Zurich, Switzerland. He holds numerous distinctions and awards from universities and organizations worldwide. He co-authored the influential books 'Modelling Extremal Events for Insurance and Finance' and 'Quantitative Risk Management: Concepts, Techniques and Tools' and has published over 200 scientific papers in leading international scientific journals. Marius Hofert is Associate Professor in the Department of Statistics and Actuarial Science at The University of Hong Kong. He obtained his Ph.D. in Mathematics from Ulm University in 2010. He then held a postdoctoral research position at RiskLab, ETH-Zurich. Afterwards, he was Guest Professor in the Department of Mathematics at the Technische Universität München, Visiting Assistant Professor in the Department of Applied Mathematics at the University of Washington and Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. Marius' research interests are dependence modeling, computational statistics, data science and quantitative risk management. He has offered several courses, mini-courses, workshops, summer and winter schools in these areas, including courses on risk management at the Risk Management Institute at the National University of Singapore and at the 29th International Summer School of the Swiss Association of Actuaries. Marius also participates in the education of actuaries and risk managers by developing teaching material and software freely available on qrmtutorial.org. Valérie Chavez-Demoulin is Professor of Statistics at the Faculty of Business and Economics, University of Lausanne (UniL). She is also co-founder and on the Executive and Scientific Board of the UniL research center ECCE (Expertise Center for Climate Extremes). Valérie holds a Master's degree in Mathematics from EPFL and a Ph.D. in Mathematics (specializing in Statistics) from the same institution. She was a research fellow at the Department of Mathematics (D-Math) at ETH-Zurich and later an Invited Professor at D-Math, ETH-Zurich, for a sabbatical leave. Her domain of expertise is extreme value theory and in particular, the statistical modeling of univariate or multivariate extreme events in non-stationary or covariate-dependent contexts.

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