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Portfolio Management under Stress offers a novel way to apply the well-established Bayesian-net methodology to the important problem of asset allocation under conditions of market distress or, more generally, when an investor believes that a particular scenario (such as the break-up of the Euro) may occur. Employing a coherent and thorough approach, it provides practical guidance on how best to choose an optimal and stable asset allocation in the presence of user specified scenarios or 'stress conditions'. The authors place causal explanations, rather than association-based measures such as correlations, at the core of their argument, and insights from the theory of choice under ambiguity aversion are invoked to obtain stable allocations results. Step-by-step design guidelines are included to allow readers to grasp the full implementation of the approach, and case studies provide clarification. This insightful book is a key resource for practitioners and research academics in the post-financial crisis world.
- Sales Rank: #1176358 in Books
- Published on: 2014-02-24
- Original language: English
- Number of items: 1
- Dimensions: 9.72" h x 1.26" w x 6.85" l, 2.36 pounds
- Binding: Hardcover
- 516 pages
Review
"Rebonato and Denev have demolished the status quo with their radical extension of best-practice portfolio management. The key is to integrate realistic "extreme" scenarios into risk assessment, and they show how to use Bayesian networks to characterize precisely those scenarios. The book is rigorous yet completely practical, and reading it is a pleasure, with the "Rebonato touch" evident throughout."
Francis X. Diebold, Paul F. and Warren S. Miller Professor of Economics, and Professor of Finance and Statistics, University of Pennsylvania
"Standard portfolio theory has been shown by recent events to have two major shortcomings: it does not deal well with extreme events and it is often based on mechanical statistical procedures rather than modelling of fundamental causal mechanisms. In this book, Rebonato and Denev put forward an interesting approach for dealing with both of these problems. Their method is flexible enough to accommodate individual views of underlying causal mechanisms, but disciplined enough to ensure that decisions do not ignore the data. Anyone with a serious interest in making good portfolio decisions or measuring risk will benefit from reading this book."
Ian Cooper, London Business School
"This book is self-contained in that it covers a lot of familiar but diverse material from a fresh perspective. Its purpose is to take an ambitious new approach to combining this material into a coherent whole. The result is a new methodology for practical portfolio management based on Bayesian nets, which satisfactorily takes into simultaneous account both normal and extreme market conditions. While readers may themselves be under stress in absorbing the details of the new approach, serious fund managers and finance academics will ignore it at their peril."
M. A. H. Dempster, Emeritus Professor, University of Cambridge, and Cambridge Systems Associates Limited
"Here is a book that combines the soundest of theoretical foundations with the clearest practical mindset. This is a rare achievement, delivered by two renowned masters of the craft, true practitioners with an academic mind. Bayesian nets provide a flexible framework to tackle decision making under uncertainty in a post-crisis world. Modeling observations according to causation links, as opposed to mere association, introduces a structure that allows the user to understand risk, as opposed to just measure it. The ability to define scenarios, incorporate subjective views, model exceptional events, etc., in a rigorous manner is extremely satisfactory. I particularly liked the use of concentration constraints, because history shows that high concentration with low risk can be more devastating than low concentration with high risk. I expect fellow readers to enjoy this work immensely, and monetize on the knowledge it contains."
Marcos Lopez de Prado, Research Fellow, Harvard University, and Head of Quantitative Trading, Hess Energy Trading Company
"In a recent book of my own I bemoan rampant "confusion" among academics as well as practitioners of modern financial theory and practice. I am delighted to say that the authors of Portfolio Management Under Stress are not confused. It is heart-warming to find such clarity of thought among those with positions of great influence and responsibility."
Harry M. Markowitz, Nobel Laureate, Economics 1990
"Rebonato and Denev have ploughed for all of us the vast field of applications of Bayesian nets to quantitative risk and portfolio management, leaving absolutely no stone unturned."
Attilio Meucci, Chief Risk Officer at Kohlberg Kravis Roberts (KKR)
About the Author
Riccardo Rebonato is Global Head of Rates and FX Analytics at PIMCO, and a visiting lecturer in Mathematical Finance at Oxford University (OCIAM). He has previously held positions as Head of Risk Management and Head of Derivatives Trading at several major international financial institutions. Dr Rebonato has been on the Board of ISDA (2002-2011) and still serves on the Board of GARP (2001 to present). He is the author of several books in finance and an editor for several journals (International Journal of Theoretical and Applied Finance, Journal of Risk, Applied Mathematical Finance, Journal of Risk for Financial Institutions).
Alexander Denev is a Senior Team Leader in the Risk Models department at The Royal Bank of Scotland. He is specialised in Credit Risk, Regulations, Asset Allocation and Stress Testing, and has previously worked in management roles at the European Investment Bank, Soci�t� G�n�rale and the National Bank of Greece.
Most helpful customer reviews
0 of 0 people found the following review helpful.
Great book! Finally a structural approach to understanding risk ...
By Christophe
Great book! Finally a structural approach to understanding risk and not just one based on historical statistical measures.
I recommend this book to all interested in a new approach to portfolio management.
On the practical side, the book starts by explaining causality and why it should replace statistics in modern finance. A lengthy
description of Bayesian Nets follows before switching back to problems in risk management. One thing I found particularly useful is the construction and the analysis of a stress scenario from scratch and its subsequent application to a concrete asset management problem.
Maybe the book is too lengthy and sometimes difficult but it is worth going through it.
0 of 0 people found the following review helpful.
Bleeding edge of Risk Management
By Srdjan Kovacevic
Rebonato and Denev present a truly groundbreaking approach to stress testing methodology. Risk models based exclusively on historical data have proven their shortcomings by failing to warn us about recent major events that shook the financial world, indicating that a traditional frequentist approach is long due for an overhaul.
Book is mathematically sound and technical enough to allow you to cook your own solutions, but I'd love to see some Matlab code in the future. I do recommend reading it if you wish to stay on the bleeding edge of risk management.
0 of 0 people found the following review helpful.
Highly recommend it to both finance professionals and economists to gain ...
By F.
Although the book is primarily targeting technically-oriented readers, the first chapters carefully introduce and describe the essence of the authors’ methodology with causality and transparency of the model at its core, making it very accessible to the broader audience. Highly recommend it to both finance professionals and economists to gain more insight into cutting-edge risk modelling.
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