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Journal of Risk Management in Financial Institutions Vol. 2, 3 326-327
(c) Henry-Stewart Publications (2009)
The text by David Vose published this year
is the third edition of this book, substantially rewritten. This book is based
on the long consulting experience of the author in the area of risk analysis.
The text is divided into two parts, in addition there are four appendices. The
first part (about 1/6 of the book) consists of first five chapters. The main
reader of this part, according to the intention of the author, is manager. The
aim of this part is to provide understanding of risk analysis and explain its
use in decision making process.
The first four chapters are definitely of
applied nature. They describe the main objectives of risk analysis (chapter 1),
planning risk analysis (chapter 2), quality of risk analysis (chapter 3) and
discussion on the structure of the model used in risk analysis (chapter 4).
These chapters contain many useful hints for present and prospective risk
analysts and managers, particularly:
- Remarks on the selection of good risk managers;
- Introducing framework "Probability – Impact" (P/I scores);
- Description of different types of risk models (given in chapter 4);
- Distinction between variability (being the function of the studied system) and
uncertainty (being the lack of knowledge).
There is follow up of this distinction in some considerations in the second part
of the book. I consider this approach as particularly useful.
On the other hand, the author proposes the
distinction between "risk" and "opportunity" (page 3). In this approach risk is
purely negative notion, opposite to opportunity, which has positive meaning.
However, in some disciplines, for example in finance, "risk" has often neutral
meaning. This means that on one hand risk is understood as "threat" (negative
side), on the other hand as "opportunity" (positive side). The distinction
proposed by the author can lead to some confusion.
Chapter 5 is the largest and probably the
most important chapter (from modeling point of view) in the first part of the
book. I consider the remarks on the structure of the report as well as review of
tools for the graphical presentation of report as particularly useful. This
chapter contains some material which is also presented in some chapters of the
second part of the book. I think that this repetition could have been avoided.
It looks like the intention of the author
was to provide two parts that will be read by different audience.
As the title of the book indicates, it is
meant to be a guide of quantitative methods used in risk analysis. This is
particularly provided in the second part of the book, containing chapters 6-22.
Most of these chapters are constructed on the basis of the simple idea:
description of quantitative tools and the illustration by the examples coming
from different applied areas. It is worth to mention that the author starts with
very basics and then moves to very specific methods.
The consecutive chapters contain:
- The basics of probability theory and statistics (chapter 6);
- Useful hints as to the building models used in risk analysis, including
description of common mistakes made in risk analysis (chapter 7);
- Basic stochastic processes: binomial, Poisson, hypergeometric (chapter 8);
- Basics of statistical inference, with the particular attention to Bayesian
approach and bootstrapping methods (chapter 9);
- Use of simple statistical methods (including regression) in fitting
statistical distributions to data (chapter 10);
- Methods used to determine the sum of random variables (chapter 11);
- Forecasting methods for time series data, using stochastic processes in
continuous and discrete time (chapter 12);
- Modeling dependencies, including copulas (chapter 13);
- Deriving estimates using expert opinions (chapter 14);
- Practical issues related to causal analysis (chapter 15);
- Optimization methods (chapter 16), written by Francisco Zagmutt;
- Validation of risk model (chapter 17);
- Discounted Cash Flow model (chapter 18);
- Project risk analysis (chapter 19):
- Methods used in modeling of financial and insurance risk (chapter 20);
- Methods used in microbial food safety risk analysis (chapter 21);
- Methods used in animal import risk analysis (chapter 22).
I would like to see the chapter 11
included in chapter 6, since they contain basic probability theory.
This book contains many examples, brought
from different disciplines. Two types of software are used to conduct
calculations. The first one is simply Microsoft Excel, which makes examples
readable even for not advanced reader. The second one is the system ModelRisk,
developed in author’s company and used by them in practice.
In addition, the book contains four
appendices. Three of them are relatively short, these are:
- Very useful guide for lecturers, designing structures of some possible
courses taught with the use of this book;
- Description of the system ModelRisk;
- List of publications suggested for further reading.
The fourth appendix, written by Michael
van Hauwermeiren, is 120 page compendium of statistical distributions. It is
excellent reference, to be used separately for teaching purposes.
The book is very valuable source of information for these risk analysts, who
want to use quantitative methods, particularly Monte Carlo simulation, in the
process of risk analysis and management. Of course, the author may still think
about some improvements as far as the structure of book is concerned.
Krzysztof Jajuga
Department of Financial Investments and Risk Management
Wroclaw University of Economics Wroclaw,
Poland
E-mail:
krzysztof.jajuga@ue.wroc.pl
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