Plight of the Fortune Tellers: Why We Need to Manage Financial Risk Differently (Hardcover)

~ Riccardo Rebonato (Author)
Key Phrases: decisional tools, modern utility theory, market risk factors, Monte Carlo, United States, Long Island (more...)

Editorial Reviews

Review

"Nowhere have I read a better account of how a conscientious, intellectually disciplined market risk manager approaches his work." -- Nicholas Dunbar, Risk

"Overall, the book gives an interesting insight into the development of modern risk management theory." -- Will Jackson, Fund Strategy

"The book is obviously well timed since recent market events have made a nonsense of statistical models." -- Financial World

Review

[Plight of the Fortune Tellers] was written to appeal to a wide audience. Stylistically, Rebonato is an engaging writer who uses analogies and interesting examples...I'm confident you'll enjoy this book and that, after reading it, you will join in the dialog that Rebonato has started.
(Garp Risk Review )

In his new book, Plight of the Fortune Tellers, Rebonato shows... why Merrill Lynch and Citigroup shareholders are right to be concerned. Nowhere have I read a better account of how a conscientious, intellectually disciplined market risk manager approaches his work in today's complex world. Well known to Risk readers as a master of interest rate modeling, Rebonato has written an accessible, non-technical book.
(Nicholas Dunbar Risk )

In Plight of the Fortune Tellers, Rebonato analyzes and offers solutions to problems related to quantitative risk management strategies and the value-at-risk (VAR) methodology currently used by financial managers. Through stories, examples, theory, and practical methods, he first provides a critical review of the current state of affairs in investment risk management. Then, he proposes how we should 'revisit our ideas about probability in financial risk management' and 'put decision making back at center stage.' In Plight of the Fortune Tellers contains valuable insights into the development of VAR methodology and problems associated with its use in the present financial management arena. . . . In Plight of the Fortune Tellers is a book recommended for practitioners currently involved in quantitative methods and for students of investments and risk management at the graduate school level.
(James Jackson CFA Digest )

This is an enjoyable, approachable book that may be read by anyone with an analytical mind. It is free of mathematics, yet it makes no concessions when it comes to explaining the complexities of a problem...I found a flowing prose that was a pleasure to read...[P]light of the Fortune Tellers is a great wake-up call for the industry. It deserves to be widely read since we all would like to be able to rely on the stability of the financial sector. It would be nice to get the risk management right.
(Jessica James Physics World )

Remember that feeling of bewilderment after your first few weeks in your first job after university? That wrenching realization that, while the theories that you had laboured to understand may have been illuminating, they were too abstract to be applied to the real world? Reading Riccardo Rebonato's intriguing book brings those memories flooding back. For while Rebonato well understands, approves of, and writes about quantitative probability and risk theory, his day job involves actually managing financial risk. Hence he appreciates the limits both of theory and of applying it to real world situations. . . . There is considerably more meat in this wise, practical, yet unpretentious book than can be summarized in a short review.
(John Llewellyn The Business Economist )

Riccardo Rebonato is a better fortuneteller than the risk analysts he writes about. He has read the palms of the 'quants' who revel in developing ever more complex risk models and found that their 'real life' line is rather short. But apart from confirming the prejudices of a financial journalist with no statistical training, is this book worth reading? The answer is yes. It is timely; the subject--financial risk management--matters hugely; it provides a relatively accessible guide to annoyingly influential statistical theories; and it makes you think.
(Financial World online )

Plight of the Fortune Tellers is insightful and entertaining. It provides a non-technical yet sophisticated introduction to the perils of modern risk management and it has the potential to lead us in a better direction. Don't miss it.
(Lisa R. Goldberg Journal of Investment Management )

This book should be on the reading list of experienced risk managers in the financial services industry as well as students who are contemplating a career in the field. It provides a thoughtful qualitative companion to more equation-laden texts on modern risk management.
(Moshe A. Milevsky Journal of Pension Economics and Finance )

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Product Details

• Hardcover: 304 pages
• Publisher: Princeton University Press (September 17, 2007)
• Language: English
• ISBN-10: 0691133611
• ISBN-13: 978-0691133614
• Product Dimensions: 9.2 x 6.4 x 1 inches
• Shipping Weight: 11.4 ounces (View shipping rates and policies)
• Average Customer Review: 4.7 out of 5 stars  See all reviews (6 customer reviews)
• Amazon.com Sales Rank: #464,372 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

16 of 16 people found the following review helpful:

5.0 out of 5 stars Timely and insightful; best of its kind!, December 5, 2007

By	David DeMers (Santa Fe) - See all my reviews (REAL NAME)

In my opinion this is the most valuable book on investment risk management of the past few years. Yet, no equations! However, with cogent arguments and literate prose, Rebonato lays out a case against the unfortunately prevalent misuse of statistical models in risk management.

Second edition should fix the minor annoyances, like "manger" for "manager" (appearing several times) and "form" for "from" (ditto), but the content should be read by everyone with interest in the area.

Especially welcomed are his arguments. Rather than setting up straw swans and knocking them down, or simply labeling alternative views as offensive or idiotic, he carefully sets out deep background for thinking about risk, and for thinking about probabilities, then shows how and why the well-meaning (and useful in the right context) VaR ideas are on a trajectory that is likely to go horribly wrong.

What to do? Unfortunately, the problem is hard and there are likely no easy solutions. But thinking correctly (my word) about the problem lets us roll up our sleeves and work on the right parts of the problem.

Investment management is all about risk management. We want to understand the risks in front of us, accept the risks we think we can get paid properly for, and avoid the ones where the bet is not in our favor. The Rumsfeldian "unknown unknowns" are the ones that are likely to cause the most damage. Those are what should keep us up at night trying to imagine. If they become "known unknowns", e.g. liquidity and linkage risks which showed up July/Aug 2007, we can get to work understanding and managing them.

Best (financial/investment) book of the year.

12 of 14 people found the following review helpful:

5.0 out of 5 stars A Challenge to the Quants, October 19, 2007

By	Great Faulkner's Ghost (Washington, DC) - See all my reviews (TOP 500 REVIEWER)

Rebonato challenges the "frequentist" approach to probabilities employed by stock analysts and rating agencies and finds lots to worry about. He says that although looking back at the past gives you masses of data that can be parsed and analyzed lots of different ways, it gives a dangerously miselading sense of security that future probabilities can be systematically determined with great prescision. The problem is that that whole thing is based on the idea that market moves are like coin flips, or monte carlo simulations, which say that while market prices change and fluctuate, that their underlying structure never actually changes. In fact, the probablities that really count are the those in the future, not those of the past. To predict those you need to understand what Rebonato dubs "subjective probability" - which while much more qualitative as opposed to mathematical, can actually be much more accurate and predictive. This is well worth thinking about, and is clearly explained for you to make your own judgment.

16 of 20 people found the following review helpful:

4.0 out of 5 stars Very interesting and important, November 8, 2007

By	Dr. Lee D. Carlson (Baltimore, Maryland USA) - See all my reviews (TOP 100 REVIEWER)    (REAL NAME)

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This book is one of the many that have come out in the last few years that has addressed the virtues and vices of financial modeling. Many of these books are devoted to the proposition that modeling has caused deep problems in the financial markets, but the evidence they present for this assertion is typically very weak. Considering the scale of modeling in financial institutions throughout the world, it would be naïve to assume that modeling has not influenced the markets, but it would also be unjustified from an empirical standpoint to say that modeling has been the predominant influence in market degradation. But if one believes that modeling has played the major role in this regard, then there will be a strong temptation to seek alternative methodologies for optimizing the risk/return trade-off.

The author is one of these, as can be ascertained early on in the book where he refers to data as giving "power to actions and decisions." However, the author is aware of the problems with the misguided imputation of power to concepts or ideas that are applied to contexts that are extremely rare in human experience. Thus he devotes several pages of the book to the "frequentist" interpretation of probability, and offers the Bayesian alternative. This is not to say that the frequentist approach should be completely discarded, for he discusses contexts where it is appropriate. One of these concerns the need for say a 99.9 percentile in some implementations of the Basel II accords. Such a level of confidence will be very problematic from the standpoint of validation given the paucity of real historical data. The author also offers suggestions for how risk managers are to clean up their act in the final chapter of the book.

He also discusses the possible use of belief theory in risk management, but apparently he is not aware that this approach has been tried in some contexts. In fact, this reviewer has applied some of the concepts from belief-theory to the problem of mortgage-broker scoring. Belief theory even has a "belief calculus" that has been applied to the modeling of financial portfolios, with the goal of learning how the returns change as new information is obtained on the factors that impact the portfolio. The belief calculus is similar to what is done using Bayesian networks, but with belief functions used to model the dependencies in the factors. Belief theory abandons the additive principle of probability theory, in that the 'belief mass', or "degree of belief" that is assigned to certain sets does not have to sum to one. However, belief functions is that they can be expressed as a probability using the so-called 'pignistic transformation', but one will obtain a loss in information if this is done. The author asserts that belief theory is a viable methodology, in that one's "confidence" that a certain event or number of events is about to occur is expressed by the willingness to "bet on" that event or events. But "credo" is Latin for "I believe" and "pignus" is Latin for a wage or bet, and certainly in everyday conversation one frequently hears "it is my belief that this will happen....I would bet a month's wages."

There is no arguing that decision making is the real essence of risk management, but does this have to involve subjective judgments, as the author seems to imply, or can it be done by a suitable collection of algorithms that are sophisticated enough to deal with most contingencies? If so, could this be taken one step further and allow the decision-making process to be automated, possibly using intelligent machines? Given the advances in artificial intelligence, this scenario is getting more plausible. But in all approaches to risk management, whether automated or not, one must still answer whether the human or machine estimation of probabilities of events is meaningful and how to assess if this is the case. Will this involve the use of traditional statistics or will some other approach be used?

Prospect theory, also discussed in the book, has certainly been a useful paradigm in risk management, to the degree that it has been utilized. But indeed how can one really know what concepts or methodologies are actually being employed by senior risk managers? In many cases, the analyst or modeler makes assumption that the management is using the results of the modeling efforts, but instead the management is relying on intuition or guesswork to make risk decisions, and completely ignoring the data from the models. In addition, distinguishing the impact of decisions based on modeling versus those based on intuition is more difficult than is realized at first glance.

Another important point to make here is that the Bayesian approach to the calculation of probabilities may not be part of the model itself, but frequently plays a major role in the validation and empirical support for the model. A similar situation occurs in other fields, such as physics, where Bayesian calculations permeate experimental confirmation of theories, but where the theories are stated in a frequentist framework.

Given the extreme events in the fixed-income sector at the present time, it is difficult to argue with the author's claim that financial risk management must be done in a different way. In fact, just this month a popular technology journal referred to a meeting of a couple of hundred of the more well-known financial modelers, who declared the summer of 2007 to be the worse ever for financial modeling. So the author is not alone in his opinions. But due to bureaucratic inertia and resistance from the status quo, finding the right time to implement these changes can be problematic, even when there is unanimous agreement that these changes are necessary.