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Today's top financial professionals have come to rely on ever-more sophisticated mathematics in their attempts to come to grips with financial risk. But this excessive reliance on quantitative precision is misleading--and puts everyone at risk. In Plight of the Fortune Tellers, Riccardo Rebonato forcefully argues that we must restore genuine decision making to our financial planning. Presenting a financial model that uses probability, experimental psychology, and decision theory, Rebonato challenges us to rethink...
Today's top financial professionals have come to rely on ever-more sophisticated mathematics in their attempts to come to grips with financial risk. But this excessive reliance on quantitative precision is misleading--and puts everyone at risk. In Plight of the Fortune Tellers, Riccardo Rebonato forcefully argues that we must restore genuine decision making to our financial planning. Presenting a financial model that uses probability, experimental psychology, and decision theory, Rebonato challenges us to rethink the standard wisdom about risk management. He offers a radical yet surprisingly commonsense solution: managing risk comes down to real people making decisions under uncertainty.
Plight of the Fortune Tellers is a must-read for anyone concerned about how today's financial markets are run. In a new preface, Rebonato explains how the ideas presented in this book fit into the context of the global financial crisis that followed its original publication. He argues that risk managers are still stuck in a probabilistic rut, and need to engage with the structural causes of real events.
"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
But what I ... thought altogether unaccountable was the strong disposition I observed in [the mathematicians of Laputa] toward news and politics, perpetually enquiring into public affairs, giving their judgement on matters of state, and passionately disputing every inch of a party opinion. I have indeed observed the same disposition among the mathematicians I have known in Europe, although I could never observe the least analogy between the two sciences, unless those people suppose that because the smallest circle hath as many degrees as the largest, therefore the regulation and management of the world require no more abilities than the handling and turning of a globe. Jonathan Swift, writing about the mathematicians of Laputa
STATISTICS AND THE STATE
This book is about the quantitative use of statistical data to manage financial risk. It is about the strengths and limitations of this approach. Since we forget the past at our own peril, we could do worse than remind ourselves that the application of statistics to economic, political, and social matters is hardly a new idea. The very word "statistics" shares its root with the word "state," a concept that, under one guise or another, has been withus for at least a few centuries. The closeness of this link, between compilations of numbers, tables of data, and actuarial information on the one hand and the organization and running of a state on the other may today strike us as strange. But it was just when the power of this link became evident that statistics as we know it today was "invented." So, in its early days probability theory may well have been the domain of mathematicians, gamblers, and philosophers. But even when mathematicians did lend a helping hand in bringing it to life, from the very beginning there was always something much more practical and hard-nosed about statistics.
To see how this happened, let us start at least close to the beginning, and go back to the days of the French Revolution. In the first pages of Italian Journey (1798), Goethe writes:
I found that in Germany they were engaged in a species of political enquiry to which they had given the name of Statistics. By statistical is meant in Germany an inquiry for the purpose of ascertaining the political strength of a country, or questions concerning matters of state.
By the end of the eighteenth century, when Goethe explained his understanding of the word "statistics," the concept had been around in its "grubby" and practical form for at least a century. It is in fact in 1700 that we find another German, Leibniz, trying to forward the cause of Prince Frederick of Prussia who wanted to become king of the united Brandenburg and Prussia. The interesting point for our discussion is that Leibniz offers his help by deploying a novel tool for his argument: statistics. Prince Frederick of Prussia was at a disadvantage with respect to his political rivals, because the population of Prussia was thought to be far too small compared with that of Brandenburg to command a comparable seat at the high table of power. If at the time the true measure of the power of a country was the size of its population, the ruler could not be a Prussian. What Leibniz set out to prove was that, despite its smaller geographical size, Prussia was nonetheless more populous than was thought, indeed almost as populous as Brandenburg-and hence, by right and might, virtually as important. How did he set out to do so in those pre-census days? By an ingenious extrapolation based solely on the Prussian register of births, which had been started seventeen years earlier and carefully updated since. The details of how the estimate was reached need not concern us here-probably so much the better for Leibniz, because the jump from the birth data collected over seventeen years to the total size of the population was, by modern statistical standards, flawed. What is of great current interest is the logical chain employed by Leibniz, i.e., the link between some limited information that we do have but that, per se, we may consider of little importance-What do we care about births in Prussia?-to information that we would desperately like to have but is currently beyond our reach: for Leibniz and Prince Frederick, ultimately, what is the might of the Prussian army? If anyone were ever to doubt that there is real, tangible power in data and in data collection, this first example of the application of the statistical line of argument to influence practical action should never be forgotten. The modern bank that painstakingly collects information about failures in the clearing of cheques, about minute fraud, about the delinquency of credit card holders and mortgagors (perhaps sorted by age, postcode, income bracket, etc.) employs exactly the same logic today: data give power to actions and decisions. To the children of the Internet age it may all seem very obvious. But, at the beginning of the eighteenth century, it was not at all self-evident that, in order to gain control over the running of the state, looking at hard, empirical, and "boring" data might be more useful than creating engaging fictions about "natural man," "noble savages," social contracts between the king and the citizens, etc. The first statisticians were not political philosophers or imaginative myth-makers: they were civil servants.
The parallels between these early beginnings and today's debates about statistics run deeper. As soon as the power of basing decisions on actual data became apparent, two schools of thought quickly developed, one in France (and Britain, Scotland in particular) and one in Prussia. Generalizing greatly, the French school advocated an interpretation of the data on the basis of the "regularities of human nature": deaths, births, illness, etc., were, according to the French and British schools of thought, no less regular, and therefore no less amenable to rigorous quantitative analysis, than, say, floods or other "natural" phenomena. Ironically, the Prussian school, that had founded the statistics bureau, failed to reap the full advantage of its head start because it remained suspicious of the French theoretical notions of "statistical law" when applied to human phenomena-and, predictably, derided the French statisticians: "What is the meaning of the statement that the average family has 2.33 children? What does a third of a child look like?"
Perhaps it is not surprising that the country of the fathers of probability theory (Descartes, Pascal, Bernoulli, Fermat, etc.) should have been on the quantitative side of the debate. Indeed, 100 years before statistics were born, Bernoulli was already asking questions such as, "How can a merchant divide his cargo between ten ships that are to brave the pirate-infested seas so as to minimize his risk?" In so doing, he was not only inventing and making use of the eponymous probability distribution, he was also discovering risk aversion, and laying the foundations of financial risk management. Probability and statistics therefore seemed to be a match made in heaven: probability theory would be the vessel into which the "hard" statistical data could be poured to reach good decisions on how to run the state. In short, the discipline of probability, to which these French minds contributed so much, appeared to offer the first glimpses of an intriguing promise: a quantitative approach to decision making.
The Prussian-French debate was not much more constructive than many of the present-day debates in finance and risk management (say, between classical finance theorists and behavioral financiers), with both parties mainly excelling in caricaturing their opponent's position. Looking behind the squabbling, the arguments about the applicability and usefulness of quantitative techniques to policy decisions have clearly evolved, but reverberations of the 200-year-old Franco-Prussian debate are still relevant today. The French way of looking at statistics (and of using empirical data) has clearly won the day, and rightly so. Perhaps, however, the pendulum has swung too far in the French direction. Perhaps we have come to believe, or assume, that the power of the French recipe (marrying empirical data with a sophisticated theory of probability) is, at least in principle, boundless.
This overconfident extrapolation from early, impressive successes of a new method is a recurrent feature of modern thought. The more elegant the theory, the greater the confidence in this extrapolation. Few inventions of the human mind have been more impressive than Newtonian mechanics. The practical success of its predictions and the beauty of the theory took a hold on Western thought that seemed at times almost impossible to shake off. Yet two cornerstones of the Newtonian edifice, the absolute nature of time and the intrinsically deterministic nature of the universe, were ultimately to be refuted by relativity and quantum mechanics, respectively. Abandoning the Newtonian view of the world was made more difficult, not easier, by its beauty and its successes.
It sounds almost irreverent to shift in one paragraph from Newtonian physics and the absolute nature of time to the management of financial risk. Yet I think that one can recognize a similar case of overconfident extrapolation in the current approach to statistics applied to finance. In particular, I believe that in the field of financial risk management we have become too emboldened by some remarkable successes and have been trying to apply similar techniques to areas of inquiry that are only superficially similar. We have come to conclude that we simply have to do "more of the same" (collect more data, scrub our time series more carefully, discover more powerful statistical theorems, etc.) in order to answer any statistical question of interest. We have come to take for granted that while some of the questions may be hard, they are always well-posed.
However, if this is not the case but the practice and the policy to control financial risk remain inspired by the nonsensical answers to ill-posed questions, then we are all in danger. And if the policies and practices in question are of great importance to Our well-being (as is, for instance, the stability and prudent control of the financial system), we are all in great danger.
WHAT IS AT STAKE?
Through financial innovations, a marvelously intricate system has developed to match the needs of those who want to borrow money (for investment or immediate consumption) and of those who are willing to lend it. But the modern financial system is far more than a glorified brokerage of funds between borrowers and lenders. The magic of modern financial engineering truly becomes apparent in the way risk, not just money, is parceled, repackaged, and distributed to different players in the economy. Rather than presenting tables of numbers and statistics, a simple, homely example can best illustrate the resourcefulness, the reach, and the intricacies of modern applied finance.
Let us look at a young couple who have just taken out their first mortgage on a small house with a local bank on Long Island. Every month, they will pay the interest on the loan plus a (small) part of the money borrowed. Unbeknownst to them, their monthly mortgage payments will undergo transformations that they are unlikely even to imagine. Despite the fact that the couple will continue to make their monthly mortgage payments to their local bank, it is very likely that their mortgage (i.e., the rights to all their payments) will be purchased by one of the large federal mortgage institutions (a so-called "government-sponsored agency") created to oil the wheels of the mortgage market and make housing more affordable to a large portion of the population. Once acquired by this institution, it will be pooled with thousands of other mortgages that have been originated by other small banks around the country to advance money to similar home buyers. All these mortgages together create a single, diversified pool of interest-paying assets (loans). These assets then receive the blessing of the federal agency who bought them in the form of a promise to continue to pay the interest even if the couple of newlyweds (or any of their thousands of fellow co-mortgagors) find themselves unable to do so. Having given its seal of approval (and financial guarantee), the federal institution may create, out of the thousands of small mortgages, new standardized securities that pay interest (the rechanneled mortgage payments) and will ultimately repay the principal (the amount borrowed by the Long Island couple).
These new securities, which have now been made appealing to investors through their standardization and the financial guarantee, can be sold to banks, individuals, mutual funds, etc. Some of these standardized securities may also be chopped into smaller pieces, one piece paying only the interest, the other only the principal when (and if) it arrives, thereby satisfying the needs and the risk appetite of different classes of investors. At every stage of the process, new financial gadgets, new financial instruments, and new market transactions are created: some mortgages are set aside to provide investors with an extra cushion against interruptions in the mortgage payments; additional securities designed to act as "bodyguards" against prepayment risk are generated; modified instruments with more predictable cash flow streams are devised; and so on.
So large is this flow of money that every rivulet has the potential to create a specialized market in itself. Few tasks may appear more mundane than making sure that the interest payments on the mortgages are indeed made on time, keeping track of who has repaid their mortgage early, channeling all the payments where they are due just when they are due, etc. A tiny fraction of the total value of the underlying mortgages is paid in fees for this humble servicing task. Yet so enormous is the river of mortgage payments, that this small fraction of a percent of what it carries along, its flotsam and jetsam, as it were, still constitutes a very large pool of money. And so, even the fees earned for the administration of the various cash flows become tradeable instruments in themselves, for whose ownership investment banks, hedge funds, and investors in general will engage in brisk, and sometimes furious, trading.
The trading of all these mortgage-based securities, ultimately still created from the payments made by the couple on Long Island and their peers, need not even be confined to the country where the mortgage originated. The same securities, ultimately backed by the tens of thousands of individual private mortgage borrowers, may be purchased, say, by the Central Bank of China. This body may choose to do so in order to invest some of the cash originating from the Chinese trade surplus with the United States. But this choice has an effect back in the country where the mortgages were originated. By choosing to invest in these securities, the Central Bank of China contributes to making their price higher. But the interest paid by a security is inversely linked to its price. The international demand for these repackaged mortgages therefore keeps (or, actually, pushes) down U.S. interest rates and borrowing costs. As the borrowing cost to buy a house goes down, more prospective buyers are willing to take out mortgages, new houses are built to meet demand, the house-building sector prospers and employment remains high. The next-door neighbor of the couple on Long Island just happens to be the owner of one small enterprise in the building sector (as it happens, he specializes in roof tiling). The strong order book of his roof tiling business and his optimistic overall job outlook make him feel confident about his prospects. Confident enough, indeed, to take out a mortgage for a larger property. So he walks into the local branch of his Long Island bank. Au refrain.
Excerpted from Plight of the Fortune Tellers by Riccardo Rebonato
Copyright © 2007 by Princeton University Press. Excerpted by permission.
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Posted September 1, 2009
Reading this book is like reading the prophecies of Cassandra, whose fate was to speak the truth to the unbelieving. In the wake of the fiscal crisis, no one can question the observation that the practice of financial risk management has serious flaws. Business journalist Riccardo Rebonato's discussion of why and how financial institutions misunderstand and mismanage risk provides valuable insights. He works to make his ideas accessible beyond the narrow circles of financial economists and quantitative risk managers. He uses no equations in the text, and his few graphs are clear and accessible. He states his case against excess reliance on statistical methods in plain language. getAbstract believes that his analysis should interest any manager or regulator whose responsibilities include oversight of finance.Was this review helpful? Yes NoThank you for your feedback. Report this reviewThank you, this review has been flagged.