Google full text of our books:


Plight of the Fortune Tellers:
Why We Need to Manage Financial Risk Differently
Riccardo Rebonato

Book Description | Shopping Cart | Reviews | Table of Contents
Chapter 1 [HTML] or [PDF]


In my book I made several points, which have been borne out by recent events. I give below a detailed account of the specific shortcomings of much current thinking regarding the management of financial risk, as ex ante I highlighted them in Plight of the Fortune Tellers. Before going into detail it is important to see how correct my overall message was.

  1. I argued in the book that the industry and the regulators were wasting precious (and limited) risk management resources in a futile quantification attempt, when both common sense and a better-conceived type of statistical analysis (Bayesian probability) clearly indicated that these efforts were ill-conceived.
  2. We didn’t just waste time and resources. The industry and the regulators also gained a sense of spurious precision (remember the 99.975th percentile of the ‘best-practice’ economic-capital project?). This false sense of precision engendered the impression that risks so precisely known and understood could be easily managed and controlled. They were neither. The consequences are in front of us for everybody to see.
  3. I also stressed that fact that the blind faith in the collection of more and more data as a panacea for our statistical problems neglected the fact that data, to be useful, has to be relevant. I forcefully argued that the concept of relevance (our prior beliefs) goes beyond the raw data and that pretending otherwise was putting us in the predicament of the coin-tossing Martian discussed in my book. In a financial landscape that is literally changing by the day, the absurdity of the idea that more precise (frequentist) statistical analysis could simply be achieved by the mechanical collection of more data has also been shown by recent events.
  4. Finally, I made the point that, even if these probabilities had been meaningful and available to the risk management community, they would have not helped in decision making. Indeed, the best risk management decisions made in the crisis that is still unfolding have been based on expert judgement and subjective assessment of trade-offs between ‘different evils’, not on the basis of the estimation (right or wrong as it may be) of remote percentiles.

More specifically I argued in the book as follows:

  1. The attempt to determine the magnitude of extremely-low-probability financial events has been proven by recent events utterly futile. Yet both regulators and the financial industry were, and to a large extent still are, placing large reliance on tools--such as ‘economic capital’--that are supposed to allow the estimation of the magnitude of extremely rare events. Several shocks larger than what the models believed to be once-in-several-thousand-years events have occurred many times in the last eighteen months.
  2. At the root of the problem is not the need for a ‘better model’, but a misguided view of probability in risk management. The industry and the regulators have deluded themselves that the probabilities of relevance in the management of financial risk were of the type that apply to coin-tossing experiments (frequentist probabilities), rather than the subjective probabilities (“probabilities-as-degree-of-belief”) that we use in sentences like “What is the probability of the next President of the United States being a Democrat?”
  3. In my book I made clear that, even if the magnitude of these extremely low-probability events could have been predicted, this would have given no assistance in financial decision making (which is what risk management is all about). This is because human beings are cognitively ill-equipped to deal with very low probabilities (by the way, the System-I, System-II distinction in our decision-making processes that I discuss in at length in my book to prove this point is a central theme of the recent book Nudge). Recent events have shown that we are indeed fundamentally cognitively ill-equipped to turn information about extremely low probabilities into effective decision-making.
  4. In my book I stressed the importance of liquidity (at the root of a bank’s solvency), while the regulatory framework was obsessively focussed on capital adequacy. Not by chance the example I chose to illustrate the importance of liquidity was that of US mortgage-backed securities.
  5. In the context of liquidity I have also discussed bank runs, despite the fact that, at the time of my writing, the last bank run had occurred decades before.
  6. I made the point that the statistical (frequentist) tools at the basis of the current regulatory and industry framework are based on a naďve conception of co-dependence (correlation) that totally breaks down just when it is most needed, i.e. in periods of market turmoil.
  7. In my ‘alternative suggestions’ I emphasized the importance of various forms of stress-testing. One of them (the break-even analysis) has been put forth as an alternative way of analyzing positions by the latest Corrigan report.

A few quotes:

  • About the futility of estimation of the magnitude of extremely-low-probability financial events:
    [T]hose banks who literally believe to have set aside enough capital to safeguard against once-in-three-thousand-year events are likely to be the first to regale the front pages of the financial press with the next story about 'unexplainable losses.'. . .
  • On the dangers of spurious precision:
    [T]he last thing regulators should do is to impose pseudo-scientific requirements. The myth of quantification is a pernicious (and expensive) one. Nobody's interests are well served when a great part of the finite risk management resources of a bank are devoted to calculating numbers of dubious meaning [the high percentile losses], and when these numbers are interpreted using a flawed (frequentist) concept of probability. . . .
  • On bank runs:
    But if a rumour spreads that a bank is not solvent, the individually-rational thing to do is to rush to the head of the queue, not to come back tomorrow when the queue to bank, now circling two blocks, will be shorter: by tomorrow the queue may well be shorter, but simply because there may be no money left in the vault. This is how runs on banks occur and, given the asymmetry of information between insiders and depositors, the same response (run for the till!) applies towards the perfectly healthy bank and the one that has really got itself into financial difficulties.
  • On the shortcomings of correlation
    In all these cases, the familiar correlation coefficient does a very poor job at explaining how different variables move together. Not surprisingly, this is particularly true when we are dealing with the dependence among rare events, ie, with what is called tail dependence. […] If we are looking at the tails of distributions, the correlation […] that we estimate in normal conditions […] is of no help at all just when we need it. […] We may not like to hear it, but dependence in general, and tail dependence in particular, is extremely important in determining the highest percentiles of a loss distribution. The higher the percentile, the bigger the impact.
  • On the link between the financial sector and the ‘real’ economy:
    All these new financial instruments, like powerful new medicines, are potentially risky. Striking a good balance between reaping all the advantages they can afford and containing their ‘side effects' is a formidable challenge. The outcome of this balancing act will have very deep consequences for the world economy: turn the dials too much in one direction, and we shall certainly be less well off than we could have been; turn them too much in the other direction and we run a small risk of a serious derailment of the economy.
    The management of financial risk therefore acutely matters, not only to […] financial, but to the public at large and, as the agent of the public and the underwriter of deposit insurance, to the government.
    It is exactly because, in a modern economy, the boundaries between the financial plumbing and the real economy have become so blurred and porous that the management of financial risk is today vitally important--and vitally important to everyone, from Wall Street financiers down to the [public at large].
  • On the importance of liquidity and on the systemic importance of mortgage-backed securities:
    All these pieces of financial wizardry must perform their magic while ensuring that the resulting pieces of paper that are exchanged between borrowers and lenders [mortgage-backed securities] enjoy an elusive but all-important property: the ability to flow smoothly and without interruptions among the various players in the economy. All the fancy pieces of paper are useful only if they can freely flow, ie, if they can be readily exchanged into one another (thereby allowing individuals to change their risk profile at will), or, ultimately, into cash. Very aptly, this all-important quality is called `liquidity'. By itself, sheer ingenuity in inventing new financial gadgets is therefore not enough: the pieces of paper that are created must not only redirect risk in an ingenious way; they must also continually flow, and flow without hindrance.
    As the example of the mortgage suggests, if an occlusion occurs anywhere in the financial flows that link the payments made to the local Long Island bank to the foreign exchange management reserve office of the Bank of China, the repercussions of this clogging of the financial arteries will be felt a long way away from where it happens (be it in on Long Island or in Beijing). It is because of this interconnectedness of modern financial instruments that financial risk has the potential of assuming the so-called `systemic' dimension.

Return to Book Description

File created: 10/22/2008

Questions and comments to:
Princeton University Press

[an error occurred while processing this directive]
Send me emails
about new books in:
More Choices