Tuesday, March 10, 2009

The Fat-Tailed Straw Man

My Time article about the quant meltdown of August, 2007 started with “Looks like Wall Street’s mad scientists have blown up the lab again.” Articles on Wall Street’s mad scientist blowing up the lab seem to come out every month in one major publication or another. The New York Times has a story along these lines today and had a similar story in January.

There is a constant theme in these articles, invariably including a quote from Nassim Taleb, that quants generally, and quantitative risk managers specifically, missed the boat by thinking, despite all evidence to the contrary, that security returns can be modeled by a Normal distribution.
This is a straw man argument. It is an attack on something that no one believes.
Is there anyone well trained in quantitative methods working on Wall Street who does not know that security returns have fat tails? It is discussed in most every investment text book. Fat tails are apparent – even if we ignore periods of crisis – in daily return series. And historically, every year there is some market or other that has suffered a ten standard deviation move of the "where did that come from" variety. I am firmly in the camp of those who understand there are unanticipatable risks; as far back as an article I co-authored in 1985, I have argued for the need to recognize that we face uncertainty from the unforeseeable. To get an idea of how far back the appreciation of this sort of risk goes in economic thought, consider the fact that it is sometimes referred to as Knightian uncertainty.
Is there any risk manager who does not understand that VaR will not capture the risk of market crises and regime changes? The conventional VaR methods are based on historical data, and so will only be an accurate view of risk if tomorrow is drawn from the same population as the sample it uses. VaR is not perfect, it cannot do everything. But if we understand its flaws – and every professional risk manager does – then it is a useful guide for day-to-day market risk. If you want to add fat tails, fine. But as I will explain below, that is not the solution.
So, then, why is there so much currency given to a criticism of something that no one believes in the first place?
It is because quant methods sometimes fail. We can quibble with whether ‘sometimes’ should be replaced with ‘often’ or ‘frequently’ or ‘every now and again’, but we all know they are not perfect. We are not, after all, talking about physics, about timeless and universal laws of the universe when we deal with securities. Weird stuff happens. And the place where the imperfection is most telling is in risk management.
When the risk manager misses the equivalent of a force five hurricane, we ask what is wrong with his methods. By definition, what he missed was a ten or twenty standard deviation event, so we tell him he ignored fat tails. There you have it, you failed because you did not incorporate fat tails. This is tautological. If I miss a large risk – which will occur on occasion even if I am fully competent; that is why they are called risks – I will have failed to account for a fat tailed event. I can tell you that ahead of time. I can tell you now – as can everyone in risk management – that I will miss something. If after the fact you want to castigate me for not incorporating sufficiently fat tailed events, let the flogging begin.
I remember a cartoon that showed a man sitting behind a desk with a name plate that read ‘risk manager’. The man sitting in front of the desk said, “Be careful? That’s all you can tell me, is to be careful?” Observing that extreme events can occur in the markets is about as useful as saying “be careful”. We all know they will occur. And once they have occurred, we will all kick ourselves and our risk managers and our models, and ask “how could we have missed that?”
The flaw comes in the way we answer that question, a question that can be stated more analytically as “what are the dynamics of the market that we failed to incorporate.” If we answer by throwing our hands into the air and saying, “well, who knows, I guess that was one of them there ten standard deviation events”, or “what do you expect; that’s fat tails for you”, we will be in the same place when the next crisis arrives. If instead we build our models with fatter and fatter tailed distributions, so that after the event we can say, “see, what did I tell you, there was one of those fat tailed events that I postulated in my model”, or “see, I told you to be careful”, does that count for progress?
So, to recap, we all know that there are fat tails; it doesn’t do any good to state the mantra over and over again that securities do not follow a Normal distribution. Really, we all get it. We should be constructive in trying to move risk management beyond the point of simply noting that there are fat tails, beyond admonitions like “hey, you know, shit happens, so be careful.” And that means understanding the dynamics that create the fat tails, in particular, that lead to market crisis and unexpected linkages between markets.
What are these dynamics?
One of them, which I have written about repeatedly, is the liquidity crisis cycle. An exogenous shock occurs in a highly leveraged market, and the resulting forced selling leads to a cascading cycle downward in prices. This then propagates to other markets as those who need to liquidate find the market that is under pressure no longer can support their liquidity needs. Thus there is contagion based not on economic linkages, but based on who is under pressure and what else they are holding. This cycle evolves unrelated to historical relationships, out of the reach of VaR-types of models, but that does not mean it is beyond analysis.
Granted it is not easy to trace the risk of these potential liquidity crisis cycles. To do so with accuracy, we need to know the leverage and positions of the market participants. In my previous post, "Mapping the Market Genome", I argued that this should be the role of a market regulator. But even absent that level of detail, perhaps we can get some information indirectly from looking at market flows.
No doubt there are other dynamics that lead to the fat tailed events currently frustrating our efforts to manage risk in the face of market crises. We need to move beyond the fat-tail critiques and the ‘be careful’ mantra to discover and analyze them.


  1. Rick wrote: "We should be constructive in trying to move risk management beyond the point of simply noting that there are fat tails, beyond admonitions like “hey, you know, shit happens, so be careful.” And that means understanding the dynamics that create the fat tails, in particular, that lead to market crisis and unexpected linkages between markets."

    The challenge unexpected linkages pose is that they are not found in fat tails.

    The past does not contain a record of the coming unexpected linkages.

    I think a less data driven and more counterfactual approach has to drive thinking about this sort of risk.

    Some short posts about this can be found here:




  2. So maybe quant funds would benefit from hiring someone very smart but with no formal financial training. Maybe a poet or a chess g/master?

    Just lobbing one out there.......

  3. "Thus there is contagion based not on economic linkages, but based on who is under pressure and what else they are holding."

    Isn't "what else they are holding" economic linkage? They're not holding it by accident, are they?

  4. "An exogenous shock occurs in a highly leveraged market, and the resulting forced selling leads to a cascading cycle downward in prices. This then propagates to other markets as those who need to liquidate find the market that is under pressure no longer can support their liquidity needs. Thus there is contagion based not on economic linkages, but based on who is under pressure and what else they are holding."

    I look at this through a Fisher lens. It seems to me that one problem is that the leverage, while high, appears contained if it can be wound down in a contained manner, which it often is. What needs to be added is panic, which precludes an organized and efficient winding down, because its effects go outside of the immediate investment environment. So, while focusing on leverage and linkages seems like a good idea, panic, once started, is hard to predict or contain. So we need to ask if there is a way to preclude panic, in the way that FDIC insurance is used to preclude bank runs.

    Truthfully speaking, following Bagehot, if there is a LOLR, it is going to be assumed to be a guarantor. Yet, ideas of insurance seem to be too expensive for banks or too little to cover losses.

    The solution, to me, is to have a government guaranteed narrow/limited banking system, alongside a regulated/self-insured/non-guaranteed financial sector. Hopefully, because there is a LOLR, and a solid banking system under it, along with some insurance, perhaps bought from the government, that would be enough to stop a Calling Run breaking out system wide.

    The problem with assessing risk is that it can vary. In one instance, it can be contained, in another, it can't.

    As best as I can tell, VaR, CDSs, CDOs, have valid uses. In hearing calls for banning them or other investment instruments, we're involved in a kind of Debt-Deflation of human ability. We've gone from hubris to impotence and skipped the sensible middle. It doesn't seem to me to be a valid argument that, since we can't predict everything, we can't predict anything. There is also a difference between not seeing risk, and ignoring it. I think that our situation was caused by the latter.

    Don the libertarian Democrat

  5. ...the only constant in the equation of economic cycles is greed...greed, in turn, propels people towards acting on delusions rather than facts...and as you pointed out quite lucidly when you were a "theoretical biologist"::

    "But in a complex environment, there is also some chance the model will be wrong in a fundamental way and in a way that will lead to a large loss if the model is followed."

    ...human behavior is clearly a "complex environment."...why economists never quite get this point is beyond my comprehension.

  6. The problems with economists understanding of human behavior and the type of uncertainty under which we labor is the reason I wrote in the Journal of Theoretical Biology. At the time (the 1980's) the points I was making were not accepted within economics. No one seemed to accept the idea that people did not operate essentially as computer-like optimizers. No one would accept that people faced uncertainty that could not be incorporated in a well-defined probability distribution.

    So I used animals and insects to make the point I would have rather made with people. At least everyone was OK with the idea that a cockroach might be subject to shocks that were totally outside the realm of its experience and consideration.

  7. Here's a post I came across today which says some of what I was trying to say, as a simple citizen:

    "Modelling financial turmoil through endogenous risk"


    It begins:

    "Financial crises are often accompanied by large price changes, but large price changes by themselves do not constitute a crisis. Public announcements of important macroeconomic statistics, such as the US employment report, are sometimes marked by large, discrete price changes at the time of announcement. However, such price changes are arguably the signs of a smoothly functioning market that is able to incorporate new information quickly. The market typically finds composure quite rapidly after such discrete price changes.
    A crisis feeds on itself

    In contrast, the distinguishing feature of crisis episodes is that they seem to gather momentum from the endogenous responses of the market participants themselves. Rather like a tropical storm over a warm sea, they gather more energy as they develop. As financial conditions worsen, the willingness of market participants to bear risk seemingly evaporates. They curtail their exposures and generally attempt to take on a more prudent, conservative stance.

    However, the shedding of exposures results in negative spillovers on other market participants from the sale of assets or withdrawal of credit. As prices fall, measured risks rise, or previous correlations break down, market participants respond by further cutting exposures. The global financial crisis of 2007-9 has served as a live laboratory for many such distress episodes."

    Don the libertarian Democrat

  8. This point of endogenous responses is what I am talking about with the liquidity crisis cycle, discussed towards the end of the post.

    In that cycle, what makes for the endogenous acceleration of the initial exogenous shock, and thus precipitates the crisis, is the leverage of the participants, which forces them to liquidate. This in turn drops prices further, forcing more liquidation. And, as I point out in this post and in other places (including my book), the next step is selling in other markets, leading to contagion.

  9. You seem like a sincere chap and it's hard to disagree with you that anyone who was smart enough to get a job on Wall Street as a "quant" would "get" the problems with the normal distribution and Black Swans etc.
    But in all honesty how many really smart people sat through Powerpoint presentations where claims about Value At Risk were made by front office investment bankers and were gutsy enough to challenge a naive interpretation that this was a formula for calculating the worst case scenario?
    The moral of the story perhaps is that - It's better to be approximately wrong (i.e. before the quant revolution in risk management) than precisely wrong.

  10. As all readers of "Foundation" knows, it will take another fifty thousand years before the great mathematician Hari Seldon writes his famous thesis on the statistics of psychohistory.
    In the mean time we should try to move away from linear models. The traders' Boolean "greed or fear" modeling of the market looks much more human and plausible to me than linear models. The latter tends to work fine only as long as there is no dramatic shift from one state to the other in the Boolean model.

  11. I am not convinced by your argument. It seems to me that the larger point is not that quants were unaware of the possibility of fat tails. They would have failed statistics 101 if they were.

    The problem is that for all practical purposes they acted/act as if the normal distribution was the rule. Or at least they acted in a way that made it easy and tempting for their audience (managers, investors) to focus on the good news of the models and disregard the margin of uncertainty. Surely quants were not so naif as to ignore what the "illusion of certainty" would do to an eager public? It is simply being too lenient to say that they bear no responsibility for what people did with their models. In fact the central issue of ethics in the scientific professions revolves around the uses of science by scientists but specially by non-scientists.

    Frankly, to say that "we knew fat tails could happen" is suspiciously convenient. Sounds like a "tails I win, heads you loose" situation: "if everything goes well, it is our brilliant model at work, if something bad happens...it is those pesky fat tails that our statistics handbook talks about right here on note 43, chapter 12". You do say "We are not, after all, talking about physics, about timeless and universal laws of the universe when we deal with securities". But the point was that a lot of people (and perhaps some quants) acted as if they were physicists. And, to push the metaphor, it is my impression that quants were paid as if they were physicists, delivering near certainty (LCTM and all that).

    I too get annoyed with this blame game going on, and perhaps quants are being unfairly singled out. There was a generalized cultural atmosphere conducive to hubris. Bank managers, policy makers, economists ("the great moderation") and, yes, quants, were all part of this culture.

    But to suggest, as I think you are, that quants are just uninterested scientists fully aware of the limitations of their field who were surprised by what people assume about their models is, frankly, an unsatisfying argument.

  12. Answering M. Montahna:
    I do not want to say that the quants are blameless. They might have misrepresented the nature of the risk, or less damning, not have communicated it well. They might have cut corners in how they modeled it. They might have not bothered to think about the risks they could not readily address. The last part of my post is trying to make the last of these points.

    What I am trying to focus on in this post is that whatever their errors, it is not as simple as them sitting there unaware of the nature of the distributions and the limitation of VaR. They are not so stupid as to think a Normal distribution is descriptive of the markets. Yet it seems to me that many criticisms are of the nature of, "Look at these simple-minded quants. With all of their math training, they did not realize the simple point that there are fat tails; that there is Knightian uncertainty". They understood that. They did not need Taleb to point that out. And so that particular criticsm, and the efforts of Taleb and others to argue that this is a type of risk that people have not recognized, is a straw man argument.

    An argument that it was recognized but not well analyzed, or that it was recognized but not well communicated, is a different one.

    And, even if they did not understand the nature of security returns, having them all take a fat-tail catechism would not, alone, lead to much progress. The dynamics related to those fat tails, dynamics along the lines of the liquidity crisis cycle, for example, would need to be incorporated into the risk analysis.

  13. Apparently Taleb cannot find anyone brave or strong enough to debate him on his critical points like VaR. Perhaps a smackdown between Taleb and Bookstaber might enlighten a wide audience?

    Can we have it on Bloomberg instead of CNBC please?

    Taleb's Edge Essay is an attempt at some useful construction, at least to frame the debate with categories of risk. Is there a conceptual relationship between Taleb's Edge essay and Bookstaber's J Theor Bio 1985 article?

  14. I don't disagree with Taleb's views on the importance of what we might call Knightian uncertainty -- what in my J of Theoretical Biology article I called extended uncertainty. But I think once stated, you need to go further. You shouldn't make a career out of pointing out what is, for most of us, fairly obvious by now, and stopping there. And I think in the case I have made in this post, he may be casting arguments based on it that are straw men.

  15. Straw man arguments are incredibly popular, and for someone on the inside, this always drives them crazy. Whether its nature or nurture, efficient markets or free markets generating perfection, or normal distributions.

    Markowitz had a section on non-normal distributions back in his initial text on portfolio optimization. Stiglitz and Rothschild's definition of 'Risk' in the early 1970's was all about expanding from the Gaussian distribution, and it was a seminal work for decades, but it didn't really lead anywhere. Work on Stochastic Dominance (first and second order) was a nonparametric way to assess risk, it too is rarely used now. Mandelbrot wrote about fat tails in 1962. There are always articles about skewness and leptokurtosis in practitioner journals.

    It is important but it is also very difficult to address, and often a normal distribution plus a volatility smile is a nice compromise of tractability and accuracy.

    Journalists love the story that those smarty pants economists who gave them math problems they couldn't understand are missing the forest through the trees, idiot savants, blinded by hubris and their lack of common sense that journalists are simply full of (just ask them!). The accusation is too good to check. But this is a caricature, and anyone who is smart and had some real experience realizes this.

  16. I think the big issue between the normal curve and reality is that our valuation models, which are the basis for the transactions themselves, rely on normal distributions.

    The Capital Asset Pricing Model, used to determine the cost of equity, relies on the normal curve. So does Black-Scholes. Even the variants of the option pricing model that try to account for fat tails are still just making adjustments to the normal curve!

    The reason that these flawed theories are still taught and used as the basis for decision making in finance is that they are the best that exist. Fractals and other forms of Chaos/Complexity Theory work well on historical data, but I'm not aware of any successful predictive models built that way.

    Normal curves do not reflect human behavior. They work, perhaps, 90 percent of the time. Since people need to make decisions, they use what they have.

    What is really problematic is the way that these models were extended.

    In hindsight, it is clear that a portfolio of NINJA subprime loans cannot generate any sizable tranche of AAA rated paper, but the agencies were going along with as much as 80-90 percent of such portfolios having such a rating. The logic was that, historically, subprime mortgages had paid back with sufficient margins of error to support the rating. The mistake was two-fold:

    1 - Originations were not of the same quality as in the past since mortgages were being originated for sale, not to be held. There was an assumption of a reputation risk to the originator if they generated bad paper, but clearly that was incorrect.

    2 - Housing prices were increasing at accelerating rates, far beyond what had ever been experienced before. The belief that, even in default, there would be a high level of recovery was based on historical data that were no longer realistic. Housing prices are now declining rapidly and there are a growing number of homes with negative equity.

    Now we can say that these mortgages were created due to a lack of understanding of fat tails. We can say that it was due to unappreciated agency risk.

    Heck, I'm sure we can come up with all sorts of academic descriptions for the massive screw ups that led to this disaster.

    The fault is not all with the risk managers or with the theory. There was a mass psychosis.

    Now we are experiencing the liquidity effects of credit contraction.

    Rick, is there really that much of a difference between you and Taleb?

  17. On the question of whether there is a difference in view between me and Taleb:
    I don't think we differ in our views on risk. I believe, as he does, that there is Knightian uncertainty, and also that we live in a fat-tailed world when it comes to securities. My point is that so does just about everyone else in risk management, though they might not have hammered the point home as eloquently and stridently.

  18. hi rick, in support of taleb's arguments, from my experience as a derivatives trader and risk manager at a regular investment bank

    1) our risk managers print daily a meaningless VaR number and make me sign it every day. it's not pointless because of "fat tails", it is pointless because of the market situation. the main products I have in the book have been issued in very very large amounts. similar to the famous examples in your book, the banks only sell the product, they delta hedge this product every day, but the end investor keeps in a shelf and does nothing. and there is no secondary market for this product. put these facts together and you can see that a) our hedges we distort several markets and b) we are exposed to blow ups. now, our risk managers are not so impressed by the facts I just stated. they are quite busy aggregating my positions to calculate the Var

    2) until recently they were performing "stress tests" by simply multiplying my deltas and gammas by some large market move. the essential risk in this kind of book are second order cross greeks, which they didn't even measure until I told them to.

    3) our auditors are extgremely happy with the situation. they come every year to check whether I have signed my VaR sheets every day, which I do. everybody is happy. of course, they know even less what my risks really are.

    4) for the math PhD blokes in the risk methodology, market situation is of no relevance whatsoever. all they think about is model subtleties such as jump-diffusion, stochastic vols etc. all of their subtleties are worth # all if you can't find a counterparty on your delta hedge. a bunch of losers, if you ask me :) but they have a lot of power in the bank, so I have to listen to their useless cr#p at meetings (or worse than useless in some cases).

    the point I am trying to make is that, at least from what I see around me, quantitative methodologies stop people from using their heads. people are too busy with fancy math and forget the essential. I think this is the point nassim tries to make. I am sure that all risk managers in my bank know the limitations of VaR, but that doesn't seem to help. as an organization we still fail.

    as I said before, what we need to do is stop the PL printing machine. this would have never happened unless some fools agreed to us showing profit on each structure on day one, before having earned anything. stop rewarding people for building the avalanche, then we can worry about the market genome.

  19. Having been on both sides of the fence - first as a trader, then as a risk manager and then back to the trading firing line - I could not agree more with the previous comments by r2. Three more remarks:
    1) While Taleb is absolutely correct in his remark that the fancy-schwanzy quantitative technology and the computers have resulted in an athrophy in people's brains, eliminating measurements altogether is not a solution either. By definition, in any remit, you cannot manage what you cannot measure. Making the use of abacuses in trading rooms would go a long way towards stretching people's intelligence and risk insights but hardly qualifies as a robust solution that we can yearn for.
    2) The key issue remains the brains and incentives at the top. Dummy folks who just rehearse accounting-driven incentives for the joy of shareholders will remain useless irrespective of whether you feed them with VaR or more intelligent and comprehensive representations of risk. A top-notch car does not by itself turn a rookie into Schumacher. Furthermore, as long as performance and compensation are measured in accounting terms - the perverse incentives will remain.
    3) Last but not least, which is sort of implicit in r2 comments, the crisis has finally put back to center stage the issue of risk reporting being disguised and camouflaged under the catchier and more glamorous Risk Management label - and the horrible consequences, too. No army would ever confuse support staff and SAS (or SEAL)-like frontline commando operations and nor should firms involved in trading. The way forward is for risk management to get back to its 1980s roots by having small autonomous tactical trading units in the trading room and all the support,model validation, regulatory matters, IT etc. performed by independent product control or similar staff. Needless to add, the frontline "real" RM commando operation need to have a direct reporting line to the very top of the organization.

    In the current chaos, policymakers are doing their best to compound the confusion even further with crazy proposals on relaxing mark-to-market rules. That is one unglamorous but extremely important area that is as important to the trading industry as water in the desert. Until this challnge is rebuffed head-on, arguing on model issues, VaR and the like strikes me as the wrong side of 80-20.

  20. hi fisherking, thanks a lot for the supporting comments. but now you got me started on mark to market, so hang on to your seat :) in practice, mark to market is multiplying the quantity you hold by some price on a bloomberg screen, although it is not defined this way in GAAP. looks to me that this approach to mark to market is taken to mean "fair value". people find it desirable over other methods because it doesn't allow banks to hide their losses when asset prices drop, offers transparency to end inverstors etc. but there is a reverse to it, it also gives the illusion of profit when asset prices go up, particularly in illiquid markets (same as the internet stocks example in risk's book). I have exposure in several illiquid markets, and I can tell you it's a circus. year end levels are manipulated by traders and brokers. the trader wants either to low ball the PL or overstate it (low ball more likely) and trades a little end of Dec to move the "market". last year a broker had an aggressive price but wasn't shouting it down the line, hoping the trader friend gets away with printing it on the screen without trading. traded a small amount against one of them late Dec last year, made a bit on the trade.

    again, same as the risk guys, my product control can't be bothered too much by the fact that a certain swap hardly trades 20k/ basis point in a week, while my exposure is 20 times that. they just need that damn number on their screen for "mark to market". neither can the quants be bothered by what that means to their fancy models, these are just petty market details not worth their PhD level attention.

    I gave an extreme example, but believe the same happens in all market bubbles. the uderlying assumption of this particular approach seems to be that all unrealized gains out there can be realized at that magic price on the screen. like saying a bird in hand is worth exactly one bird in the bush. I think that needs to be fixed, people should be rewarded on realized gains primarily, rather than mark to make belief profits.

    now, it may well be that I am attacking an argument that nobody made :) but I do hate "mark to market". my view is, if it's a gain, reserve a lot of it until realized, it it's a loss, show it. the principle of prudence.

  21. Rick, Yep, I hear what you say loud and clear, we are on the same wavelength (during my time at Bankers Trust, I also often had to push product controllers to accept more prudent marks and reserves than warranted by the apparent immediate volatility that one could find in the market, to the point that my reval were dubbed as "dangerously conservative").

    I grant you that MTM will never be a perfect science and am also a fan of the "when in doubt, reserve" principle. Also, if in doubt, the last word between the trader and the accountant should belong to whoever comes up with the most prudent mark according to your principle. In another situation with a European bank, I found myself fighting to get product controllers accept a more prudent reserve on a 20-year exotic should the trader, the laughable counterargument being that such would have exceeded the policy reserve vetted by internal audit ! Recent hiccups in massaged marks on exotics, CDOs etc. will hopefully be a long-overdue wake-up call but banks and financial institutions have a notoriously short memory.... ;-)

  22. For once I agree with you about the straw man argument. But why complain, your book throws out a bunch of anecdotes that can't be verified about random risk situations/traders which in fact never create any type of systematic failure to support your thesis that tight coupling and complexity is the "Demon" and causes systematic risk. I guess it is ok for you to use straw man arguments but not anyone else.

  23. isn't it inconsistent to acknowledge fat tail risk and then go ahead and lever yourself up 30-1 or 40-1 in illiquid securities? I mean, use enough leverage and even a normal distribution is going to blow you up if you play long enough.

  24. Yes, it is inconsistent. So for someone along the way, either fat tails are not a straw man -- they really don't get it -- or they have incentives which make them uninterested in the potential effect of the fat tails. Maybe not the risk manager, though who knows; but more likely the traders or even the CEO.

  25. Yes, as a trader we all know about fat-tails and company. But I could hardly agree though that the case raised in numerous articles and books by Taleb et al. could honestly be classified in the "Straw Man" camp.

    Traders, Risk Officers and Senior Management ignore these "problems" and short-comings in modeling methodology because there's safety in numbers -- everyone else believes in Gaussian Copulas to manage CDO portfolios, "Hey! What's my upside to going out on a limb?" is the reason behind stepping out from the pack, and I think Taleb makes a strong case, with extensive research to help wake the sleeping sheep.

  26. Taleb does indeed field impressive artillery both in terms of quantitative trading knowledge and cogency of arguments. While amongst his fans, I nevertheless fear that, in the real world, major trivial but extremely important issues have to be sorted out first to eradicate the problem. Possibly the key one is the existence of pervasive accounting-based incentives for virtually every organization, particularly in financial services. Since accounting is the key lingua franca atop organizations, is it any wonder that banks have made a business out of selling what are in essence out-of-the-money options (be they on credit, unlikely events or liquidity itself)?

    The popular fixation of people on prices - as opposed to probabilities - was best embodied by politicians themselves in the recent Congressual pressure on FASB to relax MTM rules under FASB 157. As long as performance and comp are driven by accounting - rather than risk - changing the incentives will remain an uphill battle and organizations will repeat the same mistakes in the future.

  27. About a year ago, I met Taleb at a book signing, and I wanted to ask him what he thought of Rick's ideas -- particularly how system complexity conspires to produce surprising events. Unfortunately I erred in my approach: I started, "Have you read Rick Bookstaber's book?" His brusque reply was, "I don't read finance." I wasn't capable of engaging him myself, but I'd definitely like to see a debate on this topic.

  28. Every junior trader with 2+ derivatives experience knows about the large tail risk. That's why there's a skew/smile on almost every volatility instrument on the planet since the 70's! The real issue is there's a high cost associated with hedging that tail risk. Are you willing to pay for those teeny options?

    As one of my old, brutally honest, colleague said: on wall street, every put is for free. Every strategy: risk arb, stat arb, you name it, is about selling that free put. 9 years out of 10, you collect the premium and go home a rich man. And that 1 year when every thing blows up, there's always some idiot in fixed income who loses 100 time more than you!

    It's not about statistics, it's all about conflict of interest! When you are managing OPM (other people's money), the temptation is always there. And the worst part is when you tell your investors that your return is not as good as the next guy because you are hedging the tail risk, THEY PULL THEIR MONEY OUT!


  29. Is there any risk manager who does not understand that VaR will not capture the risk of market crises and regime changes?

    Yes, unfortunately there are risk managers like this, even at banks where you would have never expected this. Running an h-var in good times and using it as a basis for strategic decisions without even realizing that it is like driving while looking into the rear view mirror.

    But even simpler things happen, like traders doing back-2-back deals and completely forgetting about counterparty risk. Basically renting out the credit rating of their institution without charging a premium for this.

    You name it, you'll find it!