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Models On Models

It seems clear that one of the big reasons why finance theoreticians may resist and despise the criticisms of finance theory (even the calls to ban finance theory as deleterious to the world´s health) is that a theory-less universe would deprive them of the capacity to model. If modeling is possibly useless and potentially dangerous, do we need modelers at all?

I have a solution for the understandable angst that some modelers may feel these days, faced more than ever with external scepticism and cynicism as to their contributions. Why not model about the limits and dangers of modeling? Rather than spent yet more time dealing with some technical minutiae of existing models, why not build a model analyzing the impact on markets and the economy of existing models?

So no more papers on, say, VaR. Rather, papers on how VaR´s presence in financeland poses risks for the world. Make it as mathematical as you want.

No more models, rather more models on the dangers of models.

The Shreve-Triana Debate

Courtesy of QuantNet

Steve Shreve on Pablo Triana’s The Flawed Math of Financial Models Editor’s note: Following Prof. Shreve’s article, we received a response from Mr. Triana on Jan 10 which we have published in full. It can be seen directly after Prof. Shreve’s article.

By STEVE SHREVE

In his article “The flawed math of financial models”, Financial Times, November 29, Pablo Triana seeks to fix a large portion of blame for the world-wide financial crisis on “quants” in the finance industry and the programs that educate them. Mr. Pablo recommends radical reform in such programs. Others, carrying these ideas farther, call for a diminished role for quants in finance.

Any discussion of quants in finance must begin with the recognition that the global integration of economies and the associated complexity of our financial system has made the use of mathematical models an indispensable tool. Rules-of-thumb and intuition will not suffice when multi-national firms face exchange rate risk, funding risk and commodity price risk, when insurance companies and pension funds face longevity risk, when financial institutions are called upon to mediate these risks, and when regulators are charged to oversee these institutions. This was recognized in the recent U.S. financial reform legislation, which authorized a government Office of Financial Research whose task in 2008 would have been to alert policy makers to the ridiculously large naked position in credit default swaps held by AIG and to predict the effect of the failure of Lehman Brothers. Such an office must necessarily be populated by quants, people who can build models into which information about financial institutions is fed.

What then is the appropriate training for quants? I believe we should focus on three aspects.

Most importantly, a quant must be competent in the technical disciplines of mathematics, statistics and computer programming, and she must be knowledgeable about financial markets. Achieving competence across this broad spectrum is a tall order. But it must be done because a well-intentioned incompetent quant is as dangerous to the financial system as a well-intentioned incompetent doctor is to personal health. The primary focus of the educational programs at Carnegie Mellon will remain the creation of competent graduates. This is what we do best.

But a good quant also needs good judgment. A wise quant takes to heart Albert Einstein’s words, “As far as the laws of mathematics refer to reality, they are not certain; and as far as they are certain, they do not refer to reality.” All models are wrong. Judgment is needed to know when an admittedly wrong model can be helpful and when it is dangerous. This kind of judgment is acquired primarily through experience, but we can begin teaching it in the classroom. Since the financial crisis, we have invited participants in the crisis to speak in detail to our students about deals that went bad, describing how the deal was analyzed, why it was approved, and what was overlooked.

Finally, we need people with integrity managing our financial systems. Teaching ethics is difficult, and guaranteeing that listeners will implement those teachings is impossible. It is not easy for a quant to sound the alarm that his models are being stretched beyond their limits, knowing that if he is taken seriously it will result in the loss of business to competing firms and may result in the loss of his job. We cannot instill in sixteen short months behavior that properly requires years of nurturing and mentoring. We do what we can, leading by example, penalizing students for academic dishonesty, setting and enforcing rules for ethical conduct when interacting with potential employers, posing ethical dilemmas for classroom discussion, and encouraging our graduates to consult with fellow graduates when facing tough ethical decisions.

A lesson that can be learned from the present crisis is that if everyone implements the same good idea, their collective action can invalidate the assumptions that made the idea good. If everyone assumes that U.S. housing prices cannot decline and makes large bets based on that assumption, their collective action will ultimately bring about a decline in housing prices. This is not a new lesson; it is the lesson of every bubble. A feature of the most recent bubble is that quantitative analysis contributed to a false sense of security that encouraged firms to scale up risks. In some cases senior managers and even quants themselves did not appreciate the limitations in the models on which they based their risk analysis. Our students do not begin their careers at the level where the disastrous decisions were taken, and only a handful of them will ever reach those positions of power. Nonetheless, in the short time they are in our care, we seek to the extent possible to make them competent quants who exercise sound ethical judgment.

About the Author

Steve Shreve’s books The Binomial Asset Pricing Model and Continuous-Time Models are the required textbooks for many MFE programs’ Stochastic Calculus courses. He is a professor at Carnegie Mellon University and one of the co-founders of the M.S. in Computational Finance at Carnegie Mellon.

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The following is a response by Mr. Triana sent to Quantnet on Jan 10, 2010.

By PABLO TRIANA

Let me first say that I deeply admire Professor Shreve. Though my mathematical background does not empower me to fully appreciate his scientific prowess (not that his unparalleled global reputation would ever necessitate my feedback as further support), I am aware that in replying to his analysis of my recent FT article on quant education I am addressing most possibly the world´s leading light when it comes to stochastic calculus and mathematical finance. And far from an aloof researcher, Professor Shreve is also a very successful and ingenius academic entrepreneur, having taken a leading role in the development and management of one of the most exciting and path-breaking university graduate programs ever devised. To top it all, I can personally attest to his human generosity and kindness, getting misty-eyed as I recall the time when Professor Shreve, now about a decade ago, kindly accepted my invitation (as President of NYU Stern´s Financial Engineering Association) to regale us with a wonderful lecture and an even more pleasant follow-up dinner at a fancy Soho restaurant. I vividly recall him being impressed by my thorough knowledge of and interest in his legendary Computational Finance program at Carnegie Mellon, to the point of asking me why I had chosen NYU instead (I didn´t even try to apply to terrifyingly intimidating Carnegie Mellon, acutely aware of my negligible chances at getting in; I ain´t no rocket scientist, folks!).

In sum, it is not only my responsibility but also my pleasure to try to address Professor Shreve´s rebuttal as respectfully as possible, given the caliber of the counterparty. I hope I manage to succeed at this, if not so much at triumphing in the debate. Some initial clarifications are in order. I don´t really blame quants and quant programs for the crisis. I blame the use of certain models for the crisis. I don´t really care if those using, peddling, and imposing the deleterious models were quants, traders, salesmen, or fast food caterers. My goal is not to target specific groups of people, my goal is to target specific analytical concoctions. Having said that, it is true that a lot of quants vouch for those models both inside and outside the financial industry and, much more critically, vouch fanatically for the quantification of finance in general. As long as such belief is held and enthusiastically pushed, we can get in trouble because the potential for bad models to infiltrate the markets would be made that much larger. We need to create much more restrictive filters when it comes to welcoming mathematical finance wizardry into the realm of practice. Quants and quant programs could and should have been much less permissive and much more critical. Roadblocks to dangerous models should have been forcefully built by those who best understand the mechanics. So, yes, quants and quant programs could in the end be subjected to one type of accusation: neglect.

Everything stated in Professor Shreve´s response makes a ton of sense, and one can´t help but wholeheartedly agree. But, like other famed quants too graced with the ability to muse gracefully and the valour to challenge flawed quanty practices, Professor Shreve does not go far enough. Just like Emanuel Derman, Paul Wilmot, or Ricardo Rebonato, Professor Shreve needs to get closer to Nassim Taleb (and, maybe, my very humble self) and take things a step or two further and engage in a healthy dose of loud name-calling and unabashed denunciation. It is not enough to state that quantitative analysis played a role in the crisis by encouraging misplaced confidence or that many misunderstood the maths. It is imperative to endlessly fingerpoint the main culprits, essentially VaR and Gaussian Copula (to Professor Shreve´s credit, he went after the latter in a recent piece), and to make sure that such utterly failed tools are never again given the keys to the risk kingdom. Demonstrably flawed and lethal models should be banned from the land, and the real reasons for their original embracement intrusively inquired. VaR can no longer be part of banking regulations. These things can´t continue being taught, unless they are presented as the bad that can emerge from the quant lab. More pressing still, those failures must serve as catalyst to force everyone to revisit whether finance can and should indeed by mathematized. Are VaR, Gaussian Copula, Black-Scholes, Portfolio Theory, or Financial Econometrics isolated cases of failure, or rather inescapable proof that financial theory is bound to be at best useless and at worst crisis-igniting? We urgently need a Mathematical Finance Council of Nicaea, so that these pressing questions are answered once and for all. I wrote my Lecturing Birds On Flying in a naively idealistic attempt to help kick-start such process. Will the best that the discipline has to offer, like Professor Shreve, pick up the gauntlet?

This is no time for mincing words, it´s time to act. Back in 1994, Carnegie Mellon showed untold innovativeness and courage by correctly embracing the forcefully emerging field of financial engineering. It became the indisputable world beater. Now, with the discipline in tatters and accused of horrible crimes, the same institution should once more display one-of-a-kindness and lead the second quant finance revolution, the one that ought to make sure that models and financial stability can coexist side by side and the one not afraid to terminally castigate those naughty analytical concoctions that wreak havoc.

About the Author

Pablo Triana is the author of Lecturing Birds On Flying: Can Mathematical Theories Destroy The Financial Markets? (Wiley)

I´m still here Trackstar

I went away for a while, but never entirely left. Will try to resume my blogging responsibilities full-throttle. To be honest, I just write less in general these days (have a new job plus spent some time in book-promotion rehab).

I did publish a VaR piece (another one!) recently (had an interesting reply from a famous author-academic, will share with you here shortly). Will run something largish on the impossibility of knowing in finance next month.

Re Lecturing Birds, to be honest I am somewhat disappointed by the sales figures (10k give or take). Given the timeliness of the topic I was hoping for a more receptive response, but hey no one really knows why books sell or don´t sell. I still, naturally, like my humble tome very much.

Will post stuff on the book business, I find it unique in that 99% of the makers of the product can´t make a living out of it. I can´t think of any other business where this applies. And even more puzzling is that people still want to be authors.

Keep in touch.

Quantitative Echoes

Heard through the media grapevine after 1997 Asian crisis and 1998 LTCM crisis (which almost destroyed the system):

"The answer is not to reject quantitative finance but to be honest about its limitations. Models have their places but they must be coupled with more subjective approaches to risk, such as stress tests and scenario-planning"

Heard through the media grapevine after 2008 credit crisis (which destroyed the system and almost caused a global depression):

"The answer is not to reject quantitative finance but to be honest about its limitations. Models have their places but they must be coupled with more subjective approaches to risk, such as stress tests and scenario-planning"

To be heard through the grapevine after 2015 sovereign debt CDO crisis (which would do away with the euro, result in the acquisition of Greece by private equity funds, and force President Palin to expulse California from the Union):

"The answer is not to reject quantitative finance but to be honest about its limitations. Models have their places but they must be coupled with more subjective approaches to risk, such as stress tests and scenario-planning"

Quantitative Madoffs?

Let´s think about disgraced “financier” Bernard Madoff for a second. Why is he the uttermost epitome of inappropriate conduct? Why is he the poster child of fraudulent behavior? Why is he unremittingly fingerpointed as the exemplar of badness? Well, if we had to boil it down to a very quick rationale, it would be the following: Mr Madoff knowingly and vastly lied in matters related to financial activities, and such sizeable untruths caused untold despair and economic setbacks to others. That, in a nutshell, is his legacy to future explicators of financial happenstances. He will always be known as someone who produced deceitful fabrications that enriched him while impoverishing the many who got conned into believing.

My question is, shouldn´t we judge the rest of participants in the financial game by the “Madoff standard”? That is, shouldn´t those who, a la Bernie, contribute to monetary pain by purposely and deliberately duping the world also be loudly accused of fraud, relentlessly disgraced as scammers? I need to ask this, because it is not immediately obvious that those who share Madoff´s affinity for financial hoodwinking and capacity for social havoc-wreaking get called to task.

Take the promoters of quantitative finance. The complex mathematical concoctions that have been increasingly used in the markets for the past three decades have contributed to non-negligible chaos. In fact, it wouldn´t be far-fetched or insultingly irrational to argue that the employment of analytical models was behind the worst three market crisis since 1929. While an army of deniers remains hidden behind academic walls, it is by now pretty much conventional wisdom among many practitioners, analysts, and regulators that things like the Black-Scholes-Merton option pricing formula, the Value at Risk capital charge-setting radar, and the Gaussian Copula CDOs-rating model decisively aided and abetted the unleash of the malaises of October 1987 (one-day 25% drop on Wall Street, threatening the system), September 1998 (LTCM blow up, threatening the system), and 2007-2009 (credit crisis, destroying the system).

But even those who do admit to the failings of the quanty concoctions have typically shied away from being too harsh on the concocters and their intentions. When analyzing the excusing that has typically followed the (chaos-igniting) malfunctioning of the math, it is impossible not to distill the main message: the modelers were acting in good faith, honestly trying to model the market as accurately and truthfully as possible; unfortunately, things went awry once the analytics hit the street, but such outcome (aka as “the perfect 1000-year storm” among financial theoreticians) could not have been predicted by anyone. In other words, the argument would go, there was no equations-driven deceit. The math that was peddled would have been peddled in good faith, the models would have been prospectively assumed to be sound and trustworthy, to the best of the modelers’ abilities. Lots of folks may have lost tons of money as a result of imbuing the math into finance, but not, the excusers would point, as a result of the mathematicians cheating anyone.

Or did they? Bluntly put, the assumptions of many of the most widely used financial models are so egregiously unworldly, so alarmingly unrealistic, so impossibly unseemly that it is very very hard not to contend that many peddlers of the quantitative snakeoil must have been perfectly aware all along of the meaninglessness of some of the solutions. Possibly even of the danger that they pose. But the incentives not to share such beliefs and to instead defend the model´s robustness may have been irresistibly tasty. As long as the math is assumed to be reliable and sound, the mathematicians can enjoy the glamour and paycheques of finance. And the math can be a wonderful alibi for banks to engage in the kind of trades that they love most. By conveniently (and widely unrealistically) projecting very little risk ahead, VaR and the Gaussian Copula, for instance, decisively allowed Wall Street and the City to play the Subprime CDOs game that eventually killed us all. If you are a modeller, are you really going to out the models as useless and dangerous or are you going to continue to trot along and profitably rate garbage as if it were gold?

Naturally, by choosing the latter approach you would be incurring in intellectual fraud. People endowed with prestigious doctorates, and who might have previously dreamed of academic glory and yearned for the pure discovery of knowledge, would be corrupting sacred scientific methodologies. They would have contributed to transforming advanced mathematics and statistics into misleading sales pitches in search of a quick buck. They would be (knowingly) contributing to a lie that clouds understanding and that puts the world at large in undue danger. Is that a lesser crime than the one committed by Bernard Madoff?

Reuters - Dynamite The Nobel In Economics

http://blogs.reuters.com/columns/2009/10/09/dynamite-the-nobel-prize-in-economics/

October 9th, 2009 Dynamite the Nobel prize in economics Did you know that worms cause cancer? They don’t, of course, yet in 1926 Johannes Fibiger won a Nobel Prize in medicine for this “discovery.”

The Nobel committees for science prizes rarely make such amusing blunders, but those awarding the medal for economics have a long history of endorsing ideas that are useless, incorrect and even dangerous.

With the latest winner of the $1.4 million windfall due to be named on Monday, the case is stronger than ever for scrapping the prize altogether. The economics award — created in 1968 by Sweden’s central bank — has always been the odd man out.

Far from celebrating those who have “conferred the greatest benefit on mankind” as Alfred Nobel intended, the economics prize has done more harm than good.

The prize has fostered a faith in economists that is often misplaced. Friedrich Hayek, who won in 1974, said he would have advised against creating the award. The title, he said, “confers on an individual an authority which in economics no man ought to possess.”

Laureates, he suggested, should be required to take “an oath of humility … never to exceed in public pronouncements the limits of their competence.”

Sadly, economists, as a caste, have showed no such humility. The Nobel imprimatur has encouraged us to exaggerate the scientific quality of the dismal science.

Unlike their counterparts in physics, chemistry and medicine, economists have precious little predictive power. Lately, there has been much soul searching about the failure of economists to anticipate the 2008 meltdown. But given the profession’s history it would have been surprising if they had.

Over the past 20 years economists have failed to forecast any of the major twists and turns of the U.S. economy. Economists, as labor leader George Meany once grumbled, is “the only profession where a person could be considered an expert without having once been right.”

Worse still, the Nobel committee has set its seal on ideas that have been extremely toxic. Nobel Prize-winning theories were behind the biggest market meltdowns since the Great Depression.

In 1987, wide acceptance of the Black-Scholes-Merton option pricing model helped turn a market stumble into the worst one-day fall in Wall Street history, threatening the entire system. The model was rejected by traders, yet a decade later Robert Merton and Myron Scholes picked up their check from the Riksbank.

Or take Value at Risk models — backed by the Nobel Prize-winning portfolio theories of Harry Markowitz — which was culpable in both the panics of 1998 and 2008. These models helped justify skimpy capital ratios in the run-up to 2008.

“These theories have managed to transform tranquillity into turbulence, creating crises out of nowhere,” says Pablo Triana, author of “Lecturing Birds on Flying: Can Mathematical Theories Destroy the Financial Markets?” He adds: “The Nobel Prize helped give them respectability.”

And Nobel-endorsed economic theories helped justify the aversion to regulation showed by policy makers like Alan Greenspan. A long list of laureates from the Chicago school from Gary Becker to Edward Prescott helped promote the idea that governments should stand aside.

If the Swedish central bank wants to give away 10 million kronor a year, that is their business. But the prize should not be allowed to coast on the prestigious Nobel brand. Surviving relatives of Nobel are right to ask that their name be taken off the prize.

Aside from a new name, the prize should also come with a label:

WARNING: These theories should not be used by everyone. Side effects can include: financial crises, turbulent stock markets and banking collapse.

I Am A Lone Wolf Howling In The Wild

From Wells Fargo (ironically, one of the early pioneers in all things quant) I find it ever more puzzling that VaR defenders never say "VaR is good", rather they say "VaR is bad, but the least bad of all" So I guess for them the pre-VaR world was a cesspool of badness, a plague of incompetent war-scarred market warriors boorishly drawing on their experience-honed gut and intuition. The effrontery of such equations-lacking impudent rogues!

Editor's Note: Dave Napalo, Wells Fargo Senior Risk Management Specialist, answers questions from our readers, covering financial risk management concepts from the basic to the complex, giving you the background information you need to effectively manage the risks you face every day.

Q: I recently saw an opinion article in BusinessWeek that attacks VaR, or value at risk, as a questionable financial risk metric. Do you consider it a valuable tool? The author, Pablo Triana, seems like a lone wolf howling in the wild against many accepted quantitative practices and I am curious to know your stand on his criticisms.

A: For the record and for other readers who might want to consider the source document, the column appeared in the July 30, 2009 issue of BusinessWeek, and can be accessed at the following URL: http://www.businessweek.com/magazine/content/09_32/b4142068736481.htm

While you characterize Mr. Triana as "a lone wolf howling in the wind," the article, "The Risk Mirage at Goldman", echoes the concerns of the highly respected Nassim Taleb, author of The Black Swan. Mr. Taleb has also argued that VaR isn't effective at measuring risk. Triana is a firm believer in Mr. Taleb's work and has written many pieces arguing for the end of VaR as a risk measurement tool.

In addition, one could add Myron Scholes to the list of critics of VaR. Scholes, the co-creator of the Black-Scholes pricing model for options, has asserted that VaR models mistakenly assume that the volatility of asset prices and the correlations between prices are constant. Mr. Scholes knows whereof he speaks, having been up close and personal when the hedge fund he helped found, Long Term Capital Management, disintegrated in 1998 as debt markets collapsed in a manner models failed to anticipate.

The recent distress in the finance industry also must call into question the limits of VaR as a means of assessing risk. But to dismiss it out of hand, as Mr. Triana's column suggests, seems short-sighted. It's an argument that brings to mind the old saw attributed to Winston Churchill's assertion about democracy, with a twist for the financial world: Capitalism is surely the worst economic system, except for all the others that have been tried. And VaR might be the worst system for assessing risk, except for all the others that have been tried.

But specifically with respect to the article referenced, Mr. Triana sets out a series of arguments that seem particularly questionable when closely examined. His main proposal is that VaR, based on historical data, should be replaced with intuition and a common sense approach to measure the risk to which firms are exposed. He claims that firms are manipulating VaR to misrepresent their level of risk: "The person supplying the data to the model can essentially select any dates." Further, he argues categorically that financial institutions need to increase capital cushions and deleverage over-extended balance sheets. However, the question remains as to what level of capital is adequate.

Our rebuttal to Triana's arguments would revolve specifically around the following issues: (1) experience-based systems for measuring risk would still be based on the past-- specifically, a risk management practitioner's personal past and experiences; (2) there is no reason to believe that risk measurement manipulation would decrease with the abolition of VaR; and (3) an increase or decrease in capital-on-hand is a response to perceived risk; this does not make it a substitute for risk measurement altogether.

VaR provides an objective, non-biased method to systematically determine the risk of a portfolio's collective positions. It would be impossible to intelligently discuss a portfolio's risk components without actual, concrete numbers. One could obviously ask a trader how he feels about the risk in his trade book based on his personal intuition, but most managers of risk would in all likelihood prefer to see an objective non-biased assessment.

The author claims that VaR can easily be manipulated by cherry-picking data, which simply isn't true. Banks and other institutions are heavily regulated entities that must follow stringent rules to calculate their risks. Current regulation does not allow for obvious misrepresentations. Regardless, it's difficult to believe that experience-based measurement systems would be less susceptible to manipulation than a historical-data-based measurement tool. One of the oldest assumptions in any traded market is to be suspicious of a trader anticipating the future who is "talking his book." VaR may be subject to criticism, but human emotion and psychology are not forces to which it will fall prey.

While many may agree that banks and other financial institutions need to carry more capital as a cushion against potential losses, this is not relevant in a discussion of risk measurement techniques. VaR can be a useful tool to determine how much risk is inherent in a particular portfolio. The required capital reserves that should be on hand then become an extension of the amount of risk that needs to be offset. That, however, is a subjective assessment and is not a direct product of VaR, or any other system for measuring risk.

The financial crisis of 2008 and 2009 brings to light that VaR must receive a portion of the blame for what has transpired. After all, the financial fallout and massive write-downs of value from the financial industry indicate that VaR methodology did not accurately predict an outcome that we know only in retrospect presented a huge risk. This conundrum reminds me of an economist I once worked with who unwittingly and laughably had the penchant for announcing in his morning briefings, "We expect no surprises today." Surprises by their very nature are unknowable in advance.

VaR attempted to anticipate and measure risk, but was not prepared for the Black Swan that crossed its path as the housing market began a financial meltdown. The challenge and attendant opportunity now is for financial managers to expand their risk metrics knowing what recent history has instructed to make VaR a more robust tool for managing risk. VaR may not be an infallible predictor of the future, but our assertion is that it will work better than any rule-of-thumb guesstimate that Mr. Triana is pining for.

RIP Peter Bernstein

I still vividly remember reading his Capital Ideas on my Washington DC apartment´s couch almost fifteen years ago, being introduced for the first time to finance theory through his easygoing prose

I know that we (I) have criticized theory and theorists quite intensely in these blogs (mostly for good reasons I believe); but if I am honest I must admit that it was precisely those accomplishments (initially heard though the Bernstein grapevine) what originally ignited my interest in high finance and what inspired me to try to become a derivatives person. I very much doubt that I would have worked on a tradig floor, written financial books, and be penning this blog if I had not stumbled upon Capital Ideas all those years ago.

The advantage I had at the time is that, in my lovely innocent naivete, I didn´t know that the theories were wrong and all I saw through Berstein´s eyes were intelligent highly-credentialed people building rabidly sophisticated financial spacecrafts that promised to make tons of dough for their skippers. It was Capital Ideas that first made me want to become a financial astronaut. So in a big sense, and perhaps rather paradoxically for those who read my not-so-innocent current musings, I am in debt to theory-revering Peter Bernstein.

Not sure what he would have made of Lecturing Birds or my myriad of theory-doubting articles, but I hope that he would have found my arguments honest and truth-seeking, even if possibly not entirely his cup of tea. What I most certainly hope is that he wouldn´t have been taken completely aback by them. After all, without his initial inspiration it is a safe bet that those arguments would have never been transformed into printed ruminations.

Why Theoreticians Dominate Economics

Courtesy of FT´s Gideon Rachman, one of the best explanations I´ve ever heard on why obscurantists took over the campus:

"I heard something similar recently from a friend who teaches economics at Oxford, who was bemoaning the fact that the course there is increasingly maths-based. His explanation is that maths-driven economics is so obscure and uninteresting to the outside world, that the academics who specialise in it can spend all their time in Oxford, taking over the faculty. By contrast, the economists whose work is empirical and expressed largely in English find themselves in demand in the outside world - and therefore do not have the time to block the forward march of the mathemeticians"

As Taleb says in the foreword to my Lecturing Birds, it is history written by the losers. The guys no one could care about end up dominating the department (and thus the outside world´s overall perception of the Economics discipline) PRECISELY because no one gives a damn about them. Darwinism in reverse! Those discarded by the world survive, those embraced by the world perish The freak no one wants to be around wins, precisely because of his unbearable freakishness. I mean, I totally concur. Have you ever met an orthodox, cloistered economist? Did you also have the feeling that you were talking to Frankenstein or some other type of weird creature? Someone very very freaky. Very very unpleasant.

No, I don´t mean nerds. Economists are not nerds (they wish). Bill Gates is a nerd, the Google guys are nerds, Steve Jobs is a nerd. The world needs nerds, we love them, we want them, we embrace them, we admire them, we envy them, we want to be like them. But who the heck would want to be like an orthodox cloistered economist, envy them? Orthodox economists are the wrong kind of geek. Completely noncreative, just exam-taking idiot savants who had no option but to get straight As because they could not do anything else with their lives. And they know that full well, thus their Torquemada-like repressive and persecutoty attitude towards those more creative, more dynamic, more wordly, more brilliant. And thus their incontrollable cynicism and to-the-bone intellectual corruption.

Best thing I ever did in my entire life was spend my Economics undergraduate years doing anything but studying (dogmatic, stubbornly orthodox) Economics

Soderling Is The Real Black Swan

If Robin Soderling wins Roland Garros this weekend, that would truly be a Black Swan. Possibly more so than the fall of Lehman or October 87. In fact, by beating Nadal the Swede has already gained swany status. In tennis, the rare event is way way less probable than in the markets. A non-top tier player almost never reaches a Grand Slam final, let alone win one. There´s no crash, no meltdown, no outlier in tennis.

As a staunch Federer supporter I pray for normality to rule once more on the court. But I also fear that the Black Swan, having so insultingly dominated its more habitual financial surroundings for the past couple of years, may have grown bold enough to extend its supremacy into the Parisian clay.

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