naked capitalism

By George Washington of Washington’s Blog.

Investors are basically rational, right?

In fact, as many studies have demonstrated, the answer is no.

But instead of wading through all of the investment psychology research, let’s look at research into people’s basic reasoning abilities. Bear with me for a minute. A study in an area unrelated to investing sheds light on people’s basic thinking processes.

Sociologists from four major research institutions investigated why so many Americans believed that Saddam Hussein was behind 9/11, years after it became obvious that Iraq had nothing to do with 9/11.

The researchers found, as described in an article in the journal Sociological Inquiry (and re-printed by Newsweek):

• Many Americans felt an urgent need to seek justification for a war already in progress

• Rather than search rationally for information that either confirms or disconfirms a particular belief, people actually seek out information that confirms what they already believe.

• “For the most part people completely ignore contrary information.”

• “The study demonstrates voters’ ability to develop elaborate rationalizations based on faulty information”

• People get deeply attached to their beliefs, and form emotional attachments that get wrapped up in their personal identity and sense of morality, irrespective of the facts of the matter.

• “We refer to this as ‘inferred justification, because for these voters, the sheer fact that we were engaged in war led to a post-hoc search for a justification for that war.

• “People were basically making up justifications for the fact that we were at war”

• “They wanted to believe in the link [between 9/11 and Iraq] because it helped them make sense of a current reality. So voters’ ability to develop elaborate rationalizations based on faulty information, whether we think that is good or bad for democratic practice, does at least demonstrate an impressive form of creativity.

An article yesterday in Alternet discussing the Sociological Inquiry article helps us to understand that the key to people’s active participation in searching for excuses for actions by the big boys is fear:

Subjects were presented during one-on-one interviews with a newspaper clip of this Bush quote: “This administration never said that the 9/11 attacks were orchestrated between Saddam and al-Qaeda.”The Sept. 11 Commission, too, found no such link, the subjects were told.

“Well, I bet they say that the commission didn’t have any proof of it,” one subject responded, “but I guess we still can have our opinions and feel that way even though they say that.”

Reasoned another: “Saddam, I can’t judge if he did what he’s being accused of, but if Bush thinks he did it, then he did it.”

Others declined to engage the information at all. Most curious to the researchers were the respondents who reasoned that Saddam must have been connected to Sept. 11, because why else would the Bush Administration have gone to war in Iraq?

The desire to believe this was more powerful, according to the researchers, than any active campaign to plant the idea.

Such a campaign did exist in the run-up to the war…

He won’t credit [politicians spouting misinformation] alone for the phenomenon, though.

“That kind of puts the idea out there, but what people then do with the idea … ” he said. “Our argument is that people aren’t just empty vessels. You don’t just sort of open up their brains and dump false information in and they regurgitate it. They’re actually active processing cognitive agents”…

The alternate explanation raises queasy questions for the rest of society.

“I think we’d all like to believe that when people come across disconfirming evidence, what they tend to do is to update their opinions,” said Andrew Perrin, an associate professor at UNC and another author of the study…

“The implications for how democracy works are quite profound, there’s no question in my mind about that,” Perrin said. “What it means is that we have to think about the emotional states in which citizens find themselves that then lead them to reason and deliberate in particular ways.”

Evidence suggests people are more likely to pay attention to facts within certain emotional states and social situations. Some may never change their minds. For others, policy-makers could better identify those states, for example minimizing the fear that often clouds a person’s ability to assess facts …

The Alternet article links to a must-read interview with psychology professor Sheldon Solomon, who explains:

A large body of evidence shows that momentarily [raising fear of death], typically by asking people to think about themselves dying, intensifies people’s strivings to protect and bolster aspects of their worldviews, and to bolster their self-esteem. The most common finding is that [fear of death] increases positive reactions to those who share cherished aspects of one’s cultural worldview, and negative reactions toward those who violate cherished cultural values or are merely different.

Fear in the Economic and Financial Arenas

Has something similar happened in the economic/financial arenas?

Congressmen Brad Sherman and Paul Kanjorski and Senator James Inhofe all say that the government warned of martial law if Tarp wasn’t passed. And Rahm Emanuel famously said:

Never let a serious crisis go to waste. What I mean by that is it’s an opportunity to do things you couldn’t do before.

Last year:

• Senator Leahy said “If we learned anything from 9/11, the biggest mistake is to pass anything they ask for just because it’s an emergency”

• The New York Times wrote:
  

  “The rescue is being sold as a must-have emergency measure by an administration with a controversial record when it comes to asking Congress for special authority in time of duress.”
  ***

  Mr. Paulson has argued that the powers he seeks are necessary to chase away the wolf howling at the door: a potentially swift shredding of the American financial system. That would be catastrophic for everyone, he argues, not only banks, but also ordinary Americans who depend on their finances to buy homes and cars, and to pay for college.

  Some are suspicious of Mr. Paulson’s characterizations, finding in his warnings and demands for extraordinary powers a parallel with the way the Bush administration gained authority for the war in Iraq. Then, the White House suggested that mushroom clouds could accompany Congress’s failure to act. This time, it is financial Armageddon supposedly on the doorstep.

  “This is scare tactics to try to do something that’s in the private but not the public interest,” said Allan Meltzer, a former economic adviser to President Reagan, and an expert on monetary policy at the Carnegie Mellon Tepper School of Business. “It’s terrible.”

Not Just Government

But it’s not just government . . .

If the too big to fails say that the world economy will crash and there will be martial law unless they are bailed out, politicians – most of whom don’t understand finance or economics – will believe them, and sound the alarm themselves.

As Karl Denninger wrote yesterday:

[AIG's CEO] left Geithner with two documents. One was a fact sheet that listed all the attributes of AIG FP [the division run by Joe Cassano that blew the company up] and argued why it should be given status as a primary dealer. The other–a bombshell that Willumstad was confident would draw Geithner’s attention–was a report on AIG’s counterparty exposure around the world, which included “2.7 trillion of notional derivative exposures, with 12,000 individual contracts.” About halfway down the page, in bold, was the detail that Willumstad hoped would strike Geithner as startling: “$1 trillion of exposures concentrated with 12 major financial institutions.”

Was that a threat?

And isn’t threatening the United States (whether directly or otherwise) something you’re not supposed to do?

Sounds like “Bail me out or I will crash everything.”

Isn’t that analagous to walking into a bank, opening one’s coat to reveal an explosives-laced belt, and saying “gimme all the money or everyone dies!”

Yves Smith has previously used a similar analogy.

Fear Among Individual Investors

Investors – as with politicians or Americans in general – believe that “when [they] come across disconfirming evidence . . . . they tend to … update their opinions”, but in reality, they cling to the beliefs they formed during certain heightened emotional states, such as fear.

Fear turns people into sheep. Once they are sheep, they will strive mightily to justify the actions of their “leaders” – whether those leaders gave trillions of dollars in bailouts or got us into war, and even if the leaders’ justifications were false.

I believe this dynamic is also playing out in the fact that many Americans assume that the government has a real plan for fixing the economy, is working as hard as it can to do so, and that – eventually – things will improve.

Just as most Americans believe “since we’re at war in Iraq, and since the government previously claimed that Saddam was behind 9/11, he must have been”, they are probably thinking “since the government gave trillions to the giant banks and said that economists have figure out how to fix things, they must have done what was needed, and things will turn around in a v-shape recovery”.

The lengths people go to rationalize a false link between Saddam and 9/11 is a great example, because it may reveal by analogy how far people will go to justify their trust in our economic leaders and in their own investment decisions.

Of course, the yearning for high returns is the other half of what drives investor psychology. But this essay focuses on fear.

A fascinating and somewhat disturbing article at the New York Review of Books by Jerome Groopman looks at what counts for progress in medical diagnosis and finds it to be more of a mixed bag than most readers would assume. This won’t come as much of a surprise to those who know a bit about the field (one of my colleagues who worked at the National Institutes of Health called it “a medieval art”). But what is a tad disconcerting is that the efforts to make medicine more scientific may not in fact be a plus.

That may sound simply bizarre to readers. Isn’t evidence based medicine a good thing? Well, maybe not.

One of the reasons this piece struck a chord with me is that some of the efforts to make medicine more scientific parallel, in their negative aspects, the push to make economics more scientific. In medicine, this means developing more rules and tools for diagnosis; in economics, the course chosen was to impose more “rigor” which meant make greater use of mathematical exposition (proof-like theoretical papers) and to have “empirical” papers centered around statistical analysis of data sets.

Now while this all may sound well and good, in fact, both are methodological choices that limit investigation. For instance, evidence based medicine seeks to gather symptoms and then use that to determine what the ailment might be. Well, the problem is these protocols have been developed from people with only one thing wrong with them. Many people who show up in doctor’s offices have multiple pathologies. So a lot of effort is being expended to develop an approach that has limited value in the field, and worse, doctors are increasingly expected to conform to it.

An analogous problem in economics is the discipline has to ignore of finesse the role of uncertainty (unknown unknowns, as opposed to risk, outcomes that can be estimated with some precision). Frank Knight and John Maynard Keynes were both leery of undue reliance on math (and both were skilled in the art) for that very reason.

Another way that the desire to systematize medicine may not represent progress is that it limits doctors’ observational methods. Doctors look at a number of elements of a patients’ condition: skin tone, energy level, the quality of their breathing. Some of these do not fit neatly into diagnostic scoring methods and are thus discarded, resulting in information loss. There is in particular in medicine a distaste for seemingly old fashioned diagnostic methods even when they are more accurate than tests. My favorite pet peeve here is mammograms. A manual breast exam, whether done by the patient herself or by an experienced examiner, is far more successful at picking up the fast moving, dangerous cancers that pose a health risk. Mammograms are in fact a lousy test, good at picking up benign or slow moving growths (the ones patients will die with rather than of) and poor at picking up the deadly type. But women are hectored to have mammograms and they are falsely treated as a gold standard. Again, the analogy in economics is the preference for using data sets, and not having much interest in analyses that include hard and qualitative data (an author might include some discussion in a narrative section of his paper, as illustration or qualification, but there is not much receptivity to using qualitative analysis to supplement data sets with gaps).

Perhaps most important, Groopman stresses that the focus on methodology is dehumanizing medicine.

The ability to recognize complex patterns is one of our highest forms of intelligence, and one both disciplines seem inclined to devalue. Admittedly, as Malcolm Gladwell demonstrated in his book Blink, this faculty can be remarkably accurate or wildly wrong. Somehow, embracing technology too often leads to a rejection of older approaches, rather than figuring out how to use the best of both methods.

From Groopman:

Carrying the Heart: Exploring the Worlds Within Us
by F. González-Crussi
Kaplan, 291 pp., $26.95

The Deadly Dinner Party and Other Medical Detective Stories
by Jonathan A. Edlow, M.D.
Yale University Press, 245 pp., $27.50

Several months ago, I led a clinical conference for interns and residents at the Massachusetts General Hospital…

The subject of the conference centered on how physicians arrive at a diagnosis and recommend a treatment—questions that are central in the two books under review. We began by discussing not clinical successes but failures. Some 10 to 15 percent of all patients either suffer from a delay in making the correct diagnosis or die before the correct diagnosis is made. Misdiagnosis, it turns out, is rarely related to the doctor being misled by technical errors, like a laboratory worker mixing up a blood sample and reporting a result on the wrong patient; rather, the failure to diagnose reflects the unsuspected errors made while trying to understand a patient’s condition.[1]

These cognitive pitfalls are part of human thinking, biases that cloud logic when we make judgments under conditions of uncertainty and time pressure. Indeed, the cognitive errors common in clinical medicine were initially elucidated by the psychologists Amos Tversky and Daniel Kahneman in their seminal work in the early 1970s.[2] At the conference, I reviewed with the residents three principal biases these researchers studied: “anchoring,” where a person overvalues the first data he encounters and so is skewed in his thinking; “availability,” where recent or dramatic cases quickly come to mind and color judgment about the situation at hand; and “attribution,” where stereotypes can prejudice thinking so conclusions arise not from data but from such preconceptions.

A physician works with imperfect information. Patients typically describe their problem in a fragmented and tangential fashion—they tell the doctor when they began to feel different, what parts of the body bother them, what factors in the environment like food or a pet may have exacerbated their symptoms, and what they did to try to relieve their condition. There are usually gaps in the patient’s story: parts of his narrative are only hazily recalled and facts are distorted by his memory, making the data he offers incomplete and uncertain. The physician’s physical examination, where he should use all of his senses to try to ascertain changes in bodily functions—assessing the tension of the skin, the breadth of the liver, the pace of the heart—yields soundings that are, at best, approximations. More information may come from blood tests, X-rays, and scans. But no test result, from even the most sophisticated technology, is consistently reliable in revealing the hidden pathology.

So a doctor learns to question the quality and significance of the data he extracts from the medical history of the patient, physical examination, and diagnostic testing. Rigorous questioning requires considerable effort to stop and look back with a discerning eye and try to rearrange the pieces of the puzzle to form a different picture that provides the diagnosis. The most instructive moments are when you are proven wrong, and realize that you believed you knew more than you did, wrongly dismissing a key bit of information that contradicted your presumed diagnosis as an “outlier,” or failing to consider in your parsimonious logic that the patient had more than one malady causing his symptoms…

I worried aloud about how changes in the delivery of health care, particularly the increasing time pressure to see more and more patients in fewer and fewer minutes in the name of “efficiency,” could worsen the pitfalls physicians face in their thinking, because clear thinking cannot be done in haste…

Like all doctors educated over the past decade, the residents had been immersed in what is called “evidence-based medicine.” This is a movement to put medical care on a sound scientific footing using data from clinical trials of treatment rather than on anecdotal results. To be sure, this shift to science is welcome, but the “evidence” from clinical trials is often limited in its application to a particular patient’s case. Subjects in clinical trials are typically “cherry-picked,” meaning that they are included only if they have a single disease and excluded if they have multiple conditions, or are receiving other medications or treatments that might mar the purity of the population under study. People are also excluded who are too young or too old to fit into the rigid criteria set by the researchers.

Yet these excluded patients are the very people who heavily populate doctors’ clinics and seek their care…

At the conference, an animated discussion followed, and I heard how changes in the culture of medicine were altering the ways that the young doctors interacted with their patients. One woman said that she spent less and less time conversing with her patients. Instead, she felt glued to a computer screen, checking off boxes on an electronic medical record to document a voluminous set of required “quality of care” measures, many of them not clearly relevant to her patient’s problems…

During my training three decades ago, the team of interns and residents would move from bedside to bedside, engaging the sick person in discussion, looking for new symptoms; the medical chart was available to review the progress to date and new tests were often ordered in search of the diagnosis. By contrast, each patient now had his or her relevant data on the screen, and the team sat around clicking the computer keyboard. It took concerted effort for the group to leave the conference room and visit the actual people in need…

The two chief residents seemed deeply engaged by their patients’ lives and struggles, yet deeply frustrated, because that dimension of medicine, what is termed “medical humanism,” was, despite much lip service, given short shrift as a consequence of the enormous change in how medical care is being restructured.

What I heard from the residents at the Massachusetts General Hospital was not confined to that noon meeting or to young physicians. A close friend in New York City told me how his wife with metastatic ovarian cancer had spent six days in the hospital without a single doctor engaging her in a genuine conversation….no one attending to her had sat down in a chair at her bedside and conversed at eye level, asking questions and probing her thoughts and feelings about what was being done to combat her cancer and how much more treatment she was willing to undergo. The doctors had hardly touched her, only briefly placing their hands on her swollen abdomen to gauge its tension. The interactions with the clinical staff were remote, impersonal, and essentially mediated through machines.

Nor were these perceptions of the change in the nature of care restricted to reports from patients and their families. They were also made by senior physicians. My wife and frequent co-writer, Dr. Pamela Hartzband, an endocrinologist, reported conversations among the clinical faculty about how a price tag was being fixed to every hour of the doctor’s day. There were monetary metrics to be met, so-called “relative value units,” which assessed your productivity as a physician strictly by measuring how much money you, as a salaried staff member, generated for the larger department. There is a compassionate, altruistic core of medical practice—sitting with a grieving family after a loved one is lost; lending your experience to a younger colleague struggling to manage a complex case; telephoning a patient and listening to how she is faring after surgery and chemotherapy for her breast cancer; extending yourself beyond the usual working day to help others because that is much of what it means to be a doctor. But not one minute of such time may be accountable for reimbursement on a bean counter’s balance sheet.[5]

Still, I wondered whether my diagnosis of the ills of modern medicine was accurate. Perhaps I was weighed down by nostalgia, my perspective a product of selective hindsight. Certainly, coldly mercenary physicians were familiar in classical narratives of illness. Tolstoy satirized “celebrity doctors” who were well paid for offering Ivan Ilych ridiculous remedies for his undiagnosed malady while ignoring his suffering. Turgenev in “The Country Doctor” depicted an unctuous provincial physician whose degree of engagement with the sick was tied to the size of their pocketbook. Molière repeatedly lampooned the folly of pompous and greedy physicians.

Such doctors have been members of the profession since its founding. And it would be naive to believe that money is not one part of the exchange between physician and patient. But only recently has medical care been recast in our society as if it took place in a factory, with doctors and nurses as shift workers, laboring on an assembly line of the ill. The new people in charge, many with degrees in management economics, believe that care should be configured as a commodity, its contents reduced to equations, all of its dimensions measured and priced, all patient choices formulated as retail purchases. The experience of illness is being stripped of its symbolism and meaning, emptied of feeling and conflict. The new era rightly embraces science but wrongly relinquishes the soul.

n his book Carrying the Heart, Dr. Frank González-Crussi, a professor of pathology at Northwestern University, has made a sharp departure from medicine as a cold world of clinical facts and figures. Rather, he asks us to return to a view of the body not as a machine but as a wondrous work of creation, where both the corporeal and the spiritual coexist. His aim, he writes, is

to increase the public’s awareness of the body’s insides. By this, I do not mean the objective facts of anatomy, for most educated people today have a general, if limited, understanding of the body’s parts and functions. I mean the history, the symbolism, the reflections, the many ideas, serious or fanciful, and even the romance and lore with which the inner organs have been surrounded historically.

This précis captures the beauty and charm of his book. I learned from González-Crussi that for centuries the stomach was considered the most noble of organs, directing all important physiological functions. The ancients, González-Crussi tells us, called the stomach “the king of viscera,” “the senate or the patrician class; the bodily parts were the rebellious plebeians.” Shakespeare repeats this fable in Coriolanus, where the stomach lectures the rest of the body’s organs about the importance of its function.

Our gastric elements were seen as having a leading part in joy and adversity, and were the seat of the soul—predating the belief that the spirit was housed in the heart or the brain. This regal position was ultimately relinquished through the observations of Dr. William Beaumont in 1822. Beaumont studied a young French-Canadian named Alexis St. Martin, who suffered an accidental musket shot to the belly. He was left with a perforation some two and a half inches in circumference, through which the doctor could look into the living stomach and perform experiments on its workings. Via this “stomach window,” the physiology of the organ was gradually deciphered, and its fabled status faded.

No part of our anatomy, González-Crussi recounts, has failed to fascinate poets, priests, and philosophers—including the working of the colon. In the chapter on feces, we learn that the Chinese had a divinity of the toilet. “This was Zi-gu, ‘the violet lady.’ She was not entirely fictional,” González-Crussi writes,

but took her origin from a flesh-and-blood woman who lived about AD 689. To her misfortune, she was made the concubine of a high government official, Li-Jing. The man’s legitimate wife, overcome by jealousy, killed Zi-gu in cold blood while she was visiting the toilet. Since then, her ghost has haunted the latrines, “a most inconvenient circumstance for anyone in a hurry.”

The colon and its product also were part of the theology of the Aztecs. They believed that excrement

was capable of bringing ills and misfortune, and associated with sin, but also powerful and beneficent, able to ward off disease, to subdue the enemy, and to transform sexual transgressions into something useful and healthy.

Gold was termed “the sun’s excrement” and the sun god Tonatiuh deposited his own feces in the form of this precious element in the earth while he passed through to the underworld.

González-Crussi also reminds us that there was an inordinate fixation on one’s bowels during the Victorian age, which honored values of order, temperance, respect for tradition, and sexual repression. Personal self-control, the mark of British culture, was at odds with that urgent process of expelling air and waste:

Perhaps no greater ambivalence has ever existed toward the bowel than in Victorian England, where this organ was viewed with simultaneous skittish embarrassment and fascination, shame and fixed interest, shy modesty and hypnotic engrossment.
A shocking consequence of this cultural tension is that one of the most proficient surgeons of the era, William Arbuthnot Lane, who devised procedures to successfully set compound fractures, concluded that without a colon, man would free himself from inner toxins and extend his health and longevity. A natural physiological function became a pseudodisease. Initially, Lane devised operations to bypass the large bowel, and he then moved on to perform total colectomies. Patients flocked to him from all over Great Britain and abroad, certain that their lives would be more salubrious and fulfilling without their large intestine.

González-Crussi treats with similar scholarship and playful insight the uterus, the penis, the lungs, and the heart. He melds history with literature, religion with science, high humor with serious concerns. The sum of his narrative shows that medicine does not exist as some absolute ideal, but is very much a product of the prevailing culture, affected by the prejudices and passions of the time…But our culture, with its worship of technology and its deference to the technocrat, risks imposing an approach to medical care that ignores the deeply felt symbolism of our body parts and our desperate search for meaning when we suffer from illness…..

Jonathan Edlow is concerned with the doctor not as poet or philosopher or priest but as detective. An emergency room physician at the Beth Israel Deaconess Medical Center, a Harvard teaching hospital in Boston where I also work…Both detective and doctor not only assemble evidence but must judiciously weigh what they have found, seeking the underlying value of each clue. The successful doctor-detective must be alert to biases that can lead him astray. This was the message of the clinical conference those months ago; and in Edlow’s tales of difficult diagnoses, we can observe detours that are due to “anchoring,” “availability,” and “attribution.”…

In his chapter “An Airtight Case,” Edlow implicitly shows why so many of the standard formulas that policymakers promulgate fall short when answers are not obvious. He describes how an office worker (whom he calls Philip Bradford) thought he had developed “the flu—the usual cough, fevers, chest pain, just feeling lousy….” What appeared to be the symptoms of a typical viral illness did not spontaneously disappear. A chest X-ray showed pneumonia, but treatment with antibiotics proved ineffective. The presumptive diagnosis changed from infection to cancer, and Bradford was told by his doctor that he needed his chest opened to resect a piece of lung and identify the tumor.

Fortunately, the patient sought a second opinion, from a senior thoracic surgeon, and the diagnosis was again thrown into doubt—the specialist believed that the problem was neither infection nor an abnormal growth. Over the ensuing months, the mysterious pneumonia spontaneously cleared up, but after a year Bradford again started coughing and running a fever. “His chest X-ray blossomed with ominous nodules,” Edlow writes, “then, as with the previous episode, after a few weeks his symptoms mysteriously vanished.”

It was the good fortune of this ill office worker with the mysterious lung problem to see Dr. Robert H. Rubin, an infectious disease specialist at the Massachusetts General Hospital….what is striking is his “low-tech” thinking: “I was immediately impressed by three aspects of the case,” Rubin recalled.

First was that Bradford appeared healthy and athletic, not the picture of someone with a chronic disease. Second, between episodes, he continued to jog over five miles with no apparent problem. And third, his physical examination was normal.

With such comments, we are a universe away from sophisticated blood tests and CT scans, and deeply rooted in the world of the physician’s five senses. The most seasoned clinicians teach that the patient tells you his diagnosis if only you know how to listen. The clinical history, beyond all other aspects of information gathering, holds the most clues. And it is this part of medicine—the patient’s narrative, the onset and tempo of the illness, the factors that exacerbated the symptoms and those that ameliorated them, the foods the patient ate, the clothing he wore, the people he worked with, the trips he took, the myriad of other events that occurred before, during, and after the malady—that are as vital as any DNA analysis or MRI investigation.

Rubin concentrated that kind of questioning and listening on Bradford. He did not quickly dispatch him for more tests, but instead sharply shifted his focus to investigate clues in Bradford’s environment that could reveal what was causing inflammation in his lungs. Edlow goes on to write in clear and fluid prose about how Rubin systematically pursued what could be the agent provocateur in the case. The lengths to which Rubin went are extraordinary, his skill in eliciting and interpreting the patient’s narrative exemplary, and certainly not part of the rushed practice of today’s clinic. I won’t spoil the end of the story; what is important is that the solution came about only by dogged thinking that required the kind of time and inquiry that is absent in much of modern medical care.

The other detective stories in Edlow’s compilation transmit the same message: we most need a discerning doctor when a diagnosis is not obvious, when the clues are confusing, when initial tests are inconclusive. No simple technology can serve as a surrogate for the probing human mind. Edlow’s book is a welcome complement to González-Crussi’s. Both show us that medicine is truly an art and a science that requires doctors both to decipher the mystery and illuminate the meaning of the body in health and disease.

I have to admit, I have a weakness for the intersection of the daft and science:

Male readers will no doubt assume that this means the original owner of the gas mask bra must strip in the case of emergency, and that that the real point of this exercise. But the bra was designed by a woman who demonstrated at the ceremony that it could be removed discreetly. Hhm, I am sure such niceties would not be observed in a bona fide emergency.

The BBC gives a recap of the ceremony:

The Ig Nobel Prizes were presented to the winners by genuine Nobel laureates….

Past winners also returned to take part in the celebrations. They included Kees Moeliker, the discoverer of homosexual necrophilia in the mallard duck, and Dr Francis Fesmire, who devised the digital rectal massage as cure for intractable hiccups.

Each new winner was permitted a maximum of 60 seconds to deliver an acceptance speech. The time limit was enforced by an intractable eight-year-old girl.

The evening also featured numerous tributes to the evening’s theme of “Risk”.

A 15-minute risk cabaret concert by the Penny-Wise Guys preceded the ceremony, during which the band paid special tribute to fraudster Bernie Madoff.

Other winners per the Boston Globe:

Veterinary medicine: Dr. Catherine Douglas and Dr. Peter Rowlinson of Newcastle University, Newcastle-Upon-Tyne, UK, for showing that cows who have names give more milk than cows that are nameless.

Peace: Dr. Stephan Bolliger, Dr. Steffen Ross, Dr. Lars Oesterhelweg, Dr. Michael Thali, and Beat Kneubuehl of the University of Bern, Switzerland, for determining — by experiment — whether it is better to be smashed over the head with a full bottle of beer or with an empty bottle.

Economics: The directors, executives, and auditors of four Icelandic banks — Kaupthing Bank, Landsbanki, Glitnir Bank, and Central Bank of Iceland — for demonstrating that tiny banks can be rapidly transformed into huge banks, and vice versa — and for demonstrating that similar things can be done to an entire national economy.

Chemistry: Javier Morales, Miguel Apátiga, and Victor M. Castaño of Universidad Nacional Autónoma de México, for creating diamonds from liquid — specifically from tequila.

Medicine: Dr. Donald L. Unger, of Thousand Oaks, California, for investigating a possible cause of arthritis of the fingers, by diligently cracking the knuckles of his left hand — but never cracking the knuckles of his right hand — every day for more than 60 years.

Physics: Katherine K. Whitcome of the University of Cincinnati, Daniel E. Lieberman of Harvard University, and Liza J. Shapiro of the University of Texas for analytically determining why pregnant women don’t tip over.

Literature: Ireland’s police service, An Garda Siochana, for writing and presenting more than 50 traffic tickets to the most frequent driving offender in the country — Prawo Jazdy — whose name in Polish means “Driver’s License.”

Mathematics: Gideon Gono, governor of Zimbabwe’s Reserve Bank, for giving people a simple, everyday way to cope with a wide range of numbers — from very small to very big — by having his bank print bank notes with denominations ranging from 1 cent to 1 hundred trillion dollars.

Biology: Fumiaki Taguchi, Song Guofu, and Zhang Guanglei of Kitasato University Graduate School of Medical Sciences in Sagamihara, Japan, for demonstrating that kitchen refuse can be reduced more than 90 percent in mass by using bacteria extracted from the feces of giant pandas.

Conspiracy theorists will have to wait until the article described in Inside Science is published to determine whether it delivers on its claims. It claims to analyze stock holding across 48 countries and alleges they are held in very few hands. But the work was done by physicists, which means they may not have understood the limits of the data they were working with.

I suspect this will wind up resembling a paper a friend studied in his graduate level statistical methods course over two decades ago (he has since gone on to a successful career in academia). Everyone in the seminar was assigned a single paper and told to analyze the techniques used and to present their findings to the class. This was the sole basis for the grade.

The paper my buddy got had already created a bit of a stir, although it had not yet been published. The author had looked at the prices at which the Fed did its daily operations (then the famed “noon buying rate”) and compared it to the results of Treasury auctions. The paper concluded the Treasury was doing a terrible job, as demonstrated in all sorts of analyses.

When my friend’s day to present came, he stood up and said, “I have only one comment to make. The Fed conducts its daily operations in transaction sizes ranging in the millions. Treasury auctions are in the billions. The Fed data is irrelevant to the Treasury analysis,” and sat down.

He received an A.

In this case, an obvious fly in ointment is many (most?) stocks are held in street name, meaning in the name of the brokerage firm or fund, not the ultimate owner. I presume it is impossible to segregate accounts where the broker has discretion to trade versus those where the clients simply trades through the securities firm.

But even if the analysis is flawed, it might stir up some interesting discussion.

From Inside Science (hat tip reader John D):

A recent analysis of the 2007 financial markets of 48 countries has revealed that the world’s finances are in the hands of just a few mutual funds, banks, and corporations. This is the first clear picture of the global concentration of financial power, and point out the worldwide financial system’s vulnerability as it stood on the brink of the current economic crisis.

A pair of physicists at the Swiss Federal Institute of Technology in Zurich did a physics-based analysis of the world economy as it looked in early 2007. Stefano Battiston and James Glattfelder extracted the information from the tangled yarn that links 24,877 stocks and 106,141 shareholding entities in 48 countries, revealing what they called the “backbone” of each country’s financial market. These backbones represented the owners of 80 percent of a country’s market capital, yet consisted of remarkably few shareholders.

“You start off with these huge national networks that are really big, quite dense,” Glattfelder said. “From that you’re able to … unveil the important structure in this original big network. You then realize most of the network isn’t at all important.”

The most pared-down backbones exist in Anglo-Saxon countries, including the U.S., Australia, and the U.K. Paradoxically; these same countries are considered by economists to have the most widely-held stocks in the world, with ownership of companies tending to be spread out among many investors. But while each American company may link to many owners, Glattfelder and Battiston’s analysis found that the owners varied little from stock to stock, meaning that comparatively few hands are holding the reins of the entire market.

“If you would look at this locally, it’s always distributed,” Glattfelder said. “If you then look at who is at the end of these links, you find that it’s the same guys, [which] is not something you’d expect from the local view.”

Matthew Jackson, an economist from Stanford University in Calif. who studies social and economic networks, said that Glattfelder and Battiston’s approach could be used to answer more pointed questions about corporate control and how companies interact….

Based on their analysis, Glattfelder and Battiston identified the ten investment entities who are “big fish” in the most countries. The biggest fish was the Capital Group Companies, with major stakes in 36 of the 48 countries studied. In identifying these major players, the physicists accounted for secondary ownership — owning stock in companies who then owned stock in another company — in an attempt to quantify the potential control a given agent might have in a market….

Glattfelder added that the internationalism of these powerful companies makes it difficult to gauge their economic influence. “[With] new company structures which are so big and spanning the globe, it’s hard to see what they’re up to and what they’re doing,” he said. Large, sparse networks dominated by a few major companies could also be more vulnerable, he said. “In network speak, if those nodes fail, that has a big effect on the network.”

The results will be published in an upcoming issue of the journal Physical Review E.

Submitted by Richard Alford, a former economist at the New York Fed. Since them, he has worked in the financial industry as a trading floor economist and strategist on both the sell side and the buy side.

The fault, dear Brutus, is not in our model, but in ourselves–apologies to W Shakespeare

The economics profession is in disarray. Internecine warfare has broken out as proponents of various models/schools of thought are attacking and being attacked by each other. The battle between the different camps has been increasingly fought in the open e.g. The Economist and blogosphere. Despite the credentials of the combatants, there is a definite “My model can beat up your model’ air to the contretemps. The best outcome would be for policymakers to avail themselves of the models while losing the modelers.

Given the complexity of the financial markets and the economy, macro policymakers must operate on the basis of either implicit or explicit model(s). Furthermore, an explicit and transparent model subject to outside examination continuous testing is preferable to implicit poorly specified models that can serve as quasi-intellectual cover for policies based on solely belief systems.

However, macroeconomic models have been oversold again, the great moderation was fleeting. While economic models are necessary, both the recent experience and well-known limitations of the models themselves indicate that models alone will not be sufficiently robust to perform as well as many including investors and the general public have been led to expect. The underlying markets and the real economy are not stable. The models by definitions are incomplete. The responses of economic agents in times of stress and crisis may differ dramatically from the behavior reflected in parameters estimated on the basis of data collected in normal times. Goodhart’s law suggests that policy changes will induce changes in the statistical relationships on which the policy is based.

In defense of the current class of models (DSGE), some economists have spoken out saying that the models evolved as they did in response to questions raised by economists. But isn’t that the problem? Macro-economic models have become more formal and mathematically elegant, but all the while the modelers both ignored important drivers of economic performance, e.g. the workings of the financial markets, and failed to communicate the limitations of the models. The models evolved reflecting the economists‘desire for elegance and tractability, but with insufficient weight given to concerns such as financial stability or external balance.

Macro-economic policy is now being executed by the same people who devised the models. At times it has appeared that some of them sought policy making positions in order to be able to demonstrate the value of the model that they created or to which they made a contribution. These model builders were quick to take credit for the great moderation, but slow to see/ blind to the risk building up in the financial system and the imbalances. This type of behavior is to be expected. There is no reason to assume that the next set of policymaker/model builders will react any more positively to “warnings” that risks not central to the model pose real threats.

The role of model builders and policymakers should be split. Given the necessity of models in the policy formation process, it would be best, if the policymakers’ judgments about which model to use or when diverge from it are not clouded by previous involvement in the development of one or another of the models that might be employed.

Submitted by Richard Smith:

This is the Black Swan gospel according to Triana. Taleb endorses it in a characteristically incendiary and intemperate foreword. He does come out all guns blazing, and you just have to go with that. Or chuck a glass of water over him, if he’s in range, I suppose.

A quick recap for anyone who has spent the last two years in a coma: Taleb put together the beginnings of a rap sheet for modern mathematical finance theory in his book “The Black Swan”, and rapidly attained worldwide celebrity when his criticisms appeared to be borne out by the recent financial crisis. The main tenet of Black Swan theory, rather dry sounding, but with dramatic consequences, is that price changes are not normally distributed (in the way that, say, human weight or height are), but follow a power law (‘fat tails’). This implies much greater extremes of price movement than those predicted under the assumption of a normal distribution. The events that cause such price moves may be perfectly intelligible in hindsight, but are not necessarily predictable: like the existence of black swans.

The point about price distributions is actually quite an old one. Paul Levy made the same observation in the 1900s; Mandelbrot’s studies of cotton prices, in the 60s, reached similar conclusions. What gives it contemporary relevance is that the finance theory underlying current regulatory practice, risk management, fund management and derivatives pricing all overwhelmingly assume that price changes are normally distributed. And they all failed at once in the recent financial crisis, when price changes were indeed far more extreme than a normal distribution implies. It doesn’t look so good for orthodox financial theory just now.

So it is a good time for Triana to review modern finance theory’s rap sheet, add items, and add more detail to the existing charges. It goes like this.

Chapter 2: modern finance theory is a crock, peddled by charlatans at business schools who have managed to seal themselves off from the usual empirical tests of a theory.

I’ll admit I don’t see what logical point there is in attacking the character of business school teachers in this manner, whether it is a correct assessment or not. However the empirical criticism really does stack up. Consider GS CFO David Viniar’s notorious comments from August 2007 when the ABS meltdown got into full swing (Ch1, p12): “We were seeing things that were 25-standard-deviation moves, several days in a row”. To which the rejoinder from an empirically-minded observer simply has to be “No you weren’t, imbecile: those observations actually mean that your models are hopelessly wrong”. There are several reasons why one can so insouciantly cheek such an august figure. If we assume Viniar means daily observations and a normal distribution, then (if the numbers I am cribbing are correct: I haven’t gone back to the equations) one should expect to wait quite a lot longer than the age of the universe to see even a 16-standard deviation event, with a 25-standard deviation event taking many, many times longer than that. I suppose I should work out the exact number of years, just to see how big of a number it is: exercise for any readers with access to an arbitrary-precision mathematical engine.

You can find an old post by Yves on the subject that helped kick off some blogosphere chat.

Even if you assume (very charitably, I grimly suspect) that Viniar is not just parroting his VaR model outputs (more on that later), and is a bit more sophisticated about his distributions, he is still goofing, big time. And if Mandelbrot, and Taleb, his follower, and Triana, his follower, are right about the kind of distribution that underlies financial market price movements, there just ain’t sech a thing as a standard deviation of price movements, nor no correlation neither. Both standard deviation and correlation are defined in terms of variance. Since variance is infinite for stable distributions (other than the normal distribution), neither standard deviation nor correlation is defined for the distribution of market prices (a Levy skew alpha stable distribution, if you want the full geeky glory). On this theory, Viniar is talking about things that just don’t exist. Not encouraging behaviour in a CFO.

So here is the bleedin’ obvious: given its track record of ultra-wild underestimates of the frequency of sharp price moves, the assumption of normal distributions in stock price changes must be among the most lavishly disconfirmed scientific hypotheses of all time. No wonder, then, that Taleb and Triana are somewhat ratty with its various obstinately blithe proponents.

Chapter 3: Is a bit of a digression. According to Triana, the quants who work at banks work mostly on bits of IT dealing infrastructure, which is useful, and less often than you might think on mathematical models used in trading. The quants tend to be physicists and engineers rather than business school graduates. Models are used in a much more sceptical, provisional way on the trading floor than they are in academia.

I’ll take his word for it. Evidently, scepticism of models doesn’t extend to the risk management department. And, uh, actually it doesn’t look as if that trading floor scepticism managed to avert 2007’s monster trading screwups, either. Except, perhaps in the case of GS, who famously hedged a lot of MBS exposure starting late in 2006, to the great indignation of folk who don’t understand where fiduciary duties stop and start for broker-dealers.

Now we get into the meaty detail chapters. The non-normalness of price distributions means that a whole bunch of financial orthodoxies are dubious on theoretical grounds, and, post meltdown, there are some nasty data points to back up the theory.

First up is the Gaussian copula (Chapter 4). This is a modelling device which was used to calculate default correlations, for MBS and other bonds, and thus to structure, price, rate, and hedge CDOs. I think we already know how well that went overall– but the detail of how the behaviour of various tranches of CDOs diverged from predicted paths during the ’07 meltdown is instructive. Triana leaves open the question of whether the Gaussian copula was adopted out of blind faith in its efficacy, or precisely because it underrated extreme events, and thus gave an excuse for assigning a high rating, and getting a good price. Were the ratings agencies knaves or fools in this respect? I doubt we’ll find out any time soon. Anyhow, from the data and testimony Triana assembles, it looks as if the Gaussian copula is dead in the water as a structured finance tool. One wonders how Remics and re-Remics are to be priced and rated. Any NC readers want to buy one?

Chapter 5: Now we are into VaR, the risk management methodology that JP Morgan gave to the world back in the early 90’s, in the sadly mistaken belief that being able to generate a firm wide “risk number” daily would be a useful contribution to financial risk management. Back then you were reasonably smug about your bank if central management actually knew what the firm’s positions were at all (vide Barings, Sumitomo, then fast forward again to SocGen in – oh dear – 2007), so VaR was pretty cool. It was later endorsed by the Basel regulatory framework. Then the paint started to flake off.

The shortcomings of VaR have been a regular topic at NC. That pesky normal distribution assumption again. Note the reminder from practitioner Irene in the discussion thread though – the officially sanctioned VaR model may use a rolling 2 year price history rather than a normal distribution. This desperate kludge has its own perverse side effects: in times of increased volatility, the models all tell banks to stay on the sidelines at the same time. Once the volatile part of the price history rolls out, the models are all happy again. This is not a commonsense way to run banking businesses.

The other perversity of that approach to VaR is that it encourages herd behaviour in volatile markets, before the banks have even made it to the sidelines. In other words, since all the models in all the banks are essentially the same model of the same data, they all start screaming ‘fire’ at the same time, with predictable consequences at the exits. All this and more is well covered by Triana: particularly the way that a long period of low volatility before 2007 meant that VaR endorsed massive positions in assets that were suddenly big loss makers, when things went sour.

Banks were Gadarene enough without VaR. VaR makes it worse.

Oh, one thing that bugs me about VaR as used is this: if price histories tell you nothing about future prices (EMH), why is it that price volatility histories tell you something about future price volatility (VaR)? I’m just asking.

Anyhow, Triana makes the challenging points, with persuasive evidence: first, VaR is perfectly useless (it works until you need it, and at that point, it packs up: it is the chocolate teapot of risk management); second, like MTM, it is actively procyclical.

Chapter 6 is a brisk injunction to business schools (specifically, Sloane) to snap out of it and start teaching useful stuff.

In Chapter 7, we get to another polemic, against the Black-Scholes option pricing model. One can’t fault the reasoning or evidence, but somehow this is the weakest part of the meat. It is built around a recent paper by Taleb and Haug in which they review the historical record on options market making and option pricing theory and announce that a) the parts of Black-Scholes theory that are correct are not original, having been long anticipated by Thorp-Bachelier option pricing b) the parts that are original are not correct (normal distributions are again assumed, and the model simply can’t accommodate non-normal ones, unlike Thorp-Bachelier) c) no practitioners actually use Black-Scholes. The key item of evidence for (c) is the ‘volatility smile’ by which options traders systematically adjust option prices, so that the implied volatility (calculated according to Black Scholes methods) of options actually increases progressively for deeper and deeper out-of-the-money options. Under Black-Scholes pricing theory the implied volatility should be constant across all option strike prices. Traders don’t do it that way: they are compensating for the way the BS model fails to accommodate fat tails. QED. And by the way, Triana adds, there’s no such thing as implied volatility anyway, just supply and demand pushing prices around.

Well, OK to all that, so call implied volatility “demand premium” or something, and concede that Black-Scholes is a roundabout way to prices that can be reached more directly under other theories. So now what? Black-Scholes has become part of banking’s infrastructure. Do we strip out all the Black Scholes models and replace them with Thorp-Bachelier models? Will it make enough of a difference to options pricing or risk management to be worth it? Triana doesn’t try to determine the ROI. Instead (in the Finale) he asks whether Merton and Scholes should be stripped of their Economic prizes, and eventually concludes that instead the RiksBank prize should be given a silly name, so that people know it is a bit of a crock. It is an amazingly lightweight way to round off an otherwise enlightening discussion. It doesn’t come off like a joke fallen flat either: just cheesy.

While I’m carping, I’ll add a comment on the style. When I started reading the book, I kept stumbling over awesome quasi-English barbarisms, such as “qualification-inundated resumes”, “dangerously faulty mathematically charged steering”; also horrific neologisms like “analyticization”, “nonenthusiastically”, “impacting” (adj., I kid you not, and repeatedly), and “scientification aroma” (my favourite – I want some – either in a spray dispenser or roll-on form, not fussy). To my relief Triana (or his copy editor) gets more of a grip in later chapters and it’s not such a terrible read in the end. Doubtless the same relief is reflected in the generous verdicts of Taleb (“lucid”), Tett (“readable”) and Skypala (“a treat”). So, do not despair if you find yourself entangled in some pretty strange thickets of verbiage early in the piece: it does get better if you plough on.

Back to Chapters 8, 9 and 10 so that we can end on a note more favourable to the book (just skip the Finale).

Chapter 8 is a good one on the way models can be used as alibis or excuses by the lazy, reckless, or incompetent. Good reading for head traders, risk managers and regulators, I’d say; and buy-siders and pension fund trustees, come to that. Chapter 9 is a quick round up of how seductive the spurious certainty of mathematical models can be, largely illustrated by LTCM and by the confusion surrounding the meaning of the VIX.

In the end, the message of the book is that quantitative finance is a delusion, and that common sense is a better starting point for risk management. Accordingly Chapter 10 is a paean to Fat Tony, the street smart invention of Taleb in “The Black Swan”, and a call to reverse the quantification of finance. The negative leg of the case is argued persuasively. It is discomfiting to recognise just how little there was to quantitative finance.

On the positive side of Traiana’s recommendation: well, you are welcome to make your own mind up about the reserves of common sense to be found in the banking industry just now.

Nassim Nicholas Taleb gave a presentation in New York yesterday which hews closely to a recent piece of his, although his talk did include some additional interesting charts and anecdotes.

The article is worthwhile, and worth your attention, but let me highlight the two things I found most interesting.

First was his “fourth quadrant” construct. He sets up a 2 by 2 matrix. On one axis is phenomena that are normally distributed versus ones that have fat tails or unknown tails or unknown characteristics. On the other axis is the simple versus payoff from events. Simple payoffs are yes/no (dead or alive, for instance). “How much” payoffs are complex.

Models fail in the quadrant where you have fat or unknown tails and complex payoffs. A lot of phenomena fall there, such as epidemics, environmental problems, general risk management, insurance, natural catastrophes. And there are phenomena in that quadrant that have very complex payoffs, like payoffs from innovation, errors in analysis of deviation, derivative payoffs.

The other part that caught my attention was the estimation of fat tail risk.

As most readers know, all the fundamental models of finance theory use Gaussian (normal) distributions. Trading markets do not have normal probability distributions. Eurointelligence had a bit of fun with the particularly wild ride of last October:

October 2008 was certainly a spectacular month in the stock markets….

Those of us who studied modern finance theory, however, were truly astonished by the sheer improbability of the events occurring in the stock markets during that fateful month. One of the basic assumptions used in almost all our finance models is that returns are normally distributed. These models are widely used to price derivatives and other complex financial products. What do these models tell us about the probabilities of the events that occurred in October?

The following table gives an answer. We selected the six largest daily percentage changes in the Dow Jones Industrial Average during October, and asked the question of how frequent these changes occur assuming that, as is commonly done in finance models, these events are normally distributed. The results are truly astonishing. There were two daily changes of more than 10% during the month. With a standard deviation of daily changes of 1.032% (computed over the period 1971-2008) movements of such a magnitude can occur only once every 73 to 603 trillion billion years. Since our universe, according to most physicists, exists a mere 20 billion years we, finance theorists, would have had to wait for another trillion universes before one such change could be observed. Yet it happened twice during the same month. A truly miraculous event. The other four changes during the same month of October have a somewhat higher frequency, but surely we did not expect these to happen in our lifetimes.

Now supposedly quants have developed some fixes to various pricing and risk management models to allow for tail risk (can quant readers in the audience please tell us about them in comments, as in how they work and how successful do you believe them to be? I assume it’s GARCH, but confirmation/elaboration/additions welcome).

Taleb casts doubts on these fixes:

Let us start with the inverse problem of rare events and proceed with a simple, nonmathematical argument. In August 2007, The Wall Street Journal published a statement by one financial economist, expressing his surprise that financial markets experienced a string of events that “would happen once in 10,000 years”. A portrait of the gentleman accompanying the article revealed that he was considerably younger than 10,000 years; it is therefore fair to assume that he was not drawing his inference from his own empirical experience (and not from history at large), but from some theoretical model that produces the risk of rare events, or what he perceived to be rare events.

Alas, the rarer the event, the more theory you need (since we don’t observe it). So the rarer the event, the worse its inverse problem. And theories are fragile (just think of Doctor Bernanke).

The tragedy is as follows. Suppose that you are deriving probabilities of future occurrences from the data, assuming (generously) that the past is representative of the future. Now, say that you estimate that an event happens every 1,000 days. You will need a lot more data than 1,000 days to ascertain its frequency, say 3,000 days. Now, what if the event happens once every 5,000 days? The estimation of this probability requires some larger number, 15,000 or more. The smaller the probability, the more observations you need, and the greater the estimation error for a set number of observations. Therefore, to estimate a rare event you need a sample that is larger and larger in inverse proportion to the occurrence of the event.

If small probability events carry large impacts, and (at the same time) these small probability events are more difficult to compute from past data itself, then: our empirical knowledge about the potential contribution—or role—of rare events (probability × consequence) is inversely proportional to their impact. This is why we should worry in the fourth quadrant!

The issue is that when you do find one of these outliers, and you are working in a region where those extreme events are big enough to worry about, like days when the markets are really roiled, you wind up having so few of the super extreme events that one can wind up distorting how you estimate the significance of tails (Taleb goes through this in geekier form in his technical appendix).

Taleb gathered every kind of market and macroeconomic data item he could locate (stock prices in various markets, commodities, interest rates, currencies, inflation, etc) where he could have a reasonably long time series. For the ones where he had 40 years. single events would take up most of the estimate of the tail risk. For instance, the 1987 crash is (from memory) 78% of the estimate of the tail risk for the S&P 500. For silver, it was even worse, nearly 90% (click to enlarge):

The text of the article is here.

Taleb was relaxed and funny at points during his talk, and seemed to enjoy chatting with the audience afterwards. I suspect his prickly streak comes to the fore when dealing with types he calls “charlatans”, particularly when they know enough to know better.

We have been saying for some time that the policy premise of the Fed and Treasury has been that the financial crisis is that it is a liquidity crisis, not a solvency crisis. If you are of that school, the fallen prices of various assets is due to a combination of scarcity of funding plus irrational panic. Find ways to provide liquidity and give investors that magic elixir, confidence, and voila, crisis over.

Having watched the credit markets closely before the implosion, we’ll agree there was plenty of irrationality. But it was in the gross underpricing of risk. The snapback to current pricing to us thus seems a return to rationality plus new fundamentals based on borrowers who never should have been lent money in the first place defaulting on such a scale as to damage overall economic activity. And that means, as plenty of Serious Economists (Krugman, Buiter, Stiglitz, to name a few) have warned, the Geithner cash for trash program is a huge misallocation of taxpayer dollars. Even granting that something must be done about the banking system, this is a covert and wasteful way to go about it.

That thesis has been validated by Harvard’s Joshua Coval and Erik Stafford and Princeton’s Jakub Jurek in a paper “The Pricing of Investment Grade Credit Risk during the Financial Crisis” (hat tip Bill Black). It looks at the repricing of investment grade credits, which is easier to analyze than structured credits (you have other claims, namely stocks, on the same entities, which allows for a relative analysis).

The paper starts by mentioning the public private partnership and its belief that market prices are distressed:

The government’’s view is that a disappearance of liquidity has caused credit market prices to no longer refl‡ect fundamentals:2

An initial fundamental shock associated with the bursting of the housing bubble and deteriorating economic conditions generated losses for leveraged investors including banks … The resulting need to reduce risk triggered a wide-scale deleveraging in these markets and led to …fire sales … [The Public-Private Investment Program] should facilitate price discovery and should help, over time, to reduce the excessive liquidity discounts embedded in current legacy asset prices…..

Yves here. Did you catch that? The price collapse is due mainly to “excessive liquidity discounts”. Please. Some of the exotic flavors of now junk paper (as in certain CDOs) were called “trades” because they were designed NOT to be resold. So the concept of a liquidity discount applying to paper anticipated to be illiquid from the get-go is quite a stretch.

As an aside, we have to mention the intellectual inconsistency. The logic of the PPIP is that current market prices are wrong. Yet the authorities failed to question prices (or more important, overall leverage) in the frothy days. Funny how that works. Now that prices are low, that can’t be right, since it’s way too inconvenient, so we are going to create a rigged market and claim it’s necessary to produce “better” prices. Back to the article:

Our results suggest changes in fundamentals, as re‡ected in the equity market, account for a large portion of the repricing of credit that has occurred. In particular, the dramatic increase in the price of low cash‡ow states can account for most, if not all, of the rise in credit spreads for cash bonds. The spreads on credit default swaps, which currently trade at a large and negative basis relative to the underlying bonds, appear too low relative to risk-matched alternatives in the equity
market.

We also …nd that the repricing of the investment grade structured credit securities suggests a correction of an ex ante failure of investors to appropriately charge for systematic risk. Prior to the crisis, Coval, Jurek, and Sta¤ord (2009b) argued that investors did not appreciate the systematic risk exposures of these securities and provided evidence that credit protection on the senior tranches of the investment grade CDX was underpriced (i.e. spreads were too low), while protection on the junior most tranche was overpriced.

Did you catch that little doozy, credit default swaps now look underpriced? Lordie. And CDS are still being written, some by firms that have Federal backstops.

I’d welcome the input of any hard core quants reading the paper, but I also note the authors use a modified CAPM approach. That I presume would still use Gaussian distributions, Although most quants resist using Levy type distributions (which are brutally hard to model, the Options Clearing Corp. since 1990 has used Levy distributions for setting margin requirements, which says it is not as impossible to implement as the crowd adhering to the conventional techniques asserts). Thus I wonder if even this approach understates risk, for if so, that would argue for even lower prices.

Full disclosure: I have a great deal of respect for both Tim Duy and the hedge fund manager Scott who is also quoted in this post. As you will see, Duy wrote an interesting post addressing a question posed by Brad DeLong, in essence “Since we are in the midst of the worst financial crisis since the Great Depression, why isn’t the economy in worse shape?” Although the answer is more complicated and nuanced, a big piece of it is that we haven’t felt the impact of the crisis because our friendly foreign funding sources have stepped up to provide liquidity.

As readers no doubt know, I’m pretty bearish, but if Duy’s take is correct (and perhaps more important, continues to be what is driving the equation (although I harbor doubts that this forbearance can be sustained), perhaps the downside will not be as bad as it ought to be. I forwarded Duy’s post to Scott, who is even more bearish than I am, and I thought readers would be interested in this take.

Admittedly, the two analyses address different questions: Duy focuses more on why conditions are as they are now, while Scott is more forward-looking.

First from Tim Duy, via Mark Thoma (charts omitted):

I think economic activity has surpassed most peoples’ expectations….

1. The nature of the expansion defines the nature of the following contraction. The post-tech bubble expansion was anemic by most measures, and never gained much traction until the housing bubble arose….The tepid upside suggests a tepid downside….

2. The impact of the consumer slowdown is partially offshored….This shifts job destruction to an overseas producer. In fact, as spencer at Anger Bear shows, the recent improvement in the real trade balance has less to do with rising exports, which continue to follow recent trends, than the sharp slowdown in real import growth….

3. Perhaps most importantly, however, is the massive liquidity injections from the rest of the world, or what Brad Setser calls “the quiet bailout.” In the first half of this, global central banks accumulated $283.5 billion of Treasuries and Agencies, something around $1,000 per capita. This is real money – I outlined the likely implications in January. Foreign CBs are happily financing the first US stimulus package; will they be happy to finance a second? Do they have a choice? Their accumulation of Agency debt is also keeping the US mortgage market afloat. Do not underestimate the impact of these foreign capital inflows. If the rest of the world treated the US like we treated emerging Asia in 1997-1998, the US economy would experience a slowdown commensurate with the magnitude of the financial market crisis. The accumulation of US assets is also forcing an expansion of foreign CB’s balance sheets, creating global monetary stimulus that allows the rest of the world to decouple from the US economy, supporting continued US export growth (see point 2 above).

Ideally, the slowdown remains moderate, allowing for a rebalancing as we expand export and import competing industries domestically, narrowing the current account deficit and eliminating the necessity of foreign official financing. This means accepting a period of time with suboptimal domestic demand growth and structural adjustment. Excessive fiscal stimulus risks testing the willingness of foreign CBs to continue to accumulate US assets. Moreover, I believe that excessive stimulus will eventually foster a more damaging inflationary dynamic, but such a process would likely build over a long period of time – the seeds for the 1970s were planted in the 1960s.

In short: External dynamics play a significant role in explaining the relatively mild US downturn. As long as foreign CBs are willing to accumulate US debt, the US government is willing to issue debt, the Federal Reserve is willing to accommodate the debt with low interest rates, we will avoid the most dire deflationary predictions.

Now to hedge fund manager Scott’s reading:

[A colleague] asked me this morning what I thought of something I’d sent him, in which the writer noted that financials aside, the rest of the S&P earnings so far have not been so bad. My response was to say that, first, the timeline for economic events to play out is remarkably languid, always taking longer than one expects. And given the fact that one views it unfolding in a sense through a series of discreet datapoints, some of which are manipulated, and all of which are subject to “noise” and some serendipity, it is both really hard and really important to focus on the underlying trends in order to maintain a clear view of the larger picture.

Along those lines, for example, one might note that MSFT, GOOG, CSCO, and ORCL–all big, important tech companies with something approaching monopoly-like market positions, but all most certainly exposed/leveraged to the larger economy, have disappointed or warned in the recent past. There’s a clear message there. The other big element to consider with regard to the quarter just past is the element that the rebate checks played. Note that even with them in play, consumer spending was pretty muted. In their absence, I expect the second half of the year to be pretty challenging.

I used to think that maybe employment could hold up, based on the thought that since it never really zoomed in the recovery, it might not really decline now. I no longer believe that, just think that it’s taking some time to play out…..

Tim gingerly tiptoes around the issue my friends and I always come back to at our “Austrian” lunches. And this is the thought that we’ve issued more paper than our economy can ever pay back–given the size of the economy, it just does not compute. How long foreign central banks will continue to play the game is a difficult question to answer, and the attempts at answering are pretty much pure speculation anyway. But again, trying to view the situation from 30,000 feet, the trend of moving away from the dollar is certainly apparent. Bulls, and what me worry types can certainly find enough datapoints to continue in a fool’s paradise, but at some point this becomes one of Herb Stein’s what can’t go on forever, stops, moments, and either interest rates go through the roof, or the dollar really collapses, or both.

There is very little to feel optimistic about right now, if you think carefully about the issues we face, as far as I can tell. The
developments of the last week were really sickeningly disheartening to me, frankly. In terms of your banana republicanism, what could be more so than Paulson basically playing investment banker, forcing Syron into the arms not simply of Morgan Stanley, but also of Goldman, to talk about raising capital. Nice rainmaking there! And that followed by Cox essentially engineering a short squeeze in all the financials? It really is heartbreaking, frankly, and not just in light of what it did to my pnl on Wednesday and Thursday. So all those stocks are up 35%, but the underlying economic situation hasn’t changed a bit, except to the extent that we have more clues about the cluelessness of the guys in charge. Yikes

And he provided this comment earlier in the day on a post that featured the quote, “Classic Buffettology advises us to get greedy when others are fearful”:

The issue with Buffett/Rothschild’s buy when people are fearful admonition and wondering why it’s not applicable here is that nobody seems even slightly fearful. Just as the January effect moved into December as people became aware of and started to anticipate it, and as the Dogs of the Dow lost potency when it too become well-publicized, old saws do the same. And everybody’s looking for that capitulatory moment, so they can catch the exact bottom, as a result of which we’re nowhere near to reaching it. A VIX above 30 being one of those magic indicators, the Vix hit 30 for perhaps 30 seconds (I exaggerate a bit) yesterday before every buy button on the Street started getting pushed insistently like a rat learning how to release cocaine.

Reader Michael called to my attention a wide-ranging interview with Nassim Nicholas Taleb, author of the Black Swan and professional iconoclast, in the Times of London. The article is colorful, wide-ranging, and a bit long, so I’ve excerpted some of the most provocative bits. Needless to say, I am particularly taken by his dim view of academic economics as practiced in the US, which tends to place a premium on abstraction and models:

A noisy cafe in Newport Beach, California. Nassim Nicholas Taleb is eating three successive salads, carefully picking out anything with a high carbohydrate content.

He is telling me how to live. “The only way you can say ‘F*** you’ to fate is by saying it’s not going to affect how I live. So if somebody puts you to death, make sure you shave.”…

The world is random, intrinsically unknowable. “You will never,” he says, “be able to control randomness.”

To explain: black swans were discovered in Australia. Before that, any reasonable person could assume the all-swans-are-white theory was unassailable. But the sight of just one black swan detonated that theory. Every theory we have about the human world and about the future is vulnerable to the black swan, the unexpected event. We sail in fragile vessels across a raging sea of uncertainty. “The world we live in is vastly different from the world we think we live in.”

Last May, Taleb published The Black Swan: The Impact of the Highly Improbable. It said, among many other things, that most economists, and almost all bankers, are subhuman and very, very dangerous. They live in a fantasy world in which the future can be controlled by sophisticated mathematical models and elaborate risk-management systems. Bankers and economists scorned and raged at Taleb. He didn’t understand, they said. A few months later, the full global implications of the sub-prime-driven credit crunch became clear. The world banking system still teeters on the edge of meltdown. Taleb had been vindicated. “It was my greatest vindication. But to me that wasn’t a black swan; it was a white swan. I knew it would happen and I said so. It was a black swan to Ben Bernanke [the chairman of the Federal Reserve]. I wouldn’t use him to drive my car. These guys are dangerous. They’re not qualified in their own field.”

In December he lectured bankers at Société Générale, France’s second biggest bank. He told them they were sitting on a mountain of risks – a menagerie of black swans. They didn’t believe him. Six weeks later the rogue trader and black swan Jérôme Kerviel landed them with $7.2 billion of losses.

As a result, Taleb is now the hottest thinker in the world. He has a $4m advance on his next book. He gives about 30 presentations a year to bankers, economists, traders, even to Nasa, the US Fire Administration and the Department of Homeland Security. But he doesn’t tell them what to do – he doesn’t know. He just tells them how the world is. “I’m not a guru. I’m just describing a problem and saying, ‘You deal with it.’”…

He has rules. In California he hires bikes, not cars. He doesn’t usually carry his BlackBerry because he hates distraction and he really hates phone charges. But he does carry an Apple laptop everywhere and constantly uses it to illustrate complex points and seek out references. He says he answers every e-mail. He is sent thousands. He reads for 60 hours a week, but almost never a newspaper, and he never watches television.

“If something is going on, I hear about it. I like to talk to people, I socialise. Television is a waste of time. Human contact is what matters.”…

Startlingly, this great sceptic, this non-guru who believes in nothing, is still a practising Christian. He regards with some contempt the militant atheism movement led by Richard Dawkins.

“Scientists don’t know what they are talking about when they talk about religion. Religion has nothing to do with belief, and I don’t believe it has any negative impact on people’s lives outside of intolerance. Why do I go to church? It’s like asking, why did you marry that woman? You make up reasons, but it’s probably just smell. I love the smell of candles. It’s an aesthetic thing.”

Take away religion, he says, and people start believing in nationalism, which has killed far more people. Religion is also a good way of handling uncertainty. It lowers blood pressure. He’s convinced that religious people take fewer financial risks…

But, crucially, he also learnt from a very early age that grown-ups have a dodgy grasp of probability…For the non-mathematician, probability is an indecipherably complex field. But Taleb makes it easy by proving all the mathematics wrong. Let me introduce you to Brooklyn-born Fat Tony and academically inclined Dr John, two of Taleb’s creations. You toss a coin 40 times and it comes up heads every time. What is the chance of it coming up heads the 41st time? Dr John gives the answer drummed into the heads of every statistic student: 50/50. Fat Tony shakes his head and says the chances are no more than 1%. “You are either full of crap,” he says, “or a pure sucker to buy that 50% business. The coin gotta be loaded.”

The chances of a coin coming up heads 41 times are so small as to be effectively impossible in this universe. It is far, far more likely that somebody is cheating. Fat Tony wins. Dr John is the sucker. And the one thing that drives Taleb more than anything else is the determination not to be a sucker. Dr John is the economist or banker who thinks he can manage risk through mathematics. Fat Tony relies only on what happens in the real world.

In 1985, Taleb discovered how he could play Fat Tony in the markets. France, Germany, Japan, Britain and America signed an agreement to push down the value of the dollar. Taleb was working as an options trader at a French bank. He held options that had cost him almost nothing and that bet on the dollar’s decline. Suddenly they were worth a fortune. He became obsessed with buying “out of the money” options. He had realised that when markets rise they tend to rise by small amounts, but when they fall – usually hit by a black swan – they fall a long way.

The big payoff came on October 19, 1987 – Black Monday. It was the biggest market drop in modern history. “That had vastly more influence on my thought than any other event in history.”

It was a huge black swan – nobody had expected it, not even Taleb. But the point was, he was ready. He was sitting on a pile of out-of-the-money eurodollar options. So, while others were considering suicide, Taleb was sitting on profits of $35m to $40m. He had what he calls his “f***-off money”, money that would allow him to walk away from any job and support him in his long-term desire to be a writer and philosopher.

He stayed on Wall Street until he got bored and moved to Chicago to become a trader in the pit, the open-outcry market run by the world’s most sceptical people, all Fat Tonys. This he understood…..

In the midst of this came his purest vindication prior to sub-prime. Long-Term Capital Management was a hedge fund set up in 1994 by, among others, Myron Scholes and Robert C Merton, joint winners of the 1997 Nobel prize in economics. It had the grandest of all possible credentials and used the most sophisticated academic theories of portfolio management. It went bust in 1998 and, because it had positions worth $1.25 trillion outstanding, it almost took the financial system down with it. Modern portfolio theory had not accounted for the black swan, the Russian financial crisis of that year. Taleb regards the Nobel prize in economics as a disgrace, a laughable endorsement of the worst kind of Dr John economics. Fat Tony should get the Nobel, but he’s too smart. “People say to me, ‘If economists are so incompetent, why do people listen to them?’ I say, ‘They don’t listen, they’re just teaching birds how to fly.’ ”….

And what he knows does not sound good. The sub-prime crisis is not over and could get worse. Even if the US economy survives this one, it will remain a mountain of risk and delusion. “America is the greatest financial risk you can think of.”

Its primary problem is that both banks and government are staffed by academic economists running their deluded models. Britain and Europe have better prospects because our economists tend to be more pragmatic, adapting to conditions rather than following models. But still we are dependent on American folly.

The central point is that we have created a world we don’t understand. There’s a place he calls Mediocristan. This was where early humans lived. Most events happened within a narrow range of probabilities – within the bell-curve distribution still taught to statistics students. But we don’t live there any more. We live in Extremistan, where black swans proliferate, winners tend to take all and the rest get nothing – there’s Bill Gates, Steve Jobs and a lot of software writers living in a garage, there’s Domingo and a thousand opera singers working in Starbucks. Our systems are complex but over-efficient. They have no redundancy, so a black swan strikes everybody at once. The banking system is the worst of all.

“Complex systems don’t allow for slack and everybody protects that system. The banking system doesn’t have that slack. In a normal ecology, banks go bankrupt every day. But in a complex system there is a tendency to cluster around powerful units. Every bank becomes the same bank so they can all go bust together.”

He points out, chillingly, that banks make money from two sources. They take interest on our current accounts and charge us for services. This is easy, safe money. But they also take risks, big risks, with the whole panoply of loans, mortgages, derivatives and any other weird scam they can dream up. “Banks have never made a penny out of this, not a penny. They do well for a while and then lose it all in a big crash.”

On top of that, Taleb has shown that increased economic concentration has raised our vulnerability to natural disasters. The Kobe earthquake of 1995 cost a lot more than the Tokyo earthquake of 1923. And there are countless other ways in which we have built a world ruled by black swans – some good but mostly bad. So what do we do as individuals and the world? In the case of the world, Taleb doesn’t know. He doesn’t make predictions, he insults people paid to do so by telling them to get another job. All forecasts about the oil price, for example, are always wrong, though people keep doing it. But he knows how the world will end.

“Governments and policy makers don’t understand the world in which we live, so if somebody is going to destroy the world, it is the Bank of England saving Northern Rock. The biggest danger to human society comes from civil servants in an environment like this. In their attempt to control the ecology, they don’t understand that the link between action and consequences can be more vicious. Civil servants say they need to make forecasts, but it’s totally irresponsible to make people rely on you without telling them you’re incompetent.”

Bear Stearns – the US Northern Rock – was another vindication for Taleb. He’s always said that whatever deal you do, you always end up dealing with J P Morgan. It was JPM that picked up Bear at a bargain-basement price. Banks should be more like New York restaurants. They come and go but the restaurant business as a whole survives and thrives and the food gets better. Banks fail but bankers still get millions in bonuses for applying their useless models. Restaurants tinker, they work by trial and error and watch real results in the real world. Taleb believes in tinkering – it was to be the title of his next book. Trial and error will save us from ourselves because they capture benign black swans. Look at the three big inventions of our time: lasers, computers and the internet. They were all produced by tinkering and none of them ended up doing what their inventors intended them to do. All were black swans. The big hope for the world is that, as we tinker, we have a capacity for choosing the best outcomes.

“We have the ability to identify our mistakes eventually better than average; that’s what saves us.” We choose the iPod over the Walkman. Medicine improved exponentially when the tinkering barber surgeons took over from the high theorists. They just went with what worked, irrespective of why it worked. Our sense of the good tinker is not infallible, but it might be just enough to turn away from the apocalypse that now threatens Extremistan.

He also wants to see diplomats dying of cirrhosis of the liver. It means they’re talking and drinking and not going to war. Parties are among the great good things in Taleb’s world.

And you and me? Well, the good investment strategy is to put 90% of your money in the safest possible government securities and the remaining 10% in a large number of high-risk ventures. This insulates you from bad black swans and exposes you to the possibility of good ones. Your smallest investment could go “convex” – explode – and make you rich. High-tech companies are the best. The downside risk is low if you get in at the start and the upside very high. Banks are the worst – all the risk is downside. Don’t be tempted to play the stock market – “If people knew the risks they’d never invest.”

There’s much more to Taleb’s view of the world than that. He is reluctant to talk about matters of human nature, ethics or any of the traditional concerns of philosophy because he says he hasn’t read enough. But, when pressed, he comes alive.

“You have to worry about things you can do something about. I worry about people not being there and I want to make them aware.” We should be mistrustful of knowledge. It is bad for us. Give a bookie 10 pieces of information about a race and he’ll pick his horses. Give him 50 and his picks will be no better, but he will, fatally, be more confident.

We should be ecologically conservative – global warming may or may not be happening but why pollute the planet? – and probablistically conservative. The latter, however, has its limits. Nobody, not even Taleb, can live the sceptical life all the time – “It’s an art, it’s hard work.” So he doesn’t worry about crossing the road and doesn’t lock his front door – “I can’t start getting paranoid about that stuff.” His wife locks it, however.

He believes in aristocratic – though not, he insists, elitist – values: elegance of manner and mind, grace under pressure, which is why you must shave before being executed. He believes in the Mediterranean way of talking and listening. One piece of advice he gives everybody is: go to lots of parties and listen, you might learn something by exposing yourself to black swans.

I ask him what he thinks are the primary human virtues, and eventually he comes up with magnanimity – punish your enemies but don’t bear grudges; compassion – fairness always trumps efficiency; courage – very few people have this; and tenacity – tinker until it works for you.

“Let’s be human the way we are human. Homo sum – I am a man. Don’t accept any Olympian view of man and you will do better in society.”…

Taleb’s top life tips

1 Scepticism is effortful and costly. It is better to be sceptical about matters of large consequences, and be imperfect, foolish and human in the small and the aesthetic.

2 Go to parties. You can’t even start to know what you may find on the envelope of serendipity. If you suffer from agoraphobia, send colleagues.

3 It’s not a good idea to take a forecast from someone wearing a tie. If possible, tease people who take themselves and their knowledge too seriously.

4 Wear your best for your execution and stand dignified. Your last recourse against randomness is how you act — if you can’t control outcomes, you can control the elegance of your behaviour. You will always have the last word.

5 Don’t disturb complicated systems that have been around for a very long time. We don’t understand their logic. Don’t pollute the planet. Leave it the way we found it, regardless of scientific ‘evidence’.

6 Learn to fail with pride — and do so fast and cleanly. Maximise trial and error — by mastering the error part.

7 Avoid losers. If you hear someone use the words ‘impossible’, ‘never’, ‘too difficult’ too often, drop him or her from your social network. Never take ‘no’ for an answer (conversely, take most ‘yeses’ as ‘most probably’).

8 Don’t read newspapers for the news (just for the gossip and, of course, profiles of authors). The best filter to know if the news matters is if you hear it in cafes, restaurants… or (again) parties.

9 Hard work will get you a professorship or a BMW. You need both work and luck for a Booker, a Nobel or a private jet.

10 Answer e-mails from junior people before more senior ones. Junior people have further to go and tend to remember who slighted them.