The Anatomy of the Cyprus’ Bubble Cycle

The following article from the Reuters has a concise chronicle of the boom bust cycle which today has been plaguing Cyprus via a banking crisis and which I dissect.

(all bold highlights mine, occasional side comments of mine in italics)

1. The Pre-EU setting.

Before joining the euro, the Central Bank of Cyprus only allowed banks to use up to 30 percent of their foreign deposits to support local lending, a measure designed to prevent sizeable deposits from Greeks and Russians fuelling a bubble.

2. The Moral Hazard from EU’s economic convergence policies

When Cyprus joined the single European currency, Greek and other euro area deposits were reclassified as domestic, leading to billions more local lending, Pambos Papageorgiou, a member of Cyprus's parliament and a former central bank board member said.

"In terms of regulation we were not prepared for such a credit bubble," he told Reuters.

Banks' loan books expanded almost 32 percent in 2008 as its newly gained euro zone status made Cyprus a more attractive destination for banking and business generally, but Cypriot banks maintained the unusual position of funding almost all their lending from deposits.

3. How bubble policies reshaped the public’s behavior.

"The banks were considered super conservative," said Alexander Apostolides an economic historian at Cyprus' European University, a private university on the outskirts of Nicosia.

When Lehman Brothers collapsed in the summer of 2008, most of the world's banks suffered in the fallout, but not Cyprus's.

"Everyone here was sitting pretty," said Fiona Mullen, a Nicosia-based economist, reflecting on the fact Cypriot banks did not depend on capital markets for funding and did not invest in complex financial products that felled other institutions.

Note of the "this time is different" mentality and the attitudes of "invincibility".

4. Overconfidence and Mania

Marios Mavrides, a finance lecturer and government politician, says his warnings about the detrimental impact on the economy of so much extra lending fell on deaf ears.

"I was talking about the (property) bubble but nobody wanted to listen, because everyone was making money," he said. (sounds strikingly familiar today—Prudent Investor)

The fact that the main Cyprus property taxes are payable on sale made people hold onto property, further fuelling prices, Papageorgiou added…

Michael Olympios, chairman of the Cyprus Investor Association that represents 27,000 individual stock market investors, said he too criticized the central bank for "lax" regulation that facilitated excessive risk taking.

Ex-post, people always look for someone to pass the blame on. They forget the responsibility comes from within.

The Cyprus General Index from Tradingeconomics.com

Notice: The losses from the bust had been more brutal than the gains from the boom

5. The yield chasing dynamic fueled by monetary-credit expansion

A depositor would have earned 31,000 euros on a 100,000 euros deposit held for the last five year in Cyprus, compared to the 15,000 to 18,000 euros the same deposit would have made in Italy and Spain, and the 8,000 interest it would have earned in Germany, according to figures from UniCredit.

Bulging deposit books not only fuelled lending expansion at home, it also drove Cypriot banks overseas. Greece, where many Cypriots claim heritage, was the destination of choice for the island's two biggest lenders, Cyprus Popular Bank -- formerly called Laiki -- and Bank of Cyprus.

6. The Knowledge problem: Regulators didn’t see the crisis coming. Also the transmission mechanism: From the periphery (Greek crisis) to the core (Cyprus crisis)

The extent of this exposure was laid bare in the European Banking Authority's 2011 "stress tests", which were published that July, as the European Union and International Monetary Fund (IMF) were battling to come up with a fresh rescue deal to save Greece. (reveals how bank stress tests can’t be relied on—Prudent Investor)

The EBA figures showed 30 percent (11 billion euros) of Bank of Cyprus' total loan book was wrapped up in Greece by December 2010, as was 43 percent (or 19 billion euros) of Laiki's, which was then known as Marfin Popular.

More striking was the bank's exposure to Greek debt.

At the time, Bank of Cyprus's 2.4 billion euros of Greek debt was enough to wipe out 75 percent of the bank's total capital, while Laiki's 3.4 billion euros exposure outstripped its 3.2 billion euros of total capital.

The close ties between Greece and Cyprus meant the Cypriot banks did not listen to warnings about this exposure…

Artificial booms are often interpreted as validating the policies of the incumbent political authorities. It's only during fait accompli where people recognize of the failures of politics. This is an example of time inconsistency dilemma

Yet the blame will always be pinned on the victims (private sector, e.g. depositors, the speculators) rather than the promoters of the bubble.

 

7. More regulatory failure.

Whatever the motive, the Greek exposure defied country risk standards typically applied by central banks; a clause in Cyprus' EU/IMF December memorandum of understanding explicitly requires the banks to have more diversified portfolios of higher credit quality.

"That (the way the exposures were allowed to build) was a problem of supervision," said Papageorgiou, who was a member of the six-man board of directors of the central bank at the time.

The board, which met less than once a month, never knew how much Greek debt the banks were holding, both Papageorgiou and another person with direct knowledge of the situation told Reuters.

Note that imbalances accrued swiftly and where hardly anyone saw the imminence of today's crisis.  What used to be "Conservative" banks suddenly transformed into aggressive banks.

Yet another interesting point is that the events in Cyprus proves my thesis that crisis are essentially "unique". There is no definitive line in the sand for credit events. Cyprus had its own distinctive thumbprint or identity, particularly her "unusual position" of reliance on deposits, compared to their peers.

 

Wonderful learning experience

US Economic Growth Turns Negative Amidst US Stock Market and Property Boom

Have stock markets been about earnings or economic growth? 

Yesterday the US posted negative statistical economic growth

This from Bloomberg,

The economy in the U.S. unexpectedly came to a standstill in the fourth quarter as the biggest plunge in defense spending in 40 years swamped gains for consumers and businesses.

Gross domestic product dropped at a 0.1 percent annual rate, weaker than any economist forecast in a Bloomberg survey and the worst performance since the second quarter of 2009, when the world’s largest economy was still in the recession, Commerce Department figures showed today in Washington. A decline in government outlays and a smaller gain in stockpiles subtracted a combined 2.6 percentage points from growth.

Well a decline in government spending while statistically negative should be good news for the real economy. That’s because money not spent by government can be saved or productively used by the private sector.

But given the insatiable spending habits of the US government this is likely to be temporary.

Yesterday’s technical decline shows how anemic US statistical growth has been (chart from tradingeconomics)

This is the annualized economic growth rate for the US. (tradingeconomics.com)

Now for US companies beating earnings estimates...

The above chart from Bespoke Invest

Consensus expectations of strong earnings has been on a declining trend since 2006, this seems detached from the recent blitz in the US stock market.

Yet I previously explained how central bank actions can artificially boost earnings and how credit booms can mask statistical growth

The US is experiencing a resurgent real estate sector despite the sluggish economy, courtesy of the Ben Benanke’s QE infinity. (charts from Northern Trust). Money creation has to flow somewhere, and they seem channeled to the asset markets.

Rising property prices, which should spillover to rental prices, will likely increase statistical inflation. This puts to risks the current boom which could prompt the FED, whom in rabid fear of deflation, will likely resort to more inflationism in order to continue to suppress interest rates. And monetary expansion could feed through to the housing and housing bubble and or even consumer price inflation. The US asset economy has become greatly dependent on the Fed's doping policies. This means the US Federal Reserve has been trapped.

Yet, aside from the property sector and the spreading asset boom (via hedge funds, junk bonds, CDOs, etc…), stock market benchmarked by the S&P 500 has been attempting to carve new record highs (bigcharts.com)

Markets (and even the real economy) have essentially been distorted by monetary policies such that they don’t operate on conventional wisdom. Even the economic profession have been at a loss with their dysfunctional models.

Quote of the Day: Government Forecast is No Different than a Medieval Fortuneteller

The problem is that people have been deluded for so long into believing that economics is an actual science… and so it must be true. Well, for a time, so was bloodletting. Or the ‘ethnic sciences’.

We know all of these things are nonsense today. But for some reason, people still haven’t figured out that an economist with a forecast is no different than a medieval fortuneteller.

This is from Simon Black of the Sovereign Man debunking the popular romanticized fiction called government economic forecasting.

Graphic of the Day: MIT Academes Govern World’s Money Policies

Could revolving door relationships between central banks and the highly protected banking industry signify manifestations of more than just the Goldman Sachs connection?

Central bank policies appear to have another a common denominator; they seem to be undergirded by academic pedantry from the stealth sanctums of the Massachusetts Institute of Technology (MIT). 

From the Wall Street Journal (bold mine) [hat tip zero hedge]

Of late, these secret talks have focused on global economic troubles and the aggressive measures by central banks to manage their national economies. Since 2007, central banks have flooded the world financial system with more than $11 trillion. Faced with weak recoveries and Europe's churning economic problems, the effort has accelerated. The biggest central banks plan to pump billions more into government bonds, mortgages and business loans.

Their monetary strategy isn't found in standard textbooks. The central bankers are, in effect, conducting a high-stakes experiment, drawing in part on academic work by some of the men who studied and taught at the Massachusetts Institute of Technology in the 1970s and 1980s.

How the world’s tightly knit central bank cabal operates, again from the same article:

Central bankers themselves are among the most isolated people in government. If they confer too closely with private bankers, they risk unsettling markets or giving traders an unfair advantage. And to maintain their independence, they try to keep politicians at a distance.

Since the financial crisis erupted in late 2007, they have relied on each other for counsel. Together, they helped arrest the downward spiral of the world economy, pushing down interest rates to historic lows while pumping trillions of dollars, euros, pounds and yen into ailing banks and markets.

Three of the world's most powerful central bankers launched their careers in a building known as "E52," home to the MIT economics department. Fed Chairman Ben Bernanke and ECB President Mario Draghi earned their Ph.D.s there in the late 1970s. Bank of England Governor Mervyn King taught briefly there in the 1980s, sharing an office with Mr. Bernanke.

Many economists emerged from MIT with a belief that government could help to smooth out economic downturns. Central banks play a particularly important role in this view, not only by setting interest rates but also by influencing public expectations through carefully worded statements.

While at MIT, the central bankers dreamed up mathematical models and discussed their ideas in seminar rooms and at cheap food joints in a rundown Boston-area neighborhood on the Charles River.

This gives light to the cartel-like operations of world’s central banks, who operate in consonance or in apparent collaboration with each other. 

Experimental policies, which encompasses excessive reliance on mathematical models, centralization and presumption of knowledge, are a fatal mix to the real world. 

As Nassim Taleb wrote in The Bed of Procrustes: Philosophical and Practical Aphorisms; p.72

Academics are only useful when they try to be useless (say, as in mathematics and philosophy) and dangerous when they try to be useful.

How Government Policies Contributed to JP Morgan’s Blunder

Author and derivatives manager Satyajit Das, ironically a neoliberal, has a superb article at the Minyanville, which elaborates on how regulations and government policies, which I earlier posted, has shaped the incentives of Too Big to Fail institutions to take excessive risks and the failure of regulators to prevent them (all bold emphasis mine)

The large investment portfolio is the result of banks needing to maintain high levels of liquidity, dictated by both volatile market conditions and also regulatory pressures to maintain larger cash buffers against contingencies. Broader monetary policies, such as quantitative easing, have also increased cash held by banks, which must be deployed profitably. Regulatory moves to prevent banks from trading on their own account -- the Volcker Rule -- have encouraged the migration of trading to other areas of the bank, such as liquidity management and portfolio risk management hedging.

Faced with weak revenues in its core operations and low interest rates on cash or secure short term investment, JPMorgan may have been under pressure to increase returns on this portfolio. The bank appears to have invested in a variety of securities, including mortgage backed securities and corporate debt, to generate returns above the firm’s cost of capital.

Again, the failure of models…

Given JPMorgan vaunted risk management credentials and boasts of a “fortress like” balance sheet, it is surprising that the problems of the hedge were not identified earlier. In general, most banks stress test hedges to ensure their efficacy prior to implementation and monitor them closely.

While the $2 billion loss is grievous, the bank’s restatement of its VaR risk from $67 million to $129 million (an increase of 93%) and reinstatement of an older risk model is also significant, suggesting a failure of risk modeling.

The knowledge problem…

Banks are now obliged to report positions and trades, especially certain credit derivatives. This information is available to regulators in considerable detail. Given that the hedge appears to have been large in size (estimates range from ten to hundreds of billions), regulators should have been aware of the positions. It is not clear whether they knew and what discussions if any ensued with the bank.

External auditors and equity analysts who cover the bank also did not pick up the potential problems. Like regulators, they perhaps relied on assurances from the bank’s management, without performing the required independent analysis.

Hayek’s “Fatal Conceit” or the pretentions of knowledge by regulators to apply controls over society or the marketplace…

Legislators and regulators now argue that the rules for portfolio hedging are too wide and impossible to police effectively. In addition, the statutory basis may not support the rule. The legislative intent was intended only to exempt risk-mitigating hedging activity, specifically hedging positions that reduce a bank’s risk. Interestingly, drafters of the portfolio hedging exemption recognized the potential problems, seeking comment on whether portfolio hedging created “the potential for abuse of the hedging exemption” or made it difficult to distinguish between hedging or prohibited trading.

In a recent Congressional hearing, Former Fed Chairman Paul Volcker, who helped shape the eponymous provision, questioned whether the volume of derivatives traded was “all directed toward some explicit protection against some explicit risk.”

The pundits have been quick to suggest that the losses point to the need for more stringent regulations. But it is not clear that a prohibition on proprietary trading would have prevented the losses.

In practice, without deep and intimate knowledge of the institution and its activities, it is difficult to differentiate between legitimate investment and trading of a firm’s surplus cash resources or investment capital.

It is also difficult sometimes to distinguish between hedging and speculation. The JPMorgan positions that caused the problems were predicated on certain market movements -- a flattening of the credit margin term structure -- which did not occur.

Hedging individual positions is impractical and would be expensive. It would push up the cost of credit to borrowers significantly. All hedging also entails risk. At a minimum, it assumes that the counterparty performs on its hedge. But inability to legitimately hedge also escalates risk of financial institutions. Ultimately no hedging is perfect. or as author Frank Partnoy told Bloomberg: “The only perfect hedge is in a Japanese garden.”

Additional regulation assumes that the appropriate rules can be drafted and policed. Experience suggests that it will not prevent future problems.

Bankers and regulators have always been seduced by an elegant vision of a scientific and mathematically precise vision of risk. As the English author G.K. Chesterton wrote: “The real trouble with this world [is that]…. It looks just a little more mathematical and regular than it is; its exactitude is obvious but its inexactitude is hidden; its wildness lies in wait.”

In reality it is not just “without deep and intimate knowledge of the institution and its activities” but about having the prior knowledge of the choices of the individuals behind these institutions. This is virtually unknowable.

Finally, the monumental government failure…

How do regulatory initiatives and monetary policy action affect bank risk taking? Central bank policies are adding to the problem of banks in terms of large cash balances which must be then invested at a profit. The implementation of the Volcker Rule may have had unintended consequences. It encouraged moving risk-taking activities from trading desks where the apparatus of risk management may be marginally better established to other parts of banks where there is less scrutiny.

The most important question remains whether any specific action short of banning specific instruments and activities can prevent such episodes in the future. It seems as Lord Voldemort observed in Harry Potter and the Deathly Hallows Part 2: “They never learn. Such a pity.”

People who are blinded by power and or the thought of power never really learn.

Quote of the Day: Blinded by Science

Even some from the mainstream gets it.

Finance is often said to suffer from Physics Envy. This is generally held to mean that we in finance would love to write out complex equations and models as do those working in the field of Physics. There are certainly a large number of market participants who would love this outcome.

I believe, though, that there is much we could learn from Physics. For instance, you don’t find physicists betting that a feather and a brick will hit the ground at the same time in the real world. In other words, they are acutely aware of the limitations imposed by their assumptions. In contrast, all too often people seem ready to bet the ranch on the flimsiest of financial models.

Someone intelligent (if only I could remember who!) once opined that rather than breaking the sciences into the usual categories of “Hard” and “Soft,” they should be split into “Easy” and “Difficult.” The “Hard” sciences are generally “Easy” thanks to the ability to perform repeated controlled experiments. In contrast, the “Soft” sciences are “Difficult” because they involve trying to understand human behaviour.

Put another way, the atoms of the feather and brick don’t try to outsmart and exploit the laws of physics. Yet financial models often fail for exactly this reason. All financial model underpinnings and assumptions should be rigorously reviewed to find their weakest links or the elements they deliberately ignore, as these are the most likely source of a model’s failure.

That’s from GMO’s James Montier (source Zero Hedge).

Mr. Montier also discusses the psychological aspects of people’s predisposition for mathematical or science based models: particularly “complexity to impress” (The penchant to signal “intelligence” to acquire social acceptance—my opinion) and “defer to authority”.

And here is the warning against being blinded by science from the dean of the Austrian school of economics the great Professor Murray N. Rothbard,

Not only measurement but the use of mathematics in general in the social sciences and philosophy today, is an illegitimate transfer from physics. In the first place, a mathematical equation implies the existence of quantities that can be equated, which in turn implies a unit of measurement for these quantities. Second, mathematical relations are functional; that is, variables are interdependent, and identifying the causal variable depends on which is held as given and which is changed. This methodology is appropriate in physics, where entities do not themselves provide the causes for their actions, but instead are determined by discoverable quantitative laws of their nature and the nature of the interacting entities. But in human action, the free-will choice of the human consciousness is the cause, and this cause generates certain effects. The mathematical concept of an interdetermining "function" is therefore inappropriate.

Quote of the Day: The Value of Superfluous Fluff

Some economists like to believe (although this belief has blessedly faded in the recent decades) that economics is an edifice built on the rocks of mathematical theory and statistical empiricism, and everything else is superfluous fluff. McCloskey (1983) thoroughly strafed that conceit, pointing out in “The Rhetoric of Economics” that the research and analysis of economists is built on uncertain and subjective judgments, and often uses, among its rhetorical tools, analogy and metaphor, appeals to authority and to commonsense intuition, and the use of “toy models” counterbalanced with the choice of supposedly illustrative real-world episodes.

Economic arguments rooted purely in mathematical formalism or statistical analyses are superb at specifying the steps leading to the particular conclusion. However, cynical economists (but I repeat myself) know that a model can be built to illustrate any desired conclusion, and that if the data are tortured for long enough, they will confess to anything. Persuasiveness requires a multidimensional argument that reaches beyond formalism. As McCloskey (1983) wrote: “There is no good reason to to make ‘scientific’ as opposed to plausible statements.”

That’s from economist Timothy Taylor on the issue of editing economists (hat tip Professor David Henderson).

Phony and manipulated “tortured” models function as standard instruments used to justify social controls through public policies. Think anthropomorphic global warming, Keynesian stimulus, mercantilism and etc…

Climate Change Alarmist James Lovelock Admits Mistake

One of the intellectual pillars of climate change alarmism admits that his predictions have failed.

The MSNBC.com reports (my tip of the hat to libertarian colleague Patrick Ella)

James Lovelock, the maverick scientist who became a guru to the environmental movement with his “Gaia” theory of the Earth as a single organism, has admitted to being “alarmist” about climate change and says other environmental commentators, such as Al Gore, were too.

Lovelock, 92, is writing a new book in which he will say climate change is still happening, but not as quickly as he once feared.

He previously painted some of the direst visions of the effects of climate change. In 2006, in an article in the U.K.’s Independent newspaper, he wrote that “before this century is over billions of us will die and the few breeding pairs of people that survive will be in the Arctic where the climate remains tolerable.”…

Mr. Lovelock acknowledges that his models didn’t work and that environmentalists have been overestimating on their understanding of nature.

More from the same article…

“The problem is we don’t know what the climate is doing. We thought we knew 20 years ago. That led to some alarmist books – mine included – because it looked clear-cut, but it hasn’t happened,” Lovelock said.

“The climate is doing its usual tricks. There’s nothing much really happening yet. We were supposed to be halfway toward a frying world now,” he said.

“The world has not warmed up very much since the millennium. Twelve years is a reasonable time… it (the temperature) has stayed almost constant, whereas it should have been rising -- carbon dioxide is rising, no question about that,” he added.

He pointed to Gore’s “An Inconvenient Truth” and Tim Flannery’s “The Weather Makers” as other examples of “alarmist” forecasts of the future…

His admission…

“We will have global warming, but it’s been deferred a bit,” Lovelock said.

'I made a mistake'

As “an independent and a loner,” he said he did not mind saying “All right, I made a mistake.” He claimed a university or government scientist might fear an admission of a mistake would lead to the loss of funding.

Just say what government wants and funding will follow. This epitomizes the politics of climate change.

At least Mr. Lovelock has been forthright enough to face up with reality. Although like doomsday diviner Harold Camping whose controversial forecasts in 2011 failed to materialize, Mr. Lovelock seems locked into a defensive posture to protect his work by pushing his forecasts to the indeterminate future.

Only when the tide goes out, said Warren Buffett, do you discover who’s been swimming naked.

Apparently the anthropomorphic climate change dogma has been swimming naked.

Entrepreneurship: The Gap Between Theories and Practice

Kate Maxewell of the Kauffman Foundation writing at the Growthology blog observes of the chasm between entrepreneurial literatures and entrepreneurs in action (bold emphasis mine)

In my reading of the entrepreneurship literature I have been struck by the large gap between entrepreneurs and people who study entrepreneurship. The group of people who self select into entrepreneurship is almost entirely disjoint from the group of people who self select to study it. Such a gap exists in other fields to greater and lesser degrees. Sociologists, for instance, study phenomenon in which they are clearly participants whereas political scientists are rarely career politicians but are often actors in political systems.

But in the case of entrepreneurship the gap is cause for concern. My sense is that all too often those studying entrepreneurship don’t understand, even through exposure, the messy process of creating a business, nor, due to selection effects, are they naturally inclined to think like an entrepreneur might. At Kauffman, we have had multiple scholars say to us that they’ve found that talking to entrepreneurs is useful in their research.

This should be obvious, but it’s not. The result is research that can lack grounding, perspective and credibility. As a researcher I understand the natural impulse to keep things neatly ordered so as to create elegant papers and clear conclusions. But the fact of entrepreneurship is that it is anything but pretty or neat. More importantly, the research product resulting from such a disconnect can present a distorted view of the entrepreneurial process that may actually hinder our understanding of it. Such ill-informed research can then go on to form the basis of a policy directed at entrepreneurs – without ever having involved or understood them.

Like investing in markets, theories and practice are often detached. Yet many cling to the barnacle of academic mirages that perceives entrepreneurship as rigorous methodological science.

And as I earlier pointed out entrepreneurial traits are not acquired from books or from the academia and don’t require ‘new attitudes’. Instead they emanate from observation, knowledge, the willingness to learn from failure, and most importantly, the desire to undertake activities that profits from risk ventures through servicing or producing for the consumers.

As the great Ludwig von Mises pointed out, (bold emphasis added)

In order to succeed in business a man does not need a degree from a school of business administration. These schools train the subalterns for routine jobs. They certainly do not train entrepreneurs. An entrepreneur cannot be trained. A man becomes an entrepreneur in seizing an opportunity and filling the gap. No special education is required for such a display of keen judgment, foresight, and energy. The most successful businessmen were often uneducated when measured by the scholastic standards of the teaching profession. But they were equal to their social function of adjusting production to the most urgent demand. Because of these merits the consumers chose them for business leadership.

In short, as part of human action entrepreneurship represents more a work of art—which attempts to satisfy the preferences and value scales of consumers—than of science.

Are High IQs Key to Successful Investing?

Yale Professor Robert Shiller thinks so.

Writing at the New York Times,

YOU don’t have to be a genius to pick good investments. But does having a high I.Q. score help?

The answer, according to a paper published in the December issue of The Journal of Finance, is a qualified yes.

The study is certainly provocative. Even after taking into account factors like income and education, the authors concluded that people with relatively high I.Q.’s typically diversify their investment portfolios more than those with lower scores and invest more heavily in the stock market. They also tend to favor small-capitalization stocks, which have historically beaten the broader market, as well as companies with high book values relative to their share prices.

The results are that people with high I.Q.’s build portfolios with better risk-return profiles than their lower-scoring peers.

Certainly, caution is needed here. I.Q. tests are controversial as to what they measure, and factors like income, quality of education, and family background may not be completely controlled for. But the study’s results are worth pondering for their possible implications.

So how valid is such claim?

Let’s get some clues from some of my favorite investors.

Here is the legendary Jesse Livermore (bold emphasis mine)

The market does not beat them. They beat themselves, because though they have brains they cannot sit tight. Old Turkey was dead right in doing and saying what he did. He had not only the courage of his convictions but also the intelligence and patience to sit tight.

When I am long of stocks it is because my reading of conditions has made me bullish. But you find many people, reputed to be intelligent, who are bullish because they have stocks. I do not allow my possessions – or my prepossessions either – to do any thinking for me. That is why I repeat that I never argue with the tape.

Mr. Livermore simply posits that intelligence can be overwhelmed by egos and cognitive biases (particularly in the second quote the endowment effect, Wikipedia.org—where people place a higher value on objects they own than objects that they do not.).

Here is the 10 investing principles by another investing titan the late Sir John Templeton

1. Invest for real returns 2. Keep an open mind 3. Never follow the crowd 4. Everything changes 5. Avoid the popular 6. Learn from your mistakes 7. Buy during times of pessimism 8. Search worldwide 9. Hunt for value and bargains 10. No-one knows everything

More from John Templeton

“Bull markets are born on pessimism, grown on skepticism, mature on optimism and die on euphoria. The time of maximum pessimism is the best time to buy, and the time of maximum optimism is the best time to sell.

Here is value investor turned crony, Warren Buffett. I’d say that Mr. Buffett’s original wisdom has been a treasure. (bold emphasis mine)

‘I will tell you how to become rich. Close the doors. Be fearful when others are greedy. Be greedy when others are fearful.’

‘Read Ben Graham and Phil Fisher read annual reports, but don’t do equations with Greek letters in them.’

‘Never invest in a business you cannot understand.’

‘You’re neither right nor wrong because other people agree with you. You’re right because your facts are right and your reasoning is right – that’s the only thing that makes you right. And if your facts and reasoning are right, you don’t have to worry about anybody else.’

Does all the above sound like high IQ stuff? Evidently they represent more common sense and the school of hard knocks stuff.

Yet to the contrary, high IQs can translate to portfolio disasters.

The landmark bankruptcy by Long Term Capital Management in 1998 had been a company headed by 2 Nobel Prize winners. The company’s failure has substantially been due to flawed trading models.

In 2008, the 5 largest US investment banks vanished. These companies had an army of economists, statisticians and quant modelers, accountants, lawyers and all sort of experts who we assume, because of their stratospheric salaries and perquisites, had high IQs.

When Queen Elizabeth asked why ‘no one foresaw’ the crisis coming, the reply by the London School of Economics (LSE)

"In summary, Your Majesty," they conclude, "the failure to foresee the timing, extent and severity of the crisis and to head it off, while it had many causes, was principally a failure of the collective imagination of many bright people, both in this country and internationally, to understand the risks to the system as a whole."

Imagination had been scarce because the same army of experts heavily relied on mathematical models in dealing with investments. They did not follow the common sense advise by the real experts.

My favorite iconoclast author Nassim Taleb in Fooled by Randomness offers an explanation (emphasis added)

it is also scientific fact, and a shocking one, that both risk detection and risk avoidance are not mediated in the “thinking” part of the brain but largely in the emotional one (the “risk as feelings” theory). The consequences are not trivial: It means that rational thinking has little, very little, to do with risk avoidance. Much of what rational thinking seems to do is rationalize one’s actions by fitting some logic to them.

What the consensus mistakenly thinks as rational is, in reality, the emotional. Thus, we need more Emotional Intelligence (EI) rather than high IQs

The most important observation or lesson is one of the repeated botched attempts by high IQ people to transform investing into ‘science’.

Well, because investing involves people’s valuations and preferences, all of which constitutes human action, in truth, investing is more than science…

As the great Ludwig von Mises explained. (bold highlights mine)

For the science of human action, the valuations and goals of the final order at which men aim constitute the ultimate given, which it is unable to explain any further. Science can record and classify values, but it can no more "explain" them than it can prescribe the values that are to be acknowledged as correct or condemned as perverted. The intuitive apprehension of values by means of understanding is still not an "explanation." All that it attempts to do is to see and determine what the values in a given case are, and nothing more. Where the historian tries to go beyond this, he becomes an apologist or a judge, an agitator or a politician. He leaves the sphere of reflective, inquiring, theoretical science and himself enters the arena of human action.

...but rather, investing is an art.

Again Professor Mises from the same article.(emphasis added)

The position of science toward the other values of acting men is no different from that which it adopts toward aesthetic values. Here too science can do no more with respect to the values themselves than to record them and, at most, classify them as well. All that it can accomplish with the aid of "conception" relates to the means that are to lead to the realization of values, in short, to the rational behavior of men aiming at ends.

Bottom line: The art of managing our emotions or emotional intelligence, via common sense and self-discipline, is more important than having high IQs.

Model Failure: Unreliable Statistical Index (LEI)

More testament of the glaring failures of statistical aggregates or econometrics from Dr. Ed Yardeni, (bold emphasis mine)

I’m not a big fan of leading economic indexes (LEIs). They can be quite misleading. They are constructed by well-intentioned economists with the intention of providing an early warning that a recession is coming in a few months or assurance that the economy is likely to expand in coming months. These man-made indexes combine a bunch of indicators that purportedly lead the business cycle. When they fail to do so, the men and women who made these indexes recall them, retool them, and send them back out for all of us to marvel at how well these new improved versions would have worked in the past. I can accurately predict that when they fail in the future, they will be recalled and redesigned yet again.

This just happened to the US LEI. The Conference Board has made the first major overhaul of the components of the LEI since it assumed responsibility of the index in 1996. It replaced real money supply with its proprietary leading credit index, and the ISM supplier delivery index with the new orders index. In place of the Thomson Reuters/University of Michigan consumer expectations measure, it will now use an equally weighted average of its own consumer expectations index and the current measure. Also, the nondefense capital goods gauge was tweaked to exclude commercial aircraft.

The impact of these changes has been shocking, and really questions the credibility of constructing LEIs.

As shown above, econometricians and statisticians laboriously attempt to fit evidence into models in the hope that calibrating them would increase their predictive capabilities. Unfortunately, they don’t. That’s because social sciences isn’t physics.

As the great Friedrich von Hayek wrote,

the sort of knowledge with which I have been concerned is knowledge of the kind which by its nature cannot enter into statistics and therefore cannot be conveyed to any central authority in statistical form. The statistics which such a central authority would have to use would have to be arrived at precisely by abstracting from minor differences between the things, by lumping together, as resources of one kind, items which differ as regards location, quality, and other particulars, in a way which may be very significant for the specific decision. It follows from this that central planning based on statistical information by its nature cannot take direct account of these circumstances of time and place and that the central planner will have to find some way or other in which the decisions depending on them can be left to the "man on the spot."

Prediction Failure: Hurricane Forecasters Give Up

Another instance where math models, here applied to weather forecasting, has failed to live up to its much touted reputation (hat tip: Professor Russ Roberts)

From OttawaCitizen.com

Two top U.S. hurricane forecasters, famous across Deep South hurricane country, are quitting the practice of making a seasonal forecast in December because it doesn’t work.

William Gray and Phil Klotzbach say a look back shows their past 20 years of forecasts had no predictive value.

The two scientists from Colorado State University will still discuss different probabilities of hurricane seasons in December. But the shift signals how far humans are, even with supercomputers, from truly knowing what our weather will do in the long run.

Cheers to William Gray and Phil Klotzbach for admitting the truth.

Science Models Fail To Predict Japan’s Earthquake

If you think man has acquired enough expertise to know the environment, think again.

From the Washington Post, (bold highlights mine)

They have long been ready for the Big One in Japan. But when it arrived Friday, it was still surprising, still utterly devastating, and it left scientists around the world humbled at how unpredictable the heaving and lurching earth can be.

Japanese geologists have long forecast a huge earthquake along a major plate boundary southwest of Tokyo, and have poured enormous resources into monitoring the faint traces of strain building in that portion of the earth's crust. They have predicted in great detail the amount of property damage and the number of landslides such a tremor would generate. They have even given the conjectured event a name: The Tokai Earthquake.

Lesson: Despite the massive advances in technology, there is a limit to the knowledge man can acquire from the innate complexity of nature.

As aptly pointed out by Friedrich von Hayek in his Nobel Prize speech ‘The Pretence of Knowledge’… (bold emphasis mine)

The chief point we must remember is that the great and rapid advance of the physical sciences took place in fields where it proved that explanation and prediction could be based on laws which accounted for the observed phenomena as functions of comparatively few variables - either particular facts or relative frequencies of events. This may even be the ultimate reason why we single out these realms as "physical" in contrast to those more highly organized structures which I have here called essentially complex phenomena. There is no reason why the position must be the same in the latter as in the former fields. The difficulties which we encounter in the latter are not, as one might at first suspect, difficulties about formulating theories for the explanation of the observed events - although they cause also special difficulties about testing proposed explanations and therefore about eliminating bad theories. They are due to the chief problem which arises when we apply our theories to any particular situation in the real world. A theory of essentially complex phenomena must refer to a large number of particular facts; and to derive a prediction from it, or to test it, we have to ascertain all these particular facts. Once we succeeded in this there should be no particular difficulty about deriving testable predictions - with the help of modern computers it should be easy enough to insert these data into the appropriate blanks of the theoretical formulae and to derive a prediction. The real difficulty, to the solution of which science has little to contribute, and which is sometimes indeed insoluble, consists in the ascertainment of the particular facts.

And this applies to sociology too.

Bottom line: We should be leery of anyone who peddle to us the reliability of predictions based on science or math models, especially those who advance the policy of interventionism.

And this applies to whether we deal with the financial markets and the economy or with environmental issues such as global warming.

The Model Curse Strikes Again!

The curse of Models have struck again! And apparently government based models has been alleged as a vital contributor to the massive oil spill in Gulf of Mexico in the US!

Here is the Wall Street Journal, (hat tip Russ Roberts)

``BP PLC and other big oil companies based their plans for responding to a big oil spill in the Gulf of Mexico on U.S. government projections that gave very low odds of oil hitting shore, even in the case of a spill much larger than the current one.

``The government models, which oil companies are required to use but have not been updated since 2004, assumed that most of the oil would rapidly evaporate or get broken up by waves or weather. In the weeks since the Deepwater Horizon caught fire and sank, real life has proven these models, prepared by the Interior Department's Mineral Management Service, wrong... (emphasis added)

As Friedrich Hayek once wrote, "The curious task of economics is to demonstrate to men how little they really know about what they imagine they can design."

How true.