Obscured Risk Associated with Hedging

Obscured Risk Associated with Hedging This article is a continuation of my remarks begun last week. The central points were:

There are many ways one can be wrong when hedging and that the hedged investment positions can not only fail, but create additional losses (as the trader at JPMorgan Chase discovered.)

We are experiencing, in the words of PIMCO’s Bill Gross, “A secular delevering” while in the midst of an “authentic debt crisis.”

Risk control has little to do with investment products and everything to do with the mindset that governs the way the investor operates.

I will continue to shine light on a largely underestimated and consequently obscured risk associated with hedging and derivative investment products – a risk that has broad implications, extending far beyond Wall Street. Even if I am only partially correct, failed theoretical frameworks like today’s modern hedging strategies, the Efficient Market Hypothesis, Modern Portfolio Theory, etc. could precipitate an exceedingly painful redistribution of wealth from ignorant hands to knowledgeable hands.

The Irony

According to Greek mythology, Apollo, the son of Zeus and Leto, became infatuated with Cassandra and promised her the gift of prophecy to seduce her. Subsequent to their single liaison Cassandra rebuffed Apollo’s future advances. Enraged, Apollo cursed Cassandra so that while she would retain the gift of prophecy no one would ever believe her. The Trojans ignored her when she beseeched them to forbid the wooden horse, left as a “victory gift” by the Greeks, from being brought into the city – and we know how that turned out.

Fast forward a few millennia to the evolving events of today and we are presented with an irony worthy of ancient Greek mythology: it is the Greeks (among others) who welcomed the debt laden Trojan horse into their financial city notwithstanding numerous warnings by modern day Cassandras.

A Very Short History of Currency 

For most of human history, the exchange of goods and services has been dominated by barter. As societies grew more sophisticated, barter gave way to coin. The ability to “store” purchasing power via currency encouraged not only a more efficient exchange of goods and services – greatly facilitating trade and commerce – it also enabled the settling of accounts at some future date. The settling of accounts in the future was antecedent to more sophisticated forms of credit – credit being little more than a promise to repay a debt in the future.

In early 17th century England, merchants and traders entrusted their gold to the Royal Mint for storage and safekeeping. But in 1640, King Charles I seized the private reserves of the gold stored in the Royal Mint as a forced loan which was to be paid back over time. After that experience merchants preferred to store their gold in the private vaults of the goldsmiths of London for which the goldsmiths charged a fee. In exchange for each deposit of precious metal, the goldsmiths issued receipts certifying the quantity and purity of the metal they held in trust.

One of the first modern banking instruments to develop was the issuance of depository receipts which evolved into an assignable instrument (promissory note), circulating as a trusted and convenient form of currency backed by the goldsmith’s promise to pay. These goldsmith issued promissory notes (currency) were increasingly used in trade, and merchants and traders became increasingly comfortable with settling their accounts without requiring payment in physical gold. Goldsmiths could now advance loans and, in so doing, they became the forerunners of modern day banking as well as the creators of a fungible medium of exchange (currency or money) based on trust. Notice that each goldsmith (“bank”), by issuing its own promissory notes, created its own specific circulating currency.

At some point the goldsmiths observed that their merchant and trader clients would rarely redeem their gold, and even more rarely would redemption occur en masse. This “surplus” reserve – i.e. their client’s gold reserves – retained for safekeeping by the goldsmiths could now be invested in interest-bearing loans. This generated income for the goldsmiths but resulted in more notes on issue than actual reserves with which to redeem the notes. Over time this development altered the role of the goldsmiths from passive guardians of bullion, charging fees for safe storage, to interest-paying and interest-earning banks. Fractional-reserve banking was born.

But there is an unambiguous potential problem in a fractional-reserve banking structure. If enough creditors (gold depositors) lose faith in the ability of the “bank” to redeem (pay) their notes, goldsmiths would court the risk that their creditors might demand redemption of their notes en masse, and thus precipitate a “run on the bank.” If the bank was unable to raise sufficient funds by calling in loans or raising additional capital, it was deemed insolvent (i.e. it was unable to satisfy its obligations in a timely fashion) which frequently lead to the bank defaulting on its notes. Insolvency led to the demise of many early banks.

Fast forward to United States circa 1900 where many banks were failing for a variety of reasons, rendering their individual currencies worthless. In response, the Federal Reserve was installed in 1913 to stabilize the banking system. The Federal Reserve became the central bank of the U.S., and the dollar became our exclusive currency. The Federal Reserve was broadly charged with providing the nation with a safer, more flexible, and more stable monetary and financial system. The Fed has the authority to regulate commercial banks, impose reserve requirements, and act as the lender-of-last-resort to member banks by providing backup liquidity to extinguish the risk of a bank run. A major objective of all central banks is to mitigate the dangers associated with fractional reserve banking. (Whether they have succeeded in mitigating or exacerbating the dangers associated with fractional reserve banking is an unresolved question.)

There is no doubt, over the ensuing 100+ years since 1900, the process of credit creation powered the unparalleled economic growth of what were to become the financially advantaged nations. But credit creation is a two edged sword: as much as the absence of credit hindered earlier societies, the excess of credit now threatens modern economies.

Credit is a vital catalyst in the wealth creation process, acting as a commercial lubricant. But excessive credit promotes instability and potential wealth destruction. “Like nuclear energy” explains PIMCO’s Bill Gross, “‘atomic’ credit or debt must be controlled if it is to benefit, as opposed to destroy. And so the job of modern-day central bankers – Bernanke, King, Draghi and their counterparts – is to decide how to control a beneficial chain reaction without [it] getting out of hand.

“…Yet how much credit is too much credit and how is a ded­i­cated cen­tral banker to know? Part of the prob­lem is in clearly defin­ing what does or doesn’t fit the def­i­n­i­tion. There are the fam­i­lies of M’s – M1, M2 and the dis­banded M3 in the U.S. – the for­mer two of which the Fed now loosely uses to mon­i­tor a growth rate so as not to bring credit cre­ation to a boil. 21st cen­tury pri­va­teers, how­ever, proved there can be no accu­rate gauge of credit growth as long as banks and the shadow banks can cre­ate their own money at will. CDOs, CLOs and secu­ri­tized lend­ing that man­aged to skirt reg­u­la­tory stan­dards for bank loans… made a mock­ery of sound bank­ing and ulti­mately cre­ated great risk for cen­tral bankers and their abil­ity to tem­per the excess of credit cre­ation. In 2008, cen­tral bankers never really knew how much debt was out there, and to be hon­est, they don’t know now.”

The Failure of Inductive Reasoning

The failure to anticipate the unexpected is one of the central challenges we face as human beings generally, and as investors specifically. Nowhere is this concept more clearly presented than in Nassim Taleb’s book, The Black Swan – and most explicitly in Taleb’s Thanksgiving Turkey illustration.

Imagine a turkey who experiences a lifetime of care and feeding from the most benevolent of creatures, the Homo Sapien. With each feeding, the bird’s faith and trust is reaffirmed… until shortly before Thanksgiving Day. With the flash of a steel blade, the bird’s worldview is altered, irrevocably. We, like the turkey, are just as vulnerable to life’s enigmatic interventions due to our incorrect assumptions and reasoning. By relying on inductive reasoning – the process of unconsciously divining that the future will resemble the past by observing past experiences and generalizing that knowledge – we are as vulnerable as the turkey.

It is this inductive reasoning bias that, in large measure, was the reason those who should have seen the banking crisis coming, did not. And those who did see it coming – and we were not alone! – endured the fate of a modern day Cassandra. If we are to overcome our inductive reasoning biases, we must incorporate into our thinking the inevitability of Black Swans and Predictable Surprises.

Nassim Taleb describes Black Swans as statistical outliers that create an extreme effect, operating in the realm of random events and “unknown unknowns.” Black Swans also encourage “false-cause” thinking. That is, human beings innately seek to explain the world by means of cause and effect scrutiny. While one may learn what caused a specific incident, few learn what is most critical: you can never truly foresee the emergence and/or timing of a Black Swan.

In contrast to Black Swans are what Watkins and Bazerman call Predictable Surprises. Predictable Surprises are preceded by clear warning signals that folks simply miss or choose to ignore. According to Watkins and Bazerman, predictable surprises are characterized by these three elements: there is a small minority of people who are aware of the problem; the problem gets worse over time; eventually the problem transitions into a crisis.

The Gaussian frequency distribution, more commonly referred to as the bell shaped curve, is a backward looking model. Regrettably, a backward looking model is wholly inadequate in measuring investment risk because a backward looking model is incapable of accounting for an event that never occurred before – like a national contraction of residential real estate prices exceeding 30% which triggered the housing bubble collapse. Today’s risk management experts, rather than abandon the deeply flawed Gaussian frequency distribution risk model, simply continue to tinker with it. I liken these risk management experts, and the inevitable consequence of employing a flawed model, to a bug in pursuit of a windshield.

These are the facts: capital markets are not always efficient, the distribution of risk is not normally distributed (i.e. bell shaped), and not all price movements are random. That these facts alone seem unable to dislodge the discredited backward looking Gaussian frequency distributions underscore another human failing: the intellectual entrenchment bias. In his 1964 letter to his partners, Warren Buffett humorously depicted the irrational behavior of investors who refuse to reject failed investment assumptions and approaches by explaining, “In some corner of the world they are probably still holding regular meetings of the Flat Earth Society.”

Value at Risk

“Value at Risk” (VaR) has emerged as a “sophisticated” enhancement/extension of this flawed risk management framework. VaR purportedly measures aggregate portfolio risk. The VaR hypothesis is that individual risky positions are presumed to offset each other, rendering a potentially high risk portfolio to be safer. If, for example, a portfolio has a $1 million long position in a specific security, and a $1million short position in a similar security, a risk management model like VaR subtracts the short position from the long position. Voilà! – the aggregate risk level is now netted out and it is affirmed to be a safer portfolio.

Notice VaR assumes future relationships will resemble the past; that price fluctuations are never synchronized; and that risk is measured by “net” exposures. Also notice that VaR became the Great Enabler of the financial crisis of 2008. As you will see next week, in a complex adaptive system that incorporates power laws and scale, the risk elements depicted in a VaR model should be added together, not netted out.

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