NetCompetition

In the fall of 2008, we all were shocked to learn that the root system of our capital markets, that we had always assumed was healthy and strong, was actually frighteningly weak and brittle requiring the slapdash reinforcement of multi-trillion dollar emergency scaffolding of whatever material was close at hand, a TARP, bailout lifelines, capital sandbags, etc. — to buttress the main market “trees” from toppling over, trees that the Government judged to big to be allowed to fall.

With the financial storm clouds apparently passed for now, many are becoming complacent, because the old adage is true — out of sight out of mind. Moreover, everyone desperately wants and needs to be able to assume that the essential root system that they cannot see is fine and nothing to worry about. That’s because if people knew the root system was weak with root rot, systemic uneconomics, they would have less confidence in the capital markets forest or the fledgling economic recovery.

So many are myopically focusing on structurally preventing the trees from falling down, largely by packing tens of billions of dollars of additional capital “soil” around the base of the trees to try and reinforce them. More capital “soil” to reinforce the trees makes good sense. However, it totally covers up the most important point — that the capital markets forest must have a healthy root system so that the market’s trees can stand by themselves long-term. If the health of the root system is not restored with sound economics, it won’t be able to withstand future storms/crises that will surely come, if the future is anything like the past three decades.

Unfortunately, we also know that another old adage is true: what we don’t know can hurt us.

The real problem is neither the market nor economics, but the irresponsible proliferation of inherently uneconomic financial instruments that undermine the ability of natural market economics to function. It is common sense that if enough inherently uneconomic activity is introduced, condoned, and allowed to spread broadly and deeply into the public capital markets system, public markets deteriorate from being systemically economic to being systemically uneconomic; in other words the systemically dysfunctional mess we witnessed in the dismal fall of 2008.  

More specifically, the root system rot of uneconomics comes from introducing a variety of inherently uneconomic derivative financial instruments into the public capital markets system, that inherently undermine, weaken and destabilize the market’s (or invisible hand’s) natural ability to equilibrate: supply and demand; risk and reward; the borrower and lender relationship; the balance between short and long term horizons; and the economic equation between risk and insurance.

Let me be crystal clear, financial derivatives themselves are not the problem because derivatives can be economic and have many legitimate and valuable benefits. As I explained in Part II of this series, “Systemic Risk Laundering,” the problem is an unaccountable, out-of-control derivative system where derivatives are all assumed to be systemically benign and allowed to destroy the underlying public asset they are derived from. Central to accountability is the fundamental question: is a particular derivative financial instrument economic or uneconomic when integrated into the overall capital market system? In other words, are particular derivative instruments constructive or destructive to the core economic linkage of: supply and demand? Risk and reward? Borrower and lender? Short term and long term? Risk and insurance? To carry the root metaphor deeper, do the particular derivative instruments impede, block, or distort the root system’s natural ability to absorb and benefit from the water and nutrients in the soil?

So what are the uneconomic derivative financial instruments that create systemic risk and systemic uneconomic dysfunction?

First, employee stock options (in stark contrast to actual employee stock grants) are inherently uneconomic because they pervasively disconnect risk from reward and supply from demand. Stock options are the market equivalent of something for nothing, an opportunity to gain with no offsetting opportunity to lose. Stock options, unlike stock grants or the buying or selling of stock, are one-way upside potential with no potential downside risk. The tech bubble taught us that too much personal financial opportunity divorced from any personal financial risk encourages unwarranted risk taking with other peoples’ money. Typical of the system, not enough was done after the tech bubble to address the inherent uneconomic nature of stock options, so they continue to rot away the market’s natural strength to this day.  

Second, indexing financial instruments are inherently uneconomic because pervasive indexing is inherently destabilizing, anti-capital formation, speculative, and hyper-stressing of the financial system, as I described in Part I of this series: “Indexing into the Ditch.” Indexing naturally impedes the market’s ability to reach equilibrium by exacerbating market volatility because it artificially creates a massive one-sided economic market. It generates substantial supply with no offsetting demand in a down market; and it generates substantial demand with no offsetting supply in an up market. Indexing fosters a market momentum dynamic which means a dominant segment of the market does not care about economics: price, fundamentals or time horizon — at all. Therefore prices can never be too high or too low for an indexer because economics have absolutely nothing to do with indexing.  

Third, off-exchange derivatives often are destructively uneconomic, because like indexing, they can subordinate the first purpose of an underlying publicly-traded asset by advantaging the second purpose of the derivative ahead of the first purpose of the publicly traded asset — the quintessential tail wagging the dog. Credit default swap derivative instruments were dangerously uneconomic in that they perverted the essential equilibrium of borrower and lender and the concept that insurance is only economically viable for quantifiable risk. New experiments with “life settlements” derivatives assuredly will end badly because they mix the economic concept of insurance for highly-quantifiable risk with markets with inherently unquantifiable risks, rewarding speculative arbitrage, manipulation and fraud.

Almost by definition, the second purposes of derivative instruments are different from the first purpose financial instruments, and that difference can either be benign and productive or uneconomic and destructive. Returning to the root system metaphor, many derivatives are akin to introducing untested synthetic bacteria or virus into the capital market’s forest ecosystem. The current near-total lack of accountability for many off-exchange derivatives means that anyone can dump in the capital market forest whatever they can convince or trick someone into buying.  

Finally, computer-automated program trading, or more simply algorithmic trading, is rapidly becoming the market norm because it offers efficiencies, mostly centered on substantially lowering transaction and management costs, which can contribute to better net performance. However, the much under-appreciated problem here is the inherent uneconomic “short-termism” effect of pervasive algorithmic trading in capital markets. The obsession, trend, and technology arms race to achieve ever faster, more complex, and more comprehensive automated trading is tautologically short-term focused. This is essentially devolving into a counter-productive race where artificial intelligence portfolio management arbitrages new information faster and faster (now measured in milliseconds and soon in nanoseconds), rather than compete for long-term investment returns — the universal goal of most investors, pensioners, and companies that are supposedly the true customers of the public capital markets system.

I call this pervasive and corrosive technological dynamic “algorithmia.” At core, algorithmia is a technological downward spiral to achieve a relative mili-second edge and is all about extremely short-term arbitrage, often less than a day. The flood of investable resources into immediate-term algorithmia only exacerbates the distortion and destabilization for the rest of the market that is trying to investment optimize for various long-term investment horizons that investors, pensioners and companies need.

Why algorithmia is profoundly uneconomic is that it powerfully disconnects the market’s natural function of reaching equilibrium by matching buyers and sellers via different investment horizons. If most liquid investable resources are inherently immediate-term focused, even if they are masquerading as having a longer term investment horizon, the long-term capital market purposes of capital formation, economic growth and investment simply cannot function economically. Algorithmia is not about investing at all, but about constant arbitrage within and between asset classes. In the virtual mathematical world of algorithmia, what happens in the real world that’s not readily quantifiable, other than infrequently reported official numbers, is largely irrelevant.  

Like indexing, algorithmia is inherently a momentum dynamic too, because what drives all of these algorithms is the same basic official input data. Once the market adjusts to new information the algorithmic task then shifts to see how the next piece of information will change the relative arbitrage equation competition based on what just happened, so this process is inherently sequential and cumulative, and hence momentum driven, not driven by economic fundamentals.

The 2008 Financial Crisis was a perfect and ominous example of the perils of algorithm-dominated markets. Algorithmia becomes a problem for the market when something happens that the programmers did not anticipate. Much of the market froze in fear in the fall of 2008 precisely because the established momentum of the market broke so unpredictably that many of the programs could not function as designed. In other words they worked when everything went according to plan, but they could be disastrous if and when the market behaved in an unanticipated or uneconomic way.

The scariest part of algorithmia is that almost by definition oversight and regulators will be lagging and reactive. Algorithmia also only increases the knowledge and sophistication gap between industry practitioners and regulators. Common sense suggests that, at a minimum, there needs to be an accountability system where all the algorithmic decisions and changes are at least subject to audit and re-creation by law enforcement, because without that deterrence and accountability, algorithmia, like off-exchange derivatives, will become a safe haven for speculators, market manipulators and fraudsters.

In sum, a primary root cause of the Financial Crisis of 2008 was systemic uneconomics: the ever-increasing accumulation of trillions of dollars of inherently uneconomic derivative financial instruments rotting out the root system of the capital markets forest. No amount of surface reinforcement or capital soil piled on the top of the big trees in the capital markets forest will enable the trees to stand on their own during the next big storm if their root systems continue to rot away from systemic uneconomics.

The best way to avert another financial crisis is stop the root rot in the capital markets forest. The best way to do that is to apply an “Accountability Framework Checklist” (like the one recommended below) to discern which derivative financial instruments and algorithmic practices are inherently economic and productive and which are inherently uneconomic and destructive. If the overall economic purposes of capital markets are capital formation, economic growth and investment, all the roots of the capital markets system need to be based on sound economics and not arbitrage, manipulation and fraud.

*****

Note: Don’t miss Part I & II of this research series:

• “Systemic Risk Laundering — Financial Crisis Root Causes — Part II” Click here.
•  “Indexing into the Ditch – Financial Crisis Root Causes – Part I” Click here.

***

Scott Cleland is President of Precursor LLC, an industry research and consulting firm, and was the Founding Chairman of the Investorside Research Association. Click here for Cleland’s Biography.

***

Systemic Risk Prevention Framework & Derivative Accountability Checklist

(Same Recommended Framework as in Part II of the series)

All of the thousands of new derivative financial instruments and systemic practices that have emerged over the last decade since the CFMA created a safe harbor from accountability need to be audited and evaluated for unaccountable systemic risk, fraud and uneconomics.

1. What asset, instrument, or market is the derivative dependent or predicated upon?
2. Does the derivative’s second purpose conflict with, or undermine, the first purposes/value of the underlying public asset, instrument, or market that the derivative is derived from?
3. How is the derivative interconnected with other assets, instruments, markets or counterparties? And to what extent is that interconnectedness reasonably transparent and known by all the affected parties?
4. What are the side effects, externalities, and long-term/cumulative effects of the derivative?
5. Does the derivative enhance or detract from the underlying asset, instrument, or market?
6. Does the derivative undermine or break any linkage/relationship/balance between:
   1. Supply and demand?
   2. Risk and reward?
   3. Borrower and lender?
   4. Short and long term?
   5. Risk and insurance?
7. As the derivative scales in usage could it foster systemic:
   1. Market momentum?
   2. Market speculation?
   3. Misrepresentation?
   4. Front running?
   5. Destabilization?
8. Is the derivative’s effect prone to undermining or discouraging capital formation?
9. Is the derivative’s effect prone to undermining market efficiency in reaching price equilibrium?
10. How could the derivative be susceptible to fraud or manipulation?
11. Does the derivative transfer risk transparently and with fair representation?
12. Does the derivative have independent research coverage?
13. How is the derivative accountable and to what/whom?
14. What are the accountability measures, (audit, internal controls, etc.) for the derivatives algorithms or quant models?
15. What independent third party audits and creates accountability for ensuring integrity of the algorithms and computer code that undergird these virtual derivative exchanges/systems?