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Friday, April 29, 2011

Beyond Rumsfeld by (Stephen A. Boyko and Willard C. Rappleye Jr.)

Introduction

Like him or dislike him. Agree or disagree with his policies. Donald H. Rumsfeld has had substantial careers in both private and public sectors. Yet his greatest governance contribution may have come in writing his memoirs when he segmented the randomness of policy making into known knowns, known unknowns, and unknown unknowns. This parallels a main point made in “We’re All Screwed (WAS)!” which emphasized the segmentation of randomness to provide better information for capital market governance.

Randomness is the range of variability of a complex adaptive system. A constant test to effective governance —the capability of systemic functions to do the right things, and efficient governance — the capability of systemic functions to do things right, is the relationship between the connective concept of randomness to its component parts of predictability, risk, and uncertainty. WAS reflexively provides the subjects to Rumsfeldian predicates for the construction of randomness sentences where:
·       Predictability is the known-knowns.
·       Risk is the known-unknowns. and,
·       Uncertainty is the unknown-unknowns.
Randomness sentences are complete thoughts that are more robust than foundational listings and enable greater innovative efficiencies to go “Beyond Rumsfeld.”

 Effectiveness

Effectiveness speaks to the capability of systemic functions to do the right things. Effective capital market governance requires structural change by segmenting one-size-fits-all deterministic metrics into WAS subjects of predictable, risky, and uncertain governance regimes. They form complete governance thoughts when joined to their related Rumsfeldian predicates of known knowns, known unknowns, and unknown unknowns. This description better enables information to correlate between governance metrics and their underlying economic domains’ randomness.

Managing randomness is a reflexive process between risk and uncertainty. Uncertainty is a separate and distinct concept not an extension of a “riskier form of risk”.[1]  The dictionary defines risk as the chance of loss. Risk deals with and is synonymous with probability. Risk presents foreseeable consequences. By comparison, uncertainty is indeterminate and characterized by unforeseeable consequences.

Risk and uncertainty are operationally different and require different approaches. With risk, one can insure (i.e. buying put options for portfolio insurance) and one can hedge (i.e., Ford and Exxon stocks in a portfolio). With uncertainty, one can insure against natural disasters, but cannot hedge. Uncertainty has no bounds.

Progress, in the form of innovation, takes place when uncertainty becomes risk. The uncertainty—risk conversion provides greater control over the underlying economic environment. Unless and until risk is differentiated from uncertainty errors of conflation will continue to result in noncorrelative information that produces larger and more frequent boom-bust bubbles.

Efficiency

Efficiency speaks to the capability to do things right by minimizing the functions of cost, effort, and time. Efficiency enables innovation to go “Beyond Rumsfeld” to 3-dimensional governance models.

Cost must be analyzed relative to its potential benefit. Expenditures that do not provide a societal “net benefit” are a subsidy to the inefficient and a disincentive to adaptive innovations as opined by two former SEC Commissioners who stated that “regulatory action aimed at eliminating every vestige of fraud in a given market would place such a heavy and costly burden of compliance upon issuers that investors would be safe but unable to achieve any meaningful return on their investments.”[2] Thus, regulatory proposals designed for risk-management regimes tend to be disproportionate when applied to uncertain instruments. Not so much from the capital expended but from the lack of commercial relevancy to the societal net benefit to be derived.

Effort represents the number of interested parties or amount of resources allocated to complete a transaction. Think of regulation as operational insurance. As Drivers’ Education reduces the cost of insurance for newly-licensed drivers; knowledge-driven consumerism is an efficient way to lower the cost of capital market governance.

To illustrate, there were three corruptive information errors that were causal to the subprime crash and required a greater regulatory effort:
1.     Mischaracterization of no-money down, NINJA—an acronym for “No Income, No Job or Assets,” mortgage-backed securities (MBS) that conflated risk and uncertainty to misprice subprime debt as AAA.
2.     Misuse of wrong tool (e.g., using hammer to drive a screw) where owners gave property rights to renters that created perverse foreclosure incentives.
3.     Misapplication of correct tool (e.g., using hammer handle to drive a nail) where uncertain[3] MBS portfolio tranches improperly used the standard deviation as a measure of variability. Attempting to hedge noncorrelative assets minimizes the value of both resources as the reliability of price information is corrupted.
Any effort that reduces informational deficiencies will have the added benefit of limiting the diversions from fundamental value.

Time: Commercial throughput processing speed as measured by time is directly proportionate to the level of systemic complexity. The function of time evidenced the largest increase during the transition from the Information Age to the Conceptual Age (Daniel H. Pink, 2005).[4] This requires a whole new mind-set that is built on innovation and big-picture capabilities as the society and economy move from high tech to high concept framed in a 3-dimensional context (think GPS vs. maps).

Three dimensional models drive economies of speed to expand enterprise parameters. Capital market policymakers, however, too often chose overly simplified responses. These responses were formulated within the context of a relatively narrow, two-dimensional perspective resulting in unintended consequences (i.e. Sarbanes-Oxley).

A 3-D conceptual change must take place in order for the US capital market to remain competitive in a global economy. Critical to governing a complex adaptive system is the timing and sequence of order to be processed.

To this purpose a 3-D regulatory Rubik’s Cube[5] is suggested to enable policymakers to mix-and-match individual cubes irrespective of market scenarios and different beginning regulatory configurations. Events and competitive responses can be modeled for effective and efficient governance. Dr. Tomas Rokicki Ph.D. and his team proved that any configuration of a Rubik’s cube could be solved in 20 moves or less.

Conclusion

Capital markets are complex adaptive systems with dynamical and non-linear properties. If there is complexity, then there is uncertainty. How can uncertainty be governed deterministically with one-size-fits-all regulatory metrics? If Citigroup’s financial supermarket could not cross-sell, can cross-regulation solve the problem of non-correlative information and related discontinuous market functions?

Managing randomness requires the reflexive integration of risk and uncertainty. To correct market ineffectiveness requires planned change to segment one-size-fits-all governance metrics into predictable, probable, and indeterminate underlying economic environments. To expedite market throughput requires 3-D models for processing leverage (3-D GPS vs. 2-D Maps). Before one can think outside the box requires thinking outside the square. Otherwise unplanned change, or chaos, sees risk become uncertainty resulting in the troubling, non-linear trend of larger and more frequent boom-bust cycles.



Authors

Stephen A.  Boyko is the author of "We're All Screwed! How Toxic Regulation Will Crush the Free Market System" http://readingthemarkets.blogspot.com/2009/10/boyko-were-all-screwed.html . He has over forty years of financial services industry experience that include formulating regulatory policy for the National Association of Securities Dealers (now FINRA) and providing a practitioner's perspective for the privatization of the former Soviet Union in corporate governance and regulatory development of the Ukrainian Capital Market. Contact: n2keco@bellsouth.net


Willard C. Rappleye Jr. has spent a lifetime as a financial journalist. He was the National Economic Correspondent for Time, Editor of American Banker, Founding Editor of Financier, the Journal of Private-Sector Policy, and Vice Chairman of FinancialWorld.

Endnotes



[1] This distinction between risk and uncertainty was made famous by economist Frank H. Knight in his seminal book, “Risk, Uncertainty, and Profit” (1921).

[2] Registration Under the Advisers Act of Hedge Fund Advisers File No.: S7-30-04 Dissent of Commissioners Cynthia A. Glassman and Paul S. Atkins http://sec.gov/rules/proposed/ia-2266.htm#dissent

[3] Uncertain investments lack cash flow and mark-to-market valuations.

[4] The governance evolution matrix below provides an historical context that reflects the factual realities for events that took place and how those historical events have influenced current decision making.

Age
Thought Dimension
Descriptors
Governance Metrics
Example
Agricultural
1
Linear, unidirectional
Progenitor, Malthusian
Dominoes

Industrial
1
Linear,
Binary (on-off)
Usage depreciates
Checkers
Information
2
Dynamic, Nonlinear, CAS
Usage appreciates
Chess
Conceptual
3
3-D GAAMA  (GPS vs. Maps)
Risk – uncertainty
Segmentation
Rubik’s Cube

[5]  The proposed “Regulatory Rubik’s Cube” see: http://www.sfomag.com/article.aspx?ID=1353&issueID=c  is built upon proven market and mathematical decision metrics to uncover principles of governance rather than simply profiling patterns of governance. While it is currently fashionable to criticize regulators, rating agencies, Congress, Government Sponsored Enterprises (Fannie Mae and Freddie Mac) Wall Street etc., we argue that “governance goofs” are more attributable to systemic structural obsolescence rather than individual shortcomings. Inefficient, under-regulation from two dimensional metrics that have to address three dimensional market realities lack processing speed. This is similar to using maps instead of GPS to navigate downtown traffic at rush hour. How efficient can that be?


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I want to thank the authors for their excellent article for the Blog.  They continue to publish articles and books of importance to the financial and regulatory sector.  Steve published the book "We're all Screwed!" and has been on active speaking engagements.  I am pleased to call him a friend and he has agreed to be an active contributor to the blog!

You can follow Taffy Williams on Twitter by @twilli2861 and you can email me with questions at twilli2861@aol.com and my company website is at http://www.ColonialTDC.com .

1 comment:

  1. “To correct market ineffectiveness requires planned change to segment one-size-fits-all governance metrics into predictable, probable, and indeterminate underlying economic environments. To expedite market throughput requires 3-D models for processing leverage (3-D GPS vs. 2-D Maps).”

    It would seem that you are not only thinking out-of-the-box, you are thinking out-in-the-space

    ReplyDelete