Chaos, Markets and Governance…Proof?

Let’s dwell on a fundamental aspect of Markets, pricing. This interest was triggered by reviewing Keynes’ equation for liquidity traps, and the rate of change of the cost of short term money, wherein the cost of money is expressed as interest, which is controlled by Central Banks.

An interest rate is a velocity. Velocities measure changes over time. Traveling in a car, velocity is the number showing on the speedometer. A power dam might measure the amount of water it releases per year– possibly in millions of cubic meters per year. Interest Rates are the Cost of Money, or profit from money, depending if one is a borrower or lender.

This now raises one more question: How is the model of interest rate changes, and thus all process changes, related to investor behavior in a market?

Let’s examine the expected cost (cost set by the Central Bank funds) of money’s behavior in a market, where Capital I is the interest rate, and we introduce introduce two other factors, fear (F) and greed (g) into the equation. F is defined as the fear of loss of wealth, while g is defined as the desire for ever-increasing accumulation of “riches”.

f, f1 and f2 remain in defined form, as abstract functions, t0 is now, t1 is some time in the future and k the expected Central Bank’s (a regulator) interest rate increase at t1.

Then we’d get: It1= It0+ k + f1( F, g )

Which is interesting because it forces f1(F, g) to be zero if there is no change in the expectation of changing central bank interest rates, and f1(F) + f1(g) = 0, that is the expectation from fear and greed at t1 is zero.

When (F, g) = f2( It2 ), there is the expectation of interest rate change,

the equation becomes: It1= It0+ k + f1( f2( It1 ))

and, assuming fear and greed are non-linear (insert hollow laugh here), we have a non-linear equation with feedback, as the basis for future interest rates at some discrete interval, and such non-linear feedback equations are the basis of chaos theory.

Let’s apply this to a non-regulated market, such as the stock market, where P is the price of a stock now at some period t.

Pt1 = Pt0 + f1(F, g ), or
Pt1 = Pt0 + f1( f2( Pt1 ))

here we have no regulator, “k” which could be used to adjust the (F, g) value to a manageable level.

One can conceive of three dimensions, time, fear and greed, along with their rates of change, which would make a model of the economy potentially a chaotic surface.

Fear and Greed need limits (governance) so the fear is minimized and Greed (gain) controlled within these limits. Any non-linear system CANNOT be controlled with linearly applied feedback. Sooner or later, the system will exceed the restraints applied by the feedback, and the system will CRASH. It’s simply a matter of time. Non-linear feedback doesn’t work either, because one has to be able to predict the amount of feedback which will keep the system in control. Non-linear feedback applied to a non-linear system will, at some point, fail to provide the correct amount of control to the system, and the system will fail (crash).

In other words, regulation and control can mitigate the degree of the failure, as Glass-Steagall did, but will not eliminate all crashes. Regulation and control may mitigate both the degree and amplitude of failure (crash), but there will be failures.

If you want to visualize the problem, find yourself a pendulum of some sort, and balance it on your finger, heavy side UP. Now, keep it balanced. The inverted pendulum is a famous example of a system which is difficult to balance, and which, once a certain point is reached, cannot be restored to balance. The pendulum falls. Chaotic systems are like that. Money flow in an economy is another example of a chaotic system. As long as the changes are small, people will tend to think of money flow as a linear system. Sooner or later, based on the input variables, including fear and greed, the money flow changes catastrophically, as it did in 2006-2008. Those changes are not small, and, if people think about them, they can serve to remind them that the system is NOT linear; it’s chaotic, because of the multiplicity of inputs/influences on the money market.

How ISDS (The Investor State Dispute System) emphasizes Gresham’s dynamic – bad drives out good when Fear is eliminated

Now that we’ve demonstrated proof markets are fundamentally chaotic, it’s worth noting the effect that the trade treaties President Obama is pushing will have on the markets. Note that due to the inclusion of ISDS in these trade treaties, supra-national (above countries) or extra-national (apart from countries) companies would be able to sue national governments for “loss of profits” if the signatory countries agree to this clause. The effect of this clause is to remove any cause for fear by these companies, because they can do anything they like, and if a signatory country seeks to rein in their behavior by passing a law which restricts them, they simply turn around and sue that country for loss of profits, in a private “court” which is controlled by the organization enforcing the treaty.

Restraint and regulation vanish, and the likelihood of another catastrophic market collapse increases sharply. Greed can be controlled by taxation (except as pertaining to ISDS and TPP, TISA, and TAFTA. When corporations lose Fear, because they can litigate for coverage from signatory countries, only Greed remains to imposes limits on their behavior.

Because government is both unwilling and unable to provide good regulatory infrastructure, corporate bad behavior will multiply until the damage becomes too large to ignore. Then, countries will have to repudiate the treaty or become permanent sources of funds for corporations which behave badly.

What will investors in these companies do? Because their earnings will, over time, become more and more polluted by “lack of fear,” investors will adopt that fear, and be ready to dump their interests in these companies at any news; that is their stock prices will increase in volatility based on the excess of corporate greed (insured profits) and investors fear (lack of sustainable earnings growth).

Isn’t it interesting to think about how distasteful Obama’s “legacy” legislation efforts are going to become over the next few years, if they succeed? Another unintended consequence, brought to you by people who like greed and dislike fear, without realizing that fear has value in restraining bad or unsafe conduct.

And relying on market self governance is provably an invitation to chaos.

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  • These equation may for the basis of computing the fear and greed, but fear and greed need measurement system and the function, f1 anf2, need elaborating.

    Fear might be measured by social media, with possibly some keywords. A postulate would be that a fear curve would be a typical life/death curve, and it initial gradient an exponent in the equation a measure to the degree of the fear.

    The greed curve, again could be a life death curve, but where would it become evident? “Spontaneous” contributions to Politicians? The rate at which politicians become adhered to a position?

    It certainly involve some me measure of money, driving the greed.

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