Brady on Speculation in Financial Markets

Food for thought from Michael Emmett Brady:

“There is a long 400–500 year history that demonstrates repeatedly, time and time again, that past and current speculation always leads to some kind of future economic problem.

Keynes recognized that financial markets, for the last 400–500 years since the introduction of modern, fractional reserve banking, exhibited the same speculative pattern over and over and over and over again. …. Obama, Bernanke, and Geithner … bailed out the Wall Street speculator crowd again, just as they were bailed out in the early to late 1980’s by Paul Volcker and late 1990’s–early 2000’s by Alan Greenspan. The result is that another bubble in the stock markets is being created. These financial bubbles are ergodic because the same pattern repeats again and again. New types of financial assets and financing are created by the banking industry. In the 1920’s, for example, these new financial assets were balloon payments for houses and margin account financing for stocks. The creation of these new types of assets is called securitization. The next step is debt leveraging. This allows speculators and speculating bankers to maximize their speculative debt financing. The growing bubble is fed by herding and copycat behavior that automatically leads to the creation of a larger and larger bubble. The next stage occurs as the bubble leads to a mania, which leads to a panic, which inevitably leads to a crash, which always leads to an economic downturn, recession, or depression of some sort. These kinds of events are stationary because they keep repeating over and over again. Their ultimate collapse can be predicted with a probability approaching 1. However, they are not normally distributed. One can’t use the normal distribution to describe the time series data in financial markets. The underlying processes are given by the Cauchy distribution.”
Michael Emmett Brady, September 18, 2009
http://www.amazon.com/review/R32PPK2MQ5SQUG

I find the idea that the repeated rise and fall of bubbles per se in capitalism to be ergodic worthy of further investigation.

Of course, one needs a strict definition of ergodicity and stationarity.

But another issue is how one defines “bubble.” It is entirely conceivable that a small or moderate bubble might in fact stabilise, reach plateau and then further bull or bear markets may follow, instead of simply deflating in a significant way.

Of course, if one wants to limit the definition of “bubble” used here to large, debt-fuelled bubbles, which really destabilise asset prices wildly, then the idea that the collapse of such bubbles “can be predicted with a probability approaching 1” is not so unreasonable, even though I assume that such a probability value would be what Keynes called non-numerical (Keynes 1921: 160), and cannot be understood as in the same class as a priori probabilities.

BIBLIOGRAPHY
Keynes, John Maynard. 1921. A Treatise on Probability. Macmillan, London.

Steve Keen on Minsky and Instability in Financial Markets

A short – but nice, concise and clear – talk by Steve Keen below on “Instability in Financial Markets: Sources and Remedies,” at the Institute for New Economic Thinking (INET) Paradigm Lost Conference in Berlin (held on April 14, 2012). There is also a post on Keen’s blog with a written version of the talk with graphs and a useful bibliography.

Early on (1.50) Keen confirms what I have recently said: that Minsky cannot be regarded as a neoclassical economist. It is also unfair to say that Keen simply dismisses all of neoclassical economics, for at 5.09 onwards we have an example of Keen citing good, higher-level empirical research by neoclassicals that confirms certain heterodox views, such as endogenous money theory.

Uncertainty and Non-Ergodic Stochastic Systems

The concept of uncertainty in economic life was used by Keynes in the General Theory (1936) and also in an article defending his new theory the next year (see Keynes, “The General Theory of Employment,” Quarterly Journal of Economics 51 [1937]: 209–223).

Paul Davidson notes the nature of uncertainty in the Keynesian/Knightian sense:

“Keynes’s description of uncertainty matches technically what mathematical statisticians call a nonergodic stochastic system. In a nonergodic system, one can never expect whatever data set exists today to provide a reliable guide to future outcomes. In such a world, markets cannot be efficient” (Davidson 2002: 187).

“Keynes … rejected this view that past information from economic time-series realizations provides reliable, useful data which permit stochastic predictions of the economic future. In a world where observations are drawn from a non-ergodic stochastic environment, past data cannot provide any reliable information about future probability distributions. Agents in a non-ergodic environment ‘know’ they cannot reliably know future outcomes. In an economy operating in a non-ergodic environment, therefore – our economic world – liquidity matters, money is never neutral, and neither Say’s Law nor Walras’s Law is relevant. In such a world, Keynes’s revolutionary logical analysis is relevant” (Davidson 2006: 150).

Certain types of phenomena in our universe are what mathematicians call non-ergodic stochastic systems. The concept of radical uncertainty applies to such systems, like medium term weather events, financial markets, and economies, and other natural systems studied in physics.

In these systems, past data is not a useful tool from which one can derive an objective probability score for some specific, future state of a quantitative variable in the system. Of course, such a system can still have trends, cycles and oscillations, both in the past and future. For example, stock markets certainly have cycles of bull and bear phases, but trying to predict the specific value of some stock x, say, two years from now with an objective probability score is not possible.

But the fundamental point is that it is still possible for a powerful agency or entity to reduce uncertainty in these systems, or at least in theory in some of them. It is entirely possible that in the future – with a far more advanced human civilization – we could use technology to control local, regional or perhaps even global weather.

And even today a powerful entity like the government can intervene to reduce uncertainty in the non-ergodic stochastic system we call the economy.


Is Climate a Non-Ergodic Stochastic System?

Does the earth’s climate system have the property of non-ergodicity? This question has occurred to me more than once, but I am actually unsure of the answer.

Some quick research suggests that climate models appear to make an ergodicity assumption about climate systems:

“Thus, it is perfectly valid to consider our climate a realization of a continuous stochastic process even though the time-evolution of any particular path is governed by physical laws. In order to apply this fact to our diagnostics of the observed and simulated climate we have to assume that the climate is ergodic. That is, we have to assume that every trajectory will eventually visit all parts of phase space and that sampling in time is equivalent to sampling different paths through phase space. Without this assumption about the operation of our physical system the study of the climate would be all but impossible.

The assumption of ergodicity is well founded, at least on shorter time scales, in the atmosphere and the ocean. In both media, the laws of physics describe turbulent fluids with limited predictability (ie, small perturbations grow quickly, so two paths through phase space diverge quickly) (von Storch and Zwiers 1999: 29–30).

But then what about longer time scales? If “the laws of physics describe turbulent fluids with limited predictability” on short time scales, what sort of predictability can they provide on medium or long term time scales?

Let’s assume, for the sake of argument, that long term climate is non-ergodic, in the way that a free market economy is. Does that mean all intervention would be useless and ineffective in such a system to affect the state of it? Does it mean that we are all doomed to (in a manner of speaking) live in a “free market” climate forever?

In fact, that does not follow at all. It is probably very likely that our future technology, when it becomes sophisticated and powerful enough, will be used by humans to intervene and control climate, e.g., by preventing ice ages.


BIBLIOGRAPHY

David, P. A. 2007. “Path Dependence, its Critics and the Quest for ‘Historical Economics,’” in G. M. Hodgson, The Evolution of Economic Institutions: A Critical Reader, Edward Elgar, Cheltenham. 120–144.

Davidson, P. 2002. Financial Markets, Money, and the Real World, Edward Elgar, Cheltenham.

Davidson, P. 2004. “Uncertainty and Monetary Policy,” in P. Mooslechner, H. Schuberth, and M. Schürz (eds), Economic Policy under Uncertainty: The Role of Truth and Accountability in Policy Advice, Edward Elgar, Cheltenham. 233–260.

Davidson, P. 2006. “Keynes and Money,” in P. Arestis and M. Sawyer (eds), A Handbook of Alternative Monetary Economics, Edward Elgar, Cheltenham, UK and Northampton, Mass. 139–153.

Keynes, J. M. 1937. “The General Theory of Employment,” Quarterly Journal of Economics 51 (February): 209–223.

Storch, H. von and F. W. Zwiers, 1999. Statistical Analysis in Climate Research, Cambridge University Press, Cambridge, UK and New York.