Five systems laws and what they tell us about the financial crash: Part 2

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Five systems laws and what they tell us about the financial crash: Part 2

In a previous blog, we looked at 2 out of 5 systems laws, and applied them to the financial crash. In this post, we look at 3 further laws, and what they tell us about the nature and causes of the crash.

  1. Redundancy of Potential Command Principle: In any complex decision network, the potential to act effectively is conferred by an adequate concatenation of information

Warren McCulloch was the polymath who did the initial breakthrough modelling of neural networks and he also came up with this principle. You can interpret it relatively simplistically as “information is power”, but more subtly what it states is that without an adequate set of information, it’s impossible to act effectively in a complex system. Without an adequate set of information the consequences of your actions will be unpredictable. In the context of the crash, there are two major implications, the first is that people trying to stabilize the system as it slid into collapse did not have an adequate set of information and so could not act effectively. The second is that in the run up to the crash, information was unevenly distributed and relative advantage went to those who had most. At the core of the sub-prime game was the disguising of risk as it was sliced, diced and recombined until the level of risk was hidden from view. In that context – the time leading up to the crash, the difference between having the information on how a complex financial instrument actually worked and not, was the difference between winning and losing.

  1. Adams 3rd Law: A system composed of the lowest risk components available will be a high risk system

Adams law is an insidious and counterintuitive piece of thinking that turns on its head much conventional thinking about risk. We tend to assume that if we de-risk all the components in a system that will reduce the risk overall. But it doesn’t. The reason is that if each component is optimised to reduce the risk that it will itself fail, then de-risking the internal operations is at the expense of the risks that come from the interdependences between components. Just as John Donne pointed out that no man is an island, so no component in a system is an island unto itself. In the crash, each component of the financial system had been designed and the risks of each had been calculated and factored into the design. Each component, each financial instrument and product had been designed to maximise the return to the financial institution and the risk inherent in the product balanced against the reward. Which is why there had been so much effort put into mitigating and hedging the risks associated with sub-prime and other exposed loans. What hadn’t been calculated (because it wasn’t any individual institution’s problem) were the risks that each component posed for other components. The risks of interdependence, the risks to the system as a whole. And it was those that brought the whole edifice crashing down.

  1. Relaxation Time Principle: System stability is possible only if the system’s relaxation time is shorter than the mean time between disturbances

Systems can absorb shocks if they are given enough time to recover. As shocks hit a complex system they ripple through it like ripples on a pond and the after effects can last a surprisingly long time. The relaxation time of a social economy is measured in decades, the relaxation time of a global economic system is unknown. Where a system is hit by another shock before it has recovered from the previous one, it doesn’t ever stabilise, it stays in a state of perpetual instability and in that state it is more vulnerable. Even small shocks can have a disproportionate effect, and the impacts, whether large or small are less predictable as they can combine with the after effects of previous shocks. For the economic system, the relaxation time is unknown, but that is itself an indicator that it may be permanently unstable, subject to cycles of disruption from which it never really recovers. So … Looked at through the lens of these five systems laws, the financial crash is no surprise. Together they form a picture of how and why it happened and more chillingly how likely it is to happen again. They also provide some clues as to how the probability of a repetition could be reduced: regulators that have a regulatory model of the system that actually captures the key aspects of its dynamics and can dampen the gain on its runaway growth when that threatens to go out of control, better access to information and especially understanding and management of the risks in the system of interdependence. Scarily, most of the effort seems to go into recreating the conditions that led to the crash, because in the short term that provides growth. This has all the characteristics of addiction, but without access to alcoholics anonymous. There is no global drying out clinic for economies.