TABLE OF CONTENTS:
Today’s note is part of our ‘SCENARIOS’ series, and is intended to provide a
theoretical conceptual framework around our previous notes on
market fragility
, where we argued that an unstable equilibrium in financial markets is brought about by
positive feedback loops
between public and private investors, exposing markets to the
risk of a systemic risk escalation
. Our upcoming Investor Presentation will discuss to specific points of critical transformation and upcoming regime shift for markets, pointing to the
generic early warning signals for chaos outburst.
What It Means To Be On The ‘Edge Of Chaos’
There is a magic space between order and chaos, a phase transition zone where a system reaches criticality, and can suddenly and abruptly morph into a whole new contrasting system. It is a place where its resilience may get weakened to the point where disorder and randomness prevail, and lead into a totally different environment, for an entirely new equilibrium. If the system degrades at the edge of chaos, it can then drift away from an ordered predictable regime into a chaotic unpredictable regime. It is the space, hypothesized to exist by scientists, where snowflakes suddenly accrete to form avalanches at some critical tipping point, where fluid crystallize, where desertification rapidly oversets a green valley, where a volcano breaks into eruption, a forest burns itself out, a pandemic breaks loose.
In an intrinsically inter-disciplinary endeavor, complexity scientists from fields such as mathematics, biology, physics, ecology, psychology theorize of the existence of this mysterious space, a theoretical zone, which sits in between order and disorder, between symmetry and randomness. "You’ve got randomness, and you’ve got order. And right between them, you’ve got the phase transition,” in the words of biophysicist John Beggs of Indiana University.
His analogy of a pile of sand is illustrative. It was pointed to us by one of our readers, who we thank for that. ‘Sand grains are dropped one-by-one from a single point. For a long time, nothing much happens: a conical pile slowly accumulates. Eventually, however, it becomes so steep that the addition of just one more grain can trigger a miniature avalanche, though not in a predictable way. Avalanches can be small or large, and sometimes they don’t happen at all. Just before the pile enters its avalanche-prone state, said Beggs, it’s poised at criticality. From a biological perspective, the trick is to harness the capacity for small perturbations to produce large effects without entirely entering that avalanche-prone state, in which perturbations would soon become overwhelming. Researchers studying such behaviors sometimes refer to this as the ‘edge of chaos.’
There is nothing intrinsically negative about stationing at the edge of chaos. Edge of chaos is not to be seen as necessarily a negative zone to be in. If anything, the interaction between chaos and order builds resilience. The criticality of the balance between order and deterministic chaos is an optimal evolutionary solution for systems that need to balance order and stability with flexibility and adaptability, in harmony. Complexity theorists talk of ‘evolvability’, as the capacity of a system for adaptive evolution. Evolution happens at the edge of chaos, the boundary between ordered and entropic regimes. However, such evolution is sometimes a major jump, a deep discontinuity, when the delicate balance between stability and flexibility is suddenly lost. It happens when feedback loops change in ways in which resilience is lost, making it dangerous to be there at the edge, poising for critical transformation, into chaos and then an alternative stable state.
Also, not all transitions are negative. Some systems tend to order, not disorder. What matters though is the identification and the awareness of criticality, as a state where large swings can follow swiftly, by the very nature of the state. It is an essential element of resilience management.
The sensitivity of a complex system to parameters is well known. Chaos theory focuses on the ‘deterministic chaotic behavior’ of dynamical systems that are highly sensitive to initial conditions: ‘chaos is when the present determines the future, but the approximate present does not approximately determine the future’, in the words of the theory pioneer Edward Lorenz. The butterfly effect describes how a small change in one state of a deterministic nonlinear system can result in large differences in a later state, or as is famously rephrased how ‘a butterfly flapping its wings in Brazil can cause a hurricane in Texas’.