An equation that can reliably predict crashes in financial markets and some types of epileptic seizures has been identified in a joint-study by Sussex University in the UK, and Charles Sturt University, Australia.
‘Dynamical systems’ – systems featuring complex interactions between large groups of interacting elements seen in, for example, economic structures and processes in the brain, were analysed to pinpoint transition phases – the moment before a system ‘crashes.’
Published in Physical Review Letters, the study shows how information dynamics could be used as a predictive tool. By accurately pinpointing the moment of disorder in a system, researchers believe that financial market crashes, some forms of epilepsy, disorder in climate systems and even malfunction in the human immune system could be potentially prevented.
Using computer simulations and mathematics, researchers showed how a measure of information flow reaches a peak known as a ‘phase transition’ just before a system system moves from a state of order to disorder and ‘crashes.’
Phase transitions are common in many systems and preceding ‘crashes’ are therefore highly significant Previously, methods of predicting such phase transitions have failed, peaking at the point of transition and thereby making prediction impossible.
Dr Lionel Barnett, Postdoctoral Research Fellow at the Sackler Centre for Consciousness Science comments on the recent discovery:
The key insight in the paper is that the dynamics of complex systems – like the brain and the economy – depend on how their elements causally influence each other; in other words, how information flows between them. And that this information flow needs to be measured for the system as a whole, and not just locally between its various parts.”
To measure this information flow requires a way to mathematically represent the extent to which parts of a complex system are simultaneously separated and pulled together. A way of characterizing the phenomenon of phase transitions has puzzled the scientific community for decades.
In 1925 Ernst Ising solved the problem to represent a model of magnetism for his doctoral thesis. In the more recent discovery, the research team of Sussex and Charles Sturt University demonstrated for the first time that their measure did what many have tried to do since Ising’s model – reliably predicts phase transitions in standard systems.
Professor Anil Seth, Co-Director of the Sackler Centre, comments on the scope of the discovery:
The implications of the work are far-reaching. If the results generalise to other real-world systems, we might have ways of predicting calamitous events before they happen, which would open the possibility for intervention to prevent the transition from occurring.”
He adds: “For example, the ability to predict the imminent onset of an epileptic seizure could allow a rapid medical intervention (perhaps via brain stimulation) which would change the course of the dynamics and prevent the seizure. And if similar principles apply to financial markets, climate systems, and even immune systems, similar interventions might be possible. Further research is needed to explore these exciting possibilities.”
Sussex University Press Release: Scientists identify a mathematical ‘crystal ball’ that may predict calamities
Physical Review Lettters: Information Flow in a Kinetic Ising Model Peaks in the Disordered Phase