The risks of interconnectedness

This is a tremendously interesting article in SEED Magazine, titled "On Early Warning Signs", by George Sugihara that draws on the author's background in biology to depict some of the limitations of the modern tendency to use linear systems (plus perturbations) to model fundamentally non-linear systems. Among other things, non-linear systems show high levels of interconnectedness that tends to fluctuate (technically heteroskedasticity), which makes predicting their behavior using linear models very difficult.

The author further notes:

"Leading up to the crash, there was a marked increase in homogeneity among institutions, both in their revenue-generating strategies as well as in their risk-management strategies, thus increasing correlation among funds and across countries—an early warning. Indeed, with regard to risk management through diversification, it is ironic that diversification became so extreme that diversification was lost: Everyone owning part of everything creates complete homogeneity. Reducing risk by increasing portfolio diversity makes sense for each individual institution, but if everyone does it, it creates huge group or system-wide risk. Mathematically, such homogeneity leads to increased connectivity in the financial system, and the number and strength of these linkages grow as homogeneity increases. Thus, the consequence of increasing connectivity is to destabilize a generic complex system: Each institution becomes more affected by the balance sheets of neighboring institutions than by its own."

An interesting analogy drawn from nature, this time from plants and pollinators:

"[T]he same hierarchical structure that promotes biodiversity in plant-animal cooperative networks may increase the risk of large-scale systemic failures: Mutualism facilitates greater biodiversity, but it also creates the potential for many contingent species to go extinct, particularly if large, well-connected generalists—certain large banks, for instance—disappear. It becomes an argument for the “too big to fail” policy, in which the size of the company’s Facebook network matters more than the size of its balance sheet."

Very interesting stuff.