A tightly coupled supply chain may have many co-products and dependencies that rely on its inherent economies of scope or scale. Efficiencies gained from scale or stability create dependencies based on positive externalities. The more stable the underlying source of the dependency, the more dangerous its failing can be.
Did you know that a slow down in automobile manufacturing can impact the delivery of various life saving drugs? Neither did I. You can read about it here at the always interesting Blown mortgage blog.
This is a derivative form of risk that can't be modeled as the causal agents and feedback potential are to tough to model. It is a qualitative NP hard problem if you will.
Black swans are are caused by cascading failures between what are believed extremely non-linked systems. We usually think of derivatives in the first order.
An S&P 500 option or future derives its value from the underlying value of the S&P 500 equity values which of course derive their value from the longer term expected prospects of their earnings. Black swans are caused by 2 or more loosely coupled and viewed as independent events that link up causing extreme outcomes.
Current earnings estimates point to $30 worth of earnings for the S&P 500 which is currently priced at $835. That equates to a PE ratio of 27.8 or an effective yield of 3.59%. That yield sounds a little low to me. The historical average PE ratio implies an S&P fair value at 490. For those of you who think in Dow points that equates to a 4,400 DJIA.
The free PHaT tool may be helpful when thinking yield and trading ranges over the last 90 years. For those interested, the low PE during the depression was roughly 5.6 in June 1932. That equates to 167 for todays S&P 500 and 1,590 on the DJIA based on current earnings estimates. I am not saying these are my opinions or fair values for the equities markets, merely pointing out that they are within the realm of the historically possible. As a PM I think 98% of the time about risk.