"Banks and hedge funds are in control of a ridiculous amount of the world’s wealth. They also trade irresponsibly large quantities of complex derivatives. They slavishly and unimaginatively copy each other, all holding similar positions. These contracts are then dynamically hedged by buying and selling shares according to mathematical formulae. This can and does exacerbate the volatility of the underlying."
He also points out that too much money will always chase too few products because large, undiversified bets with other people's money will always provide the most tempting returns for money managers.
In this vein, I highly recommend Richard Bookstaber's text "A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation" (Wiley, 2007). In his concluding chapter, entitled "Built to Crash?", he observes:
"...the positive effects of innovation come a a price. Innovation increases complexity. Many innovative instruments are in the form of derivatives with conditional and nonlinear payoffs. When a market dislocation arises, it is difficult to know how the prices of these instruments will react. Innovation and mechanical efficiency have also increased complexity by pushing markets to become more interconnected...The combination of tight coupling and complexity is a formula for normal accidents--accidents that are all but inevitable as a result of the structure of the system." (p. 255-256).
This line of reasoning has powerful implications for risk management. We tend to think of risk in terms of standard deviations and normal distributions. Financial systems, however, possess fat tails of returns--and increasing complexity may only increase this "fatness". We can calculate the historical odds of a market crash, but will such models accurately capture risk in systems of increasingly tight coupling?
Paul Wilmott concludes:
Banks and hedge funds employ mathematicians with no financial-market experience to build models that no one is testing scientifically for use in situations where they were not intended by traders who don’t understand them. And people are surprised by the losses!
If sophisticated mathematical models can't capture risk and complexity, can we expect the gut hunches of discretionary traders to do better? There's a lesson in all this, and it seems to be: The odds of catastrophic financial outcomes are greater than we estimate. Even when we think we're diversified, the tight coupling of complex, interwoven financial systems ensures that, at times of stress, correlations will tend toward one or minus-one.
Looking for more reading on complexity and how we are "fooled by randomness"? Check out Nassim Taleb's website and this excellent summary of his ideas. They provide a sobering perspective on how we don't really know what we don't know.