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In other words, decades ago the derivatives market moved far beyond being a place to simply hedge risk, but has become to some degree, the world’s largest casino.

The major players in these markets have mathematical models, and computer systems that, in theory, will ensure that losses are contained.

For example, one Wall Street player’s computerized systems work on the mathematical assumption that exceptional downside risks could be managed 99% of the time. The question of course is what happens the other 1%?

More specifically Wall Street’s systems (in my experience) are programmed on the assumption that markets are fluid, and that as the value of an asset falls, that one can sell it at a pre-determined price, thus capping ones potential losses. The fear of course is that on “Black Monday” and other major market retreats, experience has shown that in a free fall attempts to sell at a given price is of little use when everyone is selling.

Orange County’s derivatives-based bankruptcy in 1994, the short-lived experience of Long-Term Capital, are examples of the huge inherent risks that parties can hold, without fully understanding the risk.

Clearly the entrance of private unregulated Hedge Funds, their massive capital bases, and their willingness to highly leverage their capital may as did Long-Term capital threaten the solvency of the entire system.

In the case of Orange County it is clear that those from the county were unaware of the risks, until long after it was too late to mitigate them.

Can further transparency in the marketplace better control the risks? Can crowd sourcing better predict future market behaviors?

There is a significant amount of transparency required for financial services institutions by Sarbanes Oxley (US )and Basel II (globally). A well implemented Basel II program was designed to prevent the types of tsunami that recently occurred with the mortage meltdown. However, Basel II is being inconsistently (content and timing) implemented across jurisdictions and risk models (a major input for Basel II) are generally considered proprietary as global banks spend (in sames cases misspent) millions in developing and maintaining them. It looks like the risk models require major rework, as the only investment bank to avoid the meltdown, Goldman Sachs, did not rely on models, but on a savvy executive to minimize the impact.

I spent my last two years at Citi as the Global Technology lead for the Basel II program. I have access to a number of Basel II SMEs, including two of my current associates. One of my major deliverables for Citi was a transparency and traceability framework, as these two powerful concepts are implied by the Basel II accord.