From an article on financial modeling:

“Modeling derivatives is of particular importance due to the relative size of the derivative market when compared to the real economy. If we examine the Bank of International Settlements (BIS) estimate of “Amounts outstanding of over-the-counter (OTC) derivatives” in December 2010, this amounted to US$601,046 billion. To the World Bank estimate of World Gross Domestic Product (GDP) for 2010, the volume of financial transactions in the global economy is 73.5 times higher than nominal world GDP.

In 1990, this ratio amounted to “only” 15.3. Transactions of stocks, bonds, and foreign exchange have expanded roughly in tandem with nominal world GDP. Hence, the overall increase in financial trading is exclusively due to the spectacular boom of the derivatives markets. In the final analysis, the mathematical modeling of this system of obligations is an imperative for the world economy’s well-being.”

Basically, what this means, is that derivatives have engulfed our economy and our very existence relies on trading robots, stochastic integrals and Brownian motion. A very fragile situation which nobody today is able to grasp or control. The system is running on autopilot and nobody know how the autopilot works.

Now, we all know that one salient characteristic of derivatives is their high complexity. This is because they have deliberately been designed to be complex. There are numerous reasons why one would want to design a very complex financial product. One of them is to fool investors. However, there are very important implications deriving from the immission of highly complex financial products into the global economy:

1. Highly complex products have highly complex dynamics which are difficult to capture with conventional math methods. Monte Carlo, VaR, etc. are all techniques that not only belong to the past, they have contributed significantly to the crisis. This means they cannot be used to find a cure. If smoking causes cancer, smoking more will not make it go away.

2. A product may be said to be complex, at a given moment in time, but, precisely because of the complex dynamics of derivatives, this complexity is never constant. It changes.

3. If a product is said to be complex, it means that someone *must *have measured its complexity. Otherwise, how can such a claim be sustained? Serious science starts when you begin to measure.

4. The biggest problem with derivatives is that of their rating. Since their real dynamics is essentially unknown (or deliberately masked), attempting to rate them is futile. This is where the Credit Rating Agencies failed when they triggered the financial meltdown. On the one hand they assigned investment-grade ratings to products which where known to be toxic, on the other hand their outdated methods of rating were simply not applicable to super complex financial products.

This brings us to the main point of this article. Our economy looks more or less like this:

and we need to fix it before the system collapses. As you read this short article, every minute billions are being traded in hyperspace and the pile in the picture is growing. What can be done? There is no simple recipe. However, what *must *be done is this:

1. Start to measure and monitor the real complexity of the financial products that are out there. There exist tools today to do this. One is here.

2. Classify, rank and rate the complexity and resilience of derivatives. Establish maximum allowable levels of complexity and minimum allowable resilience of financial products. Products with low resilience contribute to making the system (economy) more fragile.

3. Once the most complex (dangerous) derivatives have been identified, they should be withdrawn progressively from circulation.

More soon.

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