This means that abrupt changes in prices or risk have a very low probability. The fallacy of this assumption has been clearly shown by Mandelbrot for stock prices, and it has been further demonstrated in many recent (and non recent) episodes for other asset prices and risk premia. Examples of the use of normal distribution in financial modelling would include the following: •  The most frequently used tool for risk measurement (VaR) frequently ignores "fat tail" risks. Many VaR measures are calibrated according to the expected loss of a portfolio under normal circumstances. Models with "fat tail" distributions are available, but seldom used, due to lack of reliable data over a sufficient period of time. •  Implied volatilities are usually extracted from option pricing, based on normal distribution. They are then used as inputs into trading strategies and models. As a result, the assumption of normal distribution widely "contaminates" the pricing, risk assessment and investment strategies across a whole range of markets and instruments. •  Finally, the pricing of many structured products is based on historical correlations among asset prices, with the assumption that those correlations are stable and do represent the ordinary state of nature. On the contrary, experience has shown that those correlations can change radically during a crisis, frequently collapsing to one, and take price movements to the extreme ends of the probability distribution. Procyclicality Many changes have been introduced in recent years to accounting and capital regimes in order to make them more risk sensitive.
One striking example is the pharmaceutical industry, where very innovative, but also potentially dangerous, products are put on the market with (almost) no accident. The reason, of course, is that those products themselves are subject to strict, and costly, testing and approbation procedures. This cannot be transposed to the financial industry, where innovation takes place under a different regime (with no protection for intellectual property). Nevertheless, some product control or standardization may contribute to reducing extreme risk. For instance, those countries where loan to value ratios were strictly enforced tend to experience less credit accidents than others. Those trade-offs may not be stable in time. For that reason, it is important that regulation and supervision become more responsive to changes in circumstances and the macro economic environment. This is the essence of the so called "macro prudential" approach to financial supervision. Implementing such an approach may prove very challenging. Early detection of incipient disequilibrium inside the financial system is conceptually difficult: no crisis looks like the previous one and the search for "early warning" indicators has not yielded fully convincing results. There is also an institutional challenge in bringing together different authorities with different mandates and approaches to financial stability. In the words of C. Borio "there is still considerable reluctance to calibrate prudential instruments more systematically from a macro prudential perspective".