#RISK PROBABILITY GAME DRIVERS#
#RISK PROBABILITY GAME DRIVER#

The tightrope performer in the image at the top of this blog is risking 100% of his life, not 1% or 1/10% of it. If you visit Lehman Brother’s website today, more than a month after the bank’s plunge into bankruptcy, you can find the following words: The effective management of risks is one of the core strengths that has made Lehman Brothers so successful”. But the very systems the banks created to protect themselves are at the heart of the financial meltdown. The author writes” Wall Street thought it had risk all figured out. These two estimates alone differ by a factor of 50%.Īnother eloquent example is from a FORTUNE article (by Nomi Prins, October 28, 2008) with the title “The Risk Fallacy”. The “total damages/costs” of Katrina were $ 140 Billion (2012 dollars). The total damage from Katrina is estimated at $92.6 billion (2012 US dollars). How can one possibly make an a-priori estimation of the costs (or consequences)? How many people will perish? How many families will lose their homes? What will the impact on the economy be? How much will stocks fall? How long will it take to recover? What was the probability of 9/11 a year before it actually happened (we now know that it was 100%!)? What have the consequences been? Can any of this be estimated a-priori in a significant manner if even after the fact it is difficult to measure the costs of catastrophic events? What, then, is the real and practical value of similar calculations?Īs an example, consider hurricane Katrina. Consider earthquakes, flooding or terrorist attacks. In the case of more complex situations, the above equation is even more disputable. The damage is the same regardless of the probability you may conjure up. So, if you get caught by radar, the cost is 100 Euros if p=0.1, or 0.001 or even 0.0000001.

For you, statistics begin the moment you start the engine. If YOU get caught, you get caught independently of the probability suggested by past statistics. In this simple example, the cost was easy to estimate.

#RISK PROBABILITY GAME DRIVERS#

Try arguing with a policeman that your fine should be 10 Euros! Suppose that drivers are obliged to carry on board a regulatory capital for fines (something similar to Basel II or III). In other words, if you drive fast, you’re risking a 100 Euros note, not a 10 Euros one. If you get caught, you pay 100 Euros, if you don’t, you pay nothing. The above formula would suggest that anyone who is speeding is risking 1/10 X 100 = 10 Euros.

#RISK PROBABILITY GAME DRIVER#

It is known from statistics that on that portion of the motorway on average one driver out of ten gets caught. If you’re 20-30 km/h above the limit, you can expect a fine of around 100 Euros. Suppose that in a certain portion of a motorway a radar is mounted with the intent of catching those who enjoy speeding. very rare events with dramatic consequences). Imagine the following example which was discussed at a recent conference on the so-called Black Swans (i.e. However, the most important flaw is hidden and it is conceptual. Even after a catastrophic event it is difficult to estimate the total damage and cost. Estimation of the costs/consequences of these events. Since this factor multiplies the “cost” in the above equation it is of paramount importance.Ģ. Rare events have very low probabilities and these are extremely difficult to estimate due to the fact that the sample of available data is very small (what is the probability of an event similar to 9/11?). Estimation of probabilities of future events is very difficult (while it is considerably easier when talking of past events). This definition is flawed because of two fundamental reasons, which the formula itself suggests very eloquently:ġ. Risk = the Probability of something happening X resulting Cost/Consequences (image from Probably the most frequently used definition of risk is this one:

Risk probability game