Monthly Archives: June 2009

Question for today: What do you get when you run Monte Carlo software back in time?    Answer: You get closer and closer to the wreckage of Air France Light 447.   The U.S. Coast Guard’s search for the crash site of the doomed Air France plane was the first major test of its "reverse-drift" […]

Six years ago when Dale Addison was speaking to a group of engineers and trying to pitch "artificial intelligence"–meaning neural networks someone in his audience asked him if it was true that a neural network had once mistakenly classified a T-62 tank as a Volkswagen.  Although the incident had occurred years before, Addison seems to […]

As anyone who has read a few of my blog entries knows, probably all too well, I believe that Monte Carlo simulation has been unfairly maligned for its role in derailing the economy.   This month in his column for Seeking Alpha, Geoff Considine made this point a lot better than I’ve been able to […]

Over the past three years I’ve been tracking an uptrend in risk analysis in what might seem an unlikely field, wildlife conservation.  But on further thought, this makes perfect, straightforward sense. At-risk animal populations could use some analytical help sorting out the live-or-die questions.    The first benchmark occurred when the World Conservation Union began […]

Kurtosis is a statistical measure of a random process that is often used, but perhaps less widely understood. This blog mentions a couple of key issues and misunderstandings about kurtosis in a risk assessment model. A high kurtosis figure is sometimes described as being associated with a distribution that has “fat tails”. However, by simply […]

A recent article entitled “When Monte Carlo analysis meets a black swan” in Investment News addresses the criticisms Monte Carlo simulation has received for “missing the meltdown.”  The author, Moshe A. Milevsky , notes that people typically seek a single number “answer” from a Monte Carlo simulation, such as the probability of meeting a single […]

Yesterday I had an interesting conversation with a colleague who is a Six Sigma and DFSS Master Black belt who just returned from Europe where he conducted a Black Belt Training session. He pointed out how much different the Europeans are to the Americans when it comes to their expectations and commitment they show for […]

An earlier blog on Best Practice Principles in Excel Modelling generated quite some interest, as well as demand for more details on some of the points made, especially those concerning the use of named ranges risk asssessment models in Microsoft Excel. In the earlier posting, I had simply stated that (in my opinion): “Named ranges […]

It must be that all the gloom in the financial sector is bringing out the gallows humor in me, because I had to laugh at this follow up on the "war games" stress testing in the British banking sector. First the Financial Times reported that risk analyses stress tests applied by regulators to British banks […]

A recent article in Bank Investment Consultant criticized the risk analysis method of Monte Carlo simulation for not taking into account extreme events like the stock market crash. According the article, a Morningstar executive states that the “bell-shaped curve that Monte Carlo simulations use” artificially assigns the probability of what happened as zero.  Furthermore, the […]