Tag Archives: IPCC

Bits and Pieces – 20180202, Friday

Commentary: I came across a Canadian blogger, Faith Goldy, with an extremely direct commentary on sex education in Ontario:

Too many PhDs and Not Enough Common Sense

Thousands of investors, both professional and amateur, build models of markets, hopefully with sufficient predictive power to make money – or avoid loosing too much. To validate their models, they back-test them. That is they run the model over a number of previous years of data to study the accuracy of their models’ predictions over the time frame chosen.

The most celebrated case is that of Long-Term Capital Management L.P. (LTCM). Founded in 1994 as a hedge fund, it counted 2 economic Nobel laureates on its staff as well as dozens of PhDs in math, physics and economics. They produced spectacular returns based on their models and strategies that were highly leveraged to produce these outsized results. Then in 1997 and 1998, the Asian and Russian financial crises produced adverse conditions of a nature that their back-testing had failed to include. A story we recall reading but could not find was that their data set stopped just short of the 1987 market crash. Had they gone back further, the outcome may have been radically different. As it was their high leverage worked against them, bankrupting the company and threatening the stability of thew entire financial system. Only Fed intervention saved it.

With this background we are perplexed that we have not heard about back-testing of climate models. The importance of such may be understood in the butterfly effect. Based on a set of mathematical equations developed by Edward Norton Lorenz, an American mathematician and meteorologist, and a pioneer of chaos theory, this effect also called the Lorenz attractor, has characteristics that show up widely in natural systems and particularly climate systems. The idea is that where your model goes depends on what set of initial conditions you use. In some systems the results of very small changes in the initial parameters create widely divergent results.

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