Calculating Forecasting Odds: Think Like a Stockbroker

In a Take Part article (here), Amy Luers, Director of Climate Change at the Skoll Global Threats Fund, takes on the issue of variability and forecasting. Leurs makes the argument that global temperature forecasting and stock forecasting have similar problems with statistical variability. Working with Leonard Sklar, Professor of Geology at San Francisco State University, Leurs developed the two graphs above. On the left is the Dow Jones Industrial Average (DJI, my forecast for the SP500 is here), on the right is Global Temperature (my forecast is here). The bottom left graph shows the odds of making money if you invested in any random year (1913-2010) and stayed in the stock market for up to 50 years. After about 35 years of staying invested, there is a 100% chance of making money. On the right is the same graph for global temperature. It takes a little longer, but after 45 years you have a 100% chance of finding a temperature increase. Notice that in both cases, if you look over only brief periods, the odds are closer to 50-50.

The graph above is from page 381 of Nate Silver's book The Signal and the Noise. In 2007, the notorious Scott Armstrong, Professor of Marketing at the Wharton Business School, made a $10,000 bet with Al Gore that Armstrong modestly called "The Global Warming Challenge." Armstrong and his colleague Kesten Green, an Australian Business School Lecturer,  have argued (here) that Global Temperature is too variable to forecast. The Armstrong-Gore bet was to be resolved monthly. Predicting "no-change," Armstrong argued from the data above that he had won the bet.

Given the Luers-Sklar data, we understand why Armstrong made this bet and we also understand why Al Gore never took the bet. Five years is far too short a time to determine whether temperature has increased or whether, for that matter, the stock market has made money. Having published "Principles of Forecasting, [...a book that...] should be considered canonical to anybody who is seriously interested in the field [...of forecasting]" (these are Silver's words), Prof. Armstrong should have known better.

The basic problem with Prof. Armstrong, his "Global Warming Challenge" and his forecasting principles (I have commented on the principles here) is summed up by a quote from Nelson Mandela "Where you stand depends on where you sit" and Prof. Armstrong sits in the business school and is paid to market business activity as having little impact on the environment. All the forecasting principles and outrageous bets in the world will not cover up this canonical conflict.