Nassim Nicholas Taleb introduced a new term into the lexicon of business forecasting, the “black swan event.” The metaphor comes from the apparent fact that, for some reason, black swans should not exist, but they sometimes do. In THE BLACK SWAN: The Impact of the Highly Improbably, Taleb expounds for 366 pages on what is, for the most part, a single idea: the normal (bell-shaped) distribution is pretty much worthless for predicting the likelihood of any random occurrence. Taleb augments this idea in various, occasionally entertaining ways, acquaints the reader with power law and “fat tail” distributions, and takes excursions through fractal geometry and chaos theory.
Taleb tells us he aspires to erudition, and he introduces the reader to plenty of “great thinkers” that history has failed to credit. You can come away from this book feeling that it is mostly about showing us how erudite Taleb is. For me, one of the key shortcomings is Taleb’s tendency, via style, to claim that we should accept his arguments on faith. There are plenty of concepts, especially involving numbers, that would benefit from concrete examples. There’s just a little too much “Take my word for it” in his writing. Still, if you’ve got time to kill, this is not an unrewarding read.
David Orrell tackles the very same subject–our inability to predict the future–in The Future of Everything: The Science of Prediction (which has a sub-sub title: “From Wealth and Weather to Chaos and Complexity”). For a mathematician, Orrel has an entertaining style and writes with clarity. This book is far more focused than THE BLACK SWAN, which is sort of meandering. The book is divided into three main parts: past, present and future. The past provides a history of forecasting, beginning with the Greeks and the Oracle at Delphi. The present considers the challenges of prediction in three key areas: weather, health (via genetics), and finance. Orrel did his dissertation research on weather forecasting, and after reading this book, I think you’ll agree that it’s a great case study for revealing everything we think we know about the “science of prediction.”
Orrel’s main point is that a key problem in prediction is model error (the basis of his dissertation), which far outweighs the influence of chaos and other random disturbances. In a nutshell, the complexity of these systems exceeds our ability to specify and parameterize models (models are subject to specification error, parameter error, and stochastic error). Weather is a great example. While there are only a few components to the system (temperature, humidity, air pressure, and such), the interactions between these components are almost impossible to predict. Another problem is the resolution of the model; conditions are extremely local, but it it very difficult to develop a model that resolves to a volume small enough to predict local conditions.
Orrell educates. The reader comes away with an understanding of the logic and mechanics of forecasting, as well as the seemingly intractable challenges. Orrell provides clear explanations of many important forecasting concepts and does a good job of making the math accessible to a general reader. There are a couple of shortcomings. Orrell gives only passing notice to agent-based simulation and similar computational approaches to complexity. And, in the third part of the book (the “future”), after spending the preceding two parts on the near futility of prediction (but for different reasons than Taleb), Orrell offers his “best guesses” for the future in areas such as climate change.
While I embrace the basic premises of these books, some new developments are cause for optimism. Economists using an agent-based model of credit markets were able to simulate the fall off the cliff that we’ve experienced in the real world, as just one example. While not truly “predictive,” these models can help us understand the conditions that are likely to produce extreme outcomes.
THE BLACK SWAN has its rewards, but The Future of Everything has far more value for the forecasting professional. As a chaser, you might try Why Most Things Fail: Evolution, Extinction and Economics by Paul Ormerod.
Copyright 2010 by David G. Bakken. All rights reservcd.