Up next, I'm pulling Nassim Taleb's The Black Swan off the shelf again. I started reading it thirteen years ago, but never finished due to starting a new job. As such, I'm going to start from the beginning here; hopefully this time I'll be able to read it through to completion.
Well, I finally finished Nassim Taleb's
The Black Swan, and it was just as fascinating as I remembered.
While the more mathematical aspects of the book were beyond me (even when I gritted my teeth and forced myself to read them), the overall thrust of the book is written very clearly, and no one needs to be an expert in math, economics, or risk management in order to understand the lessons here. Said lessons are, to quote the book's subtitle, the impact of the highly improbable.
What that means is that there are various aspects of life where unexpected, and highly improbable, events can have massive repercussions (positive or negative), and that (more importantly), attempts to forecast these improbable events (via modeling) is quite often a fool's errand. And yet, in many of these areas we lionize attempts to create such models, even when they're repeatedly shown to be unable to predict the most consequential events.
In this regard, Taleb is particularly scathing towards a large swath of economists, noting that their predictive models of risk management have failed to forecast any number of disasters (and that those lone voices, howling in the wilderness, who
did see those disasters coming weren't using models to draw predictions about how things would unfold). The result is that many people were using "Platonified" (i.e. theoretical) models which didn't match reality, were shocked and horrified when the reality didn't match those models, and then when right back to using them after the crisis had passed.
One of his best examples of this is how we rely too much on the past being a predictor of the future, since while that's
often correct, the times when it's not can potentially change everything. He illustrates this by talking about a turkey who is fed everyday for one thousand days by a farmer. The turkey has a great deal of past data to corroborate that tomorrow, the farmer will feed him again, and that this past-predicts-the-future data grows stronger as time passes; by the thousandth day, the turkey feels extremely confident in his predictions.
But what the turkey doesn't know is that tomorrow is Thanksgiving Day, and the farmer is coming out not with a bucket of feed, but with an axe.
Far better, Taleb tells us, to try and come up with robust systems which can withstand unexpected shocks (and is poised to take advantage of them when they're positive events, rather than negative ones).
Needless to say, this is going to make me take a good hard look at my stock portfolio, since I don't want to become the economic equivalent of a turkey.
