2019 Forecast: Predictions Will Be Wrong, Random or Worse
Every year, the prognosticators come out of hiding. You have to wonder why they bother, given their record.
Bloomberg, December 7, 2018
‘Tis the season, when strategists and analysts (metaphorically speaking) sharpen their pencils to jot down their most heartfelt predictions for the coming year. Full of bravado and confidence, they explain what stocks to buy, whether a recession will come along, what the Fed is going to do, and when the market is going to crash. (Truth be told, that last one is less of a prediction these days and more of a case of real time reporting, jk).
These are, for the most part, exercises in futility. All analysts belong to a species which has repeatedly shown itself to be terrible at predicting very much beyond what they might like to eat for lunch today. This is not an opinion, it is a statement of fact.
This has been a favorite subject of mine for a long time. There are numerous insights to be gleaned by analyzing the entire spectacle of 2019 predictions. As we enter peak forecasting season – it starts . . . NOW! – discussing some of the better and worse aspects of this entire debacle is productive. A few of the smarter approaches are worth noting today, as well as some of the more insidious nonsense from the crop of past future forecasts about 2018.
But first, a reminder: As we explained last year, the problem with forecasts goes beyond their mere lack of accuracy. My critique is with the underlying cognitive and philosophical failings that are associated with the entire forecasting industry: a lack of humility, the assumption of a skill set clearly not in evidence, and most damning of all, a failure to recognize the randomness of the world at large.
A reminder of our prior definition: “a forecast of a future event that is specific in time and numerical value. For investors’ purposes, this means an asset class, a price target and a date.” Descriptive phrases like the “market will be squishy” or “employment will stay robust” are too soft and ambiguous to count as true predictions. They are at best mere expectations.
I find it helpful to break forecasts into distinct archetypes: good faith guesses, foolish predictions, and marketing bullshit.