This year's stock-market correction reminds us once again that forecasting is folly. We have discussed this many times before (see this, this and this) so suffice it to say that the evidence is in: humans have no ability to say what will occur in the future. I was reminded of this courtesy of an article published one year ago today on the imminent recovery in oil prices.
The article in question, headlined "Why Oil Prices Will Rebound Before We Know It," appeared when oil prices were about $50 a barrel. Crude briefly bounced to $60, before dropping more than 50 percent to about $26, where it trades today.
Source: Bloomberg
It's not just energy forecasters who make mistakes — all of Wall Street has an unfortunate tendency to try to divine the future by looking at chicken entrails. Consider two recent Bloomberg stories: The first reported that Goldman Sachs had abandoned five of its six top trade recommedations for 2016 just six weeks into the new year. In the same vein Wall Street analysts are reducing their estimates for the Standard & Poor's 500 Index, again just a few weeks into the new year. My colleague Josh Brown calls this phenomenon "Nobody Knows Nothing, Episode 653."
Consider this definition: a prediction contains these key elements — it is 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.
Let's distinguish a true forecast from the everyday probabilistic assumptions we make. That you can cross Fifth Avenue without that bus hitting you isn't so much a forecast as a reasonable statement of probable outcomes.
Also, let's remove such general statements as "stocks tend to rise over time." It is possible to counter this claim — at least for now — by pointing out that Japanese equities haven't risen since 1989. However, it will take some time (perhaps a very long time) before we can prove or disprove that statement. In other words, a forecast must be specific, and it must be disprovable within some reasonable time frame.