Winter always brings strange weather to the Baltimore area. Given our geographic location, we often sit directly on the 32-degree line during winter storms. That means we see some combination of snow, sleet, freezing rain, and plain rain. The exact precipitation type is determined not just by the temperature at ground level, but the temperature of the air above us at various atmospheric layers. This can make forecasting winter weather here incredibly difficult.
We’ve had a few of these winter storms recently and the forecasts for a lot of snow turned into a lot of sleet and ice. Many people saw this as a failure of forecasting, but In reality, the computer models saw the storm coming a week in advance, knew when the storm would hit, roughly how much precipitation would fall, and predicted temperatures would be right around 32 degrees. But the models were off by one or two degrees at some of the higher atmospheric layers, so we wound up with more sleet and freezing rain than snow. One or two degrees!
It is incredible how much computer modeling has advanced in recent years and how accurate weather forecasting has become. We do a lot of forecasting as financial planners as well and I’ve written about the many similarities between forecasting the weather and financial planning before. Unfortunately, the forecasting we do will never be as accurate as those weather forecasts for one simple reason: human behavior.
Weather forecasting relies on many measurable data inputs and looks at past weather patterns to help forecast the future. Market forecasting also relies on data inputs, but the impact of human behavior means the future will never look like the past. We can measure the financial metrics of the economy and individual companies and look at how the market performed in the past with similar metrics. Unfortunately, that won’t tell us anything about where the market might go in the next day, month, or even year, because we don’t know how investors will react to these metrics.
The recent GameStop phenomenon is just the latest example of irrational human behavior driving stock prices to levels that are detached from their underlying fundamentals. Imagine someone had asked you to predict the stock price of this retailer at the beginning of the year. You looked at the fundamentals, analyzed the growth prospects, and pulled up this ten-year price chart:
Notice the y-axis on that chart only goes up to $95 and the price never got near that level in TEN YEARS. If we add in the first two months of 2021 to that chart we need to increase the y-axis to $1,100 as the price busted through the $95 level in January:
In a matter of days, the stock price jumped from $40 to $340, before dropping back down to $40 just as rapidly. It’s currently on the move up again, with the price over $100 as of this writing. Would you be willing to try to forecast where the price will be tomorrow?
It wasn’t fundamentals driving the price of GameStop stock, it was investor behavior. Amateur traders on Reddit message boards gathered together to buy the stock en masse and drive the price higher. How can anyone possibly predict something like this?
The answer, quite simply, is that you can’t. What happened with GameStop was extreme and unusual and that’s what made it such a big news story. There are many subplots to this story and countless words have already been written about it (Matt Levine has done a great job covering it). I don’t think the GameStop story told us that markets don’t work or that fundamentals don’t matter in investing. What it did remind us is that markets are unpredictable because they are driven by human behavior.
When we use forecasts in financial planning we aren’t trying to predict the exact future, we are trying to imagine the range of what might be possible in the future. Future market returns are just one of the variables we need to forecast in a financial plan. We also have to forecast what inflation might be in the future, how expenses might change over time and how long you will live. We know we won’t get any of these forecasts precisely right, but as John Maynard Keynes said:
“It is better to be roughly right than precisely wrong”
If we understand that we’ll never come up with a precise forecast of the future, we can try to be “roughly right” instead. This allows us to set the direction of the financial plan, but we’ll never be able to draw the exact map. As we like to say, your financial plan is a compass, not a GPS. Without it, you wouldn’t know where to go, but even with it, you’ll need to make course corrections along the way. Accepting this inability to precisely forecast the future will enable you to ignore the crazy market swings we see on a regular basis. And maybe it will give you a little more sympathy for that meteorologist who was calling for too much snow.