Investor John Hussman has bad news. Corporate profit margins are at an all-time high, and bound to fall, he says. That's going to crush profits and cause the market to drop. He makes a convincing case with charts and lots of historical data. He has a PhD.
Wharton professor Jeremy Siegel calculates profit margins a different way, totaling up the income of all businesses and partnerships, not just corporations, and comes to a different conclusion. By his metric, profit margins aren't that out of line at all. He thinks the Dow Jones could be on its way to 18,000. He makes a convincing case with charts and lots of historical data. He also has a PhD.
Who is right?
It depends how you feel about the market. If you're bearish, you'll side with Hussman, and use his analysis and credentials to confirm your views. If you're bullish, you'll follow Siegel, and use his insight to rationalize your feelings.
Everyone can back up their own views with their own data using their own preferred metrics. The problem is that equally smart people can argue the exact opposite point and sound just as convincing. "Truth" and "fact" just become whatever you prefer to believe.
Here's another example. Many cite Yale economist Robert Shiller's CAPE valuation metric to make the case that stocks are overvalued. Since 1871, CAPE -- a P/E ratio that averages 10 years of earnings adjusted for inflation -- has averaged about 16. Today it's at 22. "Listed companies according to CAPE were 53 percent overvalued at the year end and 71 percent overvalued on 20th March," analyst Andrew Smithers wrote last year. 71% overvalued!
When I mentioned this to Liz Ann Sonders, chief investment strategist of Charles Schwab, this week, she argued that CAPE can be misleading because accounting standards have changed so much that looking at 140 years of data is like comparing apples to oranges. And there's no reason, she says, to average earnings together over a 10-year period when the average business cycle is more like six years. She prefers a different metric that averages together four and a half years of past earnings with two quarters of future earnings projections. By that metric, stocks don't look too bad. Certainly nowhere near 71% overvalued.
Here again, equally smart people can use their own data and metrics to argue the exact opposite points. And both can do it convincingly. (Sonders, to her credit, pointed this out.)
Depending on what data you use, 2009 brought either deflation or hyperinflation. Depending on what baseline you use, the federal deficit is either declining or rising. Depending on what scientist you cite, global warming either is or isn't occurring. Depending on what surveys you use, the majority of Americans either strongly agree or fiercely disagree with whatever legislation you're lobbying for.
Everyone thinks they're right. And that's really dangerous.
Most of this can be explained by John Kenneth Galbraith's wisdom: "Pundits forecast not because they know, but because they are asked." No one with a PhD or an MBA or "Goldman Sachs" on their business card will ever dare utter the words, "I don't know." Curiously convinced of their intelligence, they make predictions. But since most of these predictions are really just emotional fuzzy feelings, those touting them go on a data-mining spree until they find the evidence they need to back up their preconceived notions.
This is actually getting worse with the new world of Big Data, as Nassim Taleb recently wrote:
We're more fooled by noise than ever before, and it's because of a nasty phenomenon called "big data." With big data, researchers have brought cherry-picking to an industrial level.
Modernity provides too many variables, but too little data per variable. So the spurious relationships grow much, much faster than real information.
In other words: Big data may mean more information, but it also means more false information.
And part of it is explained by our pundit culture. To make it as a pundit, all you have to do is be right on one big, bombastic prediction. If you say the market will fall 5% and you're right, no one cares. If you say the market will fall 50% and you're right, you're a god who can command five-figure speaking fees for life. So the media is dominated by wild, far-out predictions, most of which can only be rationalized by looking at a cherry-picked sliver of the data. Or even just made-up numbers.
What can you do about it? I'd recommend three things.
1. Ignore most predictions, especially hyper-specific ones
I've always loved Carl Richards' line, "Risk is what's left over when you think you've thought of everything else." As a corollary, accurate predictions are what's left over after you've watched CNBC.
Coming to terms with how awful the collective track records of market predictions are is quite liberating. Ignoring predictions forces you to think about the economy with an appreciation for how random and unpredictable things are. Will there be a recession year? I don't know, but my portfolio could take it if there is. Will there be another big market rally? I don't know, but my portfolio will enjoy it if one comes.
2. Think more like Darwin
Berkshire Hathaway's Charlie Munger loves to talk about Charles Darwin. Darwin, Munger says, wasn't abnormally smart, but he had a unique outlook on science in that he was practically allergic to confirmation bias. While most people form a theory and then seek information that proves it right, Darwin spent most of his career desperately trying to prove himself wrong. Munger once said:
He [Darwin] tried to disconfirm his ideas as soon as he got 'em. He quickly put down in his notebook anything that disconfirmed a much-loved idea. He especially sought out such things. If you keep doing that over time, you get to be a perfectly marvelous thinker instead of one more klutz repeatedly demonstrating first-conclusion bias.
Economists and investment analysts should do the same.
3. Surround yourself with people who disagree with you
Realizing that there are two sides to each story makes it imperative that you hear both stories. Whenever you get a great investment idea, or have an opinion on where the economy is headed, find someone who disagrees, and hear them out. At worst, you continue to disagree. More often, you'll gain valuable insight. Surprisingly, I think many don't do this out of fear of being persuaded away from the opinions they're most comfortable with, even if they know they're wrong. Or as Andy Rooney put it, "People will generally accept facts as truth only if the facts agree with what they already believe." Don't let that be you.
Check back every Tuesday and Friday for Morgan Housel's columns on finance and economics.
The article Bad News: Everyone Is Right! originally appeared on Fool.com.Fool contributor Morgan Housel owns shares of Berkshire Hathaway. The Motley Fool recommends Berkshire Hathaway. The Motley Fool owns shares of Berkshire Hathaway. Try any of our Foolish newsletter services free for 30 days. We Fools may not all hold the same opinions, but we all believe that considering a diverse range of insights makes us better investors. The Motley Fool has a disclosure policy.
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