Expert predictions and the wisdom of crowds
In this post I will explore whether we can get a better estimate of the fair value of a stock by averaging the estimates from a number of different sources. I also offer a thought as to whether consensus estimates are likely more accurate than individual estimates.
Most investors are familiar with Warren Buffett’s words in the 2008 Berkshire Hathaway annual report: “Price is what you pay. Value is what you get.”
If you want to find out the price of a stock, you can look at the stock quotes through your discount broker. But prices are not a good guide to value.
Warren Buffett explains it this way in the Berkshire Hathaway’s 1987 Annual Report:
“Ben Graham, my friend and teacher, long ago described the mental attitude toward market fluctuations that I believe to be most conducive to investment success. He said that you should imagine market quotations as coming from a remarkably accommodating fellow named Mr. Market who is your partner in a private business. Without fail, Mr. Market appears daily and names a price at which he will either buy your interest or sell you his.
Even though the business that the two of you own may have economic characteristics that are stable, Mr. Market’s quotations will be anything but. For, sad to say, the poor fellow has incurable emotional problems. At times he feels euphoric and can see only favorable factors affecting the business. When in that mood, he names a very high buy-sell price because he fears that you will snap up his interest and rob him of imminent gains. At other times he is depressed and can see nothing but trouble ahead for both the business and the world. On these occasions he will name a very low price, since he is terrified that you will unload your interest on him.”
Consulting Mr. Market to determine the fair value of a stock won’t work.
Market mildly over-priced
You can consult experts about current values. For example, Aswath Damodaran, a Professor of Finance at the Stern School of Business at NYU, wrote recently: “I think that the given market pricing today, and my expectations of expected earnings and cash flows, stocks are very mildly over valued on September 23, 2022.” See here.
As an aside, I take exception to his terminology. He should have said “stocks are very mildly over-priced” not “over-valued”. The stock market doesn’t value anything.
Central to Professor Damodaran’s estimate of the fair value of the S&P 500 are forecasts or predictions of Expected Earnings, Expected Earnings Growth Rate, Expected cash payout (dividends + buybacks) as % of earnings and Expected Dividends + Buybacks. That’s a lot of forecasting and predicting. Forecasts and predictions are a weak link in the investment process.
An individual stock mildly underpriced
You can also consult experts about the current value of individual stocks. For example, Morningstar, Inc., which may be the world’s largest independent investment research and investment management services firm, estimates that Charles Schwab Corp., SCHW NYSE,US has a current fair value of 84.00 USD compared with its most recent closing price of 71.87 USD.
In essence Morningstar tells us that in their opinion SCHW is mildly underpriced.
Morningstar explains that: “At the heart of our valuation system is a detailed projection of a company’s future cash flows, resulting from our analysts’ research. Analysts create custom industry and company assumptions to feed income statement, balance sheet, and capital investment assumptions into our globally standardized, proprietary discounted cash flow, or DCF, modeling templates.”
You will see immediately that central to Morningstar’s estimate of the fair value of SCHW are forecasts or predictions. So, that also necessarily involves a lot of forecasting and predicting. Again, forecasts and predictions are a weak link. But forecasts and predictions in relation to an individual stock are a simpler proposition than doing the whole market.
Are these estimates inconsistent?
These two estimates can stand comfortably together. Stocks generally might be overpriced. But that does not prevent individual stocks from being offered at less than fair value. That is the beauty of investing in individual stocks.
An improved way
Can we improve on the accuracy of these estimates by obtaining estimates from, say, 22 leading investment banks and averaging them?
Gerd Gigerenzer is currently the director of the Max Planck Institute for Human Development in Berlin in Germany. He has written many books and papers about decision making and risk. In 2014 his book Risk Savvy, How to Make Good Decisions, was published. In chapter 5 he writes about the danger for investors in relying on predictions made by experts.
To highlight his point, he refers to end-of-year currency forecasts made by twenty-two international banks over a ten-year period. The forecasts estimated one-year-out exchange rates between the Euro and the U.S. Dollar. The banks included Credit Suisse, Bank of Tokyo-Mitsubishi, Royal Bank of Canada, UBS and Deutsche Bank, Bank of America Merrill Lynch, Barclay’s investment Bank, Commerzbank, HSBC, JPMorgan Chase, Morgan Stanley, and Societe Generale.
In December of 2000 most banks were calling for the dollar and the euro to be essentially at par by the end of 2001. In fact, the actual exchange rate at the end of 2001 was .88. Citigroup came close at .85. Sadly, that was the only time over the whole decade that Citigroup came close.
Gigerenzer looks at the forecasts for 2002. He writes: “In compensation for their overestimates the year before, the banks uniformly corrected their predictions downward. Again, these varied by more than twenty cents. But the euro went up; the true exchange rate was 1.05, higher than any of the banks had foreseen.” (Gigerenzer, Gerd, 2014) p.86
The author goes on for a full page pointing out that, for most of the period, the actual exchange rate was outside of the entire range of predictions. He also points out that the banks seemed to make their following-year estimates to make up for mistakes the previous year. He says: “Thus, they are consistently one year behind and miss every up- or downswing.” His further conclusion is that the chart suggests that: “All these experts had the same thought: Next year is like this year. If you look at the ten years of predictions, they consistently predicted the upward or downward trend of the previous year. In over 90 percent of the individual forecasts, the experts follow that rule”
Take a look at Gigerenzer’s Figure 5-1. Each point shows the prediction of one of twenty-two international banks. And here’s the real point for present purposes. The average predictions of the twenty-two banks come no closer to being accurate.
There is a statistical phenomenon that tells us that if we ask a large number of people to estimate a quantity, in certain limited circumstances the average of the estimates will come out remarkably close to the actual number. It is popularly called the Wisdom of Crowds.
Michael J. Mauboussin heads Consilient Research at Morgan Stanley division Morgan Stanley Investment Management’s Counterpoint Global, is an adjunct professor of finance at Columbia Business School and author. He and co-author Dan Callahan’s report of February 10, 2015, titled Animating Mr. Market suggests:
“One way to animate Mr. Market is to consider the wisdom of crowds. What’s key is that crowds are wise under some conditions and mad when any of those conditions are violated.”
Mauboussin and Callahan did a little experiment with 67 people. The volunteers had to guess the number of jellybeans in a jar. They report: “The average estimate of the group was 1,427 beans. The jar contained 1,416 beans. So, the collective estimate was within one percent of the actual number. The accuracy was not the result of sharp individual guesses, as the average individual error was 53 percent. Rather, the guesses were sufficiently diverse to get to a very good final result. In this particular exercise, no participant did better than the collective.” See the report here.
So how does the abject failure of Gerd Gigerenzer’s banks to predict an exchange rate square with the wisdom of crowds? Mauboussin and Callahan suggest the answer:
“When nearly everyone adopts a point of view, whether it’s bullish or bearish, the psychological pull to conform is powerful. This is the main lesson from the Asch experiment. And when that psychological pull is led by stock prices, Mr. Market is no longer informing you, he is influencing you. You have come under his sway.”
Statistical basis undermined
Investing in the stock market is quite a different animal than counting jellybeans. One thing about the jellybean experiments is that everyone has to come up with an estimate without knowing what anyone else came up with. That is, the estimates are fully independent.
Imagine if the first of the 67 bean count guessers was asked to put their estimate up on a chalk board in front of the other 66 before they finalized their estimate. Once that number was on the board, imagine the second guesser was asked to put up their number. And so on, until one after another, all the estimates were up on the board. The guessers were aware of the views of the others before they gave their figure. The statistical basis for the experiment is undermined. Studies have shown this. See here.
Now let’s look at the stock market.
The views of others
It is impossible to invest in the stock market without being aware of the views of others. We read the newspaper. We read analysts’ reports of fair value and target prices. Analysts are aware of consensus estimates for future earnings made by other analysts and consensus target prices. We see prices that others have paid on the stock market.
Humans seem all too affected by the views of others. The issue comes up in many contexts. At the most extreme is the madness of crowds and mobs. Such madness is a real pathological human trait. Herd and lemming-like behavior are also fairly extreme. More subtle are peer and career pressures. More subtle again and still very powerful is group thinking (Groupthink). And then there are the forces that cause us to do what others are doing because we believe that what everyone else is doing must be right. This has been called ‘social proofing’.
Wisdom of crowds and madness of crowds
We can now compare the two different phenomena. The wisdom of crowds is nothing more than statistics at work. And the statistics only work well when the data are independent. As well, studies have shown that estimating simple number, such as the population of a city, works much better than something that requires a complex calculation based on other assumptions.
The madness of crowds is simply an extreme case of what happens in the stock market from time to time. It would be better to think of what happens all the time as the herding of crowds or the groupthink of crowds. These are essentially psychological phenomena, not statistical at all. They are Mr. Market in action.
The stock market and currency markets
The evidence presented by Gegerenzer relates to currency markets, and specifically forecasts or predictions of exchange rates. The average estimates of the 22 banks were no better than the abysmal record of the individual banks. I imagine all the banks were aware of the forecasts put out by their competitors. No doubt a certain amount of herding or groupthink was at play in the exercise. As well, as Gigerenzer puts it: “All these experts had the same thought: Next year is like this year.” Amongst other things anchoring would be at play.
As we saw at the beginning of this post, coming up with an estimate of the fair value of the stock market as a whole or of an individual stock, necessarily involves forecasting and predicting. I’ve no doubt a certain amount of herding or groupthink enters into the exercise. The experts may be affected by the recent past, anchoring and by conventional thinking.
I’m inclined to think that investors would be no further ahead collecting and averaging fair value estimates of stocks from a variety of sources. Wisdom of crowds would not help. What this further suggests to me is that consensus estimates have no more reliability or validity than individual estimates.
I suspect the best we could do would be to look at reports from several different analysts and look for different viewpoints or novel ideas to try to draw the best from them.
For a full discussion of wisdom of crowds and the stock market you might take a look at this post:
Does Wisdom of Crowds apply to earnings estimates, price targets, value estimates and stock prices?
To dig further into how investors can avoid herding, groupthink and the madness of crowds, see these posts:
The joy of contrarian investing
Explainer – herd mentality and poor investment results
Other posts on investment psychology
This post is part of a series. Readers are invited to read Investment psychology explainer for Mr. Market – introduction This will give you a better understanding of some of the terms and ideas and give you links to other posts in the series.
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