Do stock markets reliably tell us anything about the future?

The sustained market rally, with stocks up over 40% on average since the lows in March 2009 (The Dow Jones Industrial Average was about 6,500 in March 09; it is now about 9,500) is taken to be a forecast that real future economic recovery is on the horizon. But is the market a reliable forecaster of anything? That is, from the perspective of real industry and strategic foresight professionals, using hard-won, battle-tested approaches to anticipating future outcomes, should we factor the market’s direction into our expectations of the economic future?

US Stocks Do stock markets reliably tell us anything about the future?

DJIA since Sept '08

The answer is, broadly, yes. Stocks are shares in the future earnings of a company. They are therefore a “bet” on (er, an “investment” in) the future performance of a company, or many companies. The trading price on any day is the price at which there are as many buyers as sellers for these future returns. Rising prices mean there are more buyers than sellers, that means general expectation of future profits is going up. Investors are putting a higher price on the future.

The market is therefore considered a leading indicator of economic conditions. (By contrast, employment figures are lagging indicators — due frictional forces, not to mention morality, it takes companies a while to downsize in recessions or upscale in booms, so employment levels track economic conditions but with a delay.)

But how valid and dependable is the market as a leading indicator? It is also apparent that markets move up slowly and steadily, but fall in a hurry. So the downward move can hardly be held to be predictive. But the upward move appears to hold some weight as harbinger of better times. How much weight?

What’s particularly important is that the aggregate insight into future returns from shareholding investments — across many investors and many stocks — cancels out individual errors. Any one person may have a dumb idea of the ‘future cash flows’ from one or many companies, and the price of any one company may be unreliable for innumerable reasons, including fraud, but the knowledge and intelligence of hundreds of thousands of people, when aggregated and spread over many thousands of stocks, corrects for all these errors. It becomes robust.

Prediction Markets

This reliability of shared, aggregated insight — the wisdom of crowds — is precisely what makes ‘prediction markets’ such a powerful forecasting tool, as I have mentioned in previous posts. (Prediction markets apply market-like wisdom to create foresight in areas that are not normally ‘tradeable.’) Any one person will, as likely as not, get it wrong, but everyone together, rather astoundingly, get it right.

Ironically, crowd wisdom is much more reliable than the technical forecasting models that investment institutions use to try to determine how business, macroeconomic, interest rate, or other conditions will affect future stock prices. These predictions, based on the assumptions of a handful of model programmers and/or model users, are deeply vulnerable because there is no crowd-wisdom balance. It’s no better than reading tea leaves, only apparently (and unaccountably) more respectable.

Having said all this, it is well known that the ‘crowd,’ aka the ‘herd’ can and do all get it wrong together. This is what happens in price bubbles, or panic market exits, with everyone buying or selling because they are making the same wrong assumptions, or just doing what everyone else appears to be doing. (Most players making the same mistake together is the basic problem when prediction markets fail too.)

However, what is clear is this case is there was a very hard sell-off in the months prior to March 09, following revelations of the gravity of the Credit Crunch, but that this has slide has been arrested and mostly reversed. This says that innumerable smart people with, collectively, billions of dollars at stake, are expecting future profits higher than they did in March. That’s a prediction one can rely on.

read more

The Zeitgeist Effect on Prediction Markets

In my previous post, below, I threatened myself with the penance that I’d have to come back and think about the zeitgeist effect as a further limit on the use and validity of prediction markets. (Once again, I’m basically sold that prediction markets are a fabulous way to think about the short-term and/or contained system future, but it’s worth being clear about the limits of this tool.)

Zeitgeist, German for “spirit of the times,” refers to the often unconscious spectrum of intellectual views, analytical approaches, political and social concerns, etc., that people in any era share. Evidence from the checkered history of predicting the future shows that forecasters have been very heavily biased by their then-current conditions, current issues, and current state of the world, that is by their zeitgeist. They see reality and therefore the future through the lens of their times. The key marker of this effect at work is when many forecasts are not only wrong, but are wrong in the same way.

The zeitgeist effect, by the way, is not a peculiar condition. It is part of the many common human and social cognitive-perceptual biases that exist. (For a longer list and their effects in forecasting, see Future Savvy.) Zeitgeist is in fact sometimes more broadly known as “situational bias,” where situations that people find themselves in frame what they see and how they interpret events. In a depression, famously, it is difficult to see any source of upturn; in boom times it is hard to see the crash.

The Zeitgeist of the 1990s
Just one example of zeitgeist bias in forecasting can be seen in predictions made in the 1990s, when the fall of Soviet Union and the end of the Cold War provoked new hope about global interaction and growth, and this, combined with the rise of digital technologies, the Internet, WTO agreements, and the dot.com market boom, fueled a new zeitgeist of optimism. It was very common, in this era to predict global prosperity, international peace and harmony, rising standards of living, enhanced personal freedoms, and a better environment. By the end of 2001, the NASDAQ bubble had burst, Al-Qaeda had struck buildings that symbolized U.S. power, the “War on Terror” had begun, and the entire rosy 1990s and all the forecasts that went with it, were finished. Zeitgeist or situation has, evidently, a very strong pull on what people think is possible and likely in the world at large, and in their own sector or industry. It frames the questions people ask, the topics they think are important, the outcomes they expect, and how they interpret signals of change.

The point is, do prediction markets somehow counter this well-known perceptual-cognitive bias in forecasting? No. The outcomes people think more plausible – that they will “buy up” in a prediction market – are deeply affected by situational conditions. This is sure to be a factor when, for example, Google sets up a market to tap its employees for forecasts. The people involved, smart as they are, will be strongly by situational factors – and this will affect which future outcomes look more likely.

Herd Effects
Moreover, they will be pulled in the same direction. As prediction markets, like Delphi studies, are particularly a consensus-based method (forecasters drawing predictive results from the study/game are going on what most people say/do), they are by definition deeply vulnerable to the zeitgeist effect. This dovetails with another well-known social cognitive bias, the “herd effect” or “bandwagon effect,” or “groupthink,” where people to believe or do things because many other people are doing or appear to be doing them. The only way to avoid groupthink is to isolate people from each other (as Delphi studies attempt to do by not disclosing others’ responses while the study is live.) But in prediction markets the player can, of course, see what others are doing. When buying a “stock” that is getting more expensive they may be reassured that others are buying it too — leading them to buy more, producing a classic herd-effect situation.

These biases – and various others, as detailed in Future Savvy, are among the many perceptual and cognitive biases that people bring to the world. They are part of (and evidence of) perception being active and constituent in our understanding of the world, and therefore of the future. We can chip away at our perceptual framwork, particularly by questioning our assumptions and investigating the basis of our knowledge (possibly through scenario planning.) However, no matter how astutely we look and how consciously we try to eliminate them, our paradigms exist, and they color our forecasts, and prediction markets do not make them go away.

read more