When Are Crowds Unwise?

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The wisdom of crowds theory has its fair share of skeptics, and with good reason.  When we look around us, we see lots of examples of crowds acting unwise.  Lynch mobs come to mind, as do street rioters, Nazi soldiers, and sometimes even stock market investors. In each of these examples, the crowd did things that individuals would consider quite imprudent.

Aren’t these examples incongruent with the wisdom of crowds theory?

No, they aren’t.  In his landmark book The Wisdom of Crowds, author James Surowiecki offers 4 criteria that a crowd must meet in order to act wisely:   (1) diversity of opinion; (2) independence of members from one another; (3) decentralization; and (4) a good method for aggregating opinions.

In every example of a crowd acting unwisely, the crowd fails to meet at least one of these criteria.  Since this blog is about prediction markets, I’ll focus on how markets can fail to meet these criteria and thus act unwisely.  I’ll also outline mechanisms that market creators can put in place to avoid such pitfalls.

Criteria 1:  Diversity of Opinion

To function properly, markets must attract traders with a diverse range of opinions.  In particular, the trader population should include a healthy balance of speculators and value investors.

Speculators are a timid bunch.  They like to follow the herd.  When it comes to investing, they tend to buy “popular” stocks because they view them as safe bets.  They don’t mind that these stocks are expensive, because they’ll pay a premium for what they perceive as a low-risk investment.  Historically, speculators don’t make much money in markets but they serve an important role:  creating profit opportunities for value investors.

Value investors are perceived as mavericks by others, but they don’t see themselves that way.  They just don’t like to follow the herd. Value investors view “safe” investments as those that others have undervalued.  Their strategy is to buy good stocks on the cheap and then reap a reward once others recognize their true value and start to drive the price up.  Historically, value investors tend to make the most profit in markets (Warren Buffett is a classic example.)

In addition to the diversity of opinion brought by speculators and value investors, markets also need the diverse knowledge base brought by investors from different backgrounds and different walks of life.  If the investor base in diverse, everyone brings fresh information and opinions to their trades, and it’s information and opinions that make markets move.

It would be cumbersome for market creators to test every prospective trader to measure their diversity of knowledge and opinion, but steps can still be taken to assure a diverse trading population.  When we recruit traders for our iCE prediction market for concept testing, we use demographic and socio-economic diversity as a proxy for cognitive diversity.  Thus, our traders are recruited from balanced panels that mirror the general US population in terms of age, gender, ethnicity, and income per the latest US Census data.

Criteria 2:  Independence of members from one another

Human beings are hyper-social animals.  We tend to herd with other human beings, and we perceive safety in following the herd. This trait serves us well in much of the natural world, but it devastates markets.  When market participants don’t exercise independence from one another and herd together, what results is a speculative bubble.

There are many examples of speculative bubbles throughout history, including the Tulip mania of 1637, the Dot-com bubble of the late 1990’s, and the recent US housing bubble of of 2008.   All of these bubbles share a similar pattern of origin, growth and crash.  Though there are various macro economic and sociological factors that can contribute to bubbles, one thing they all have in common is herding behavior.

Market creators can deploy various techniques to encourage investors to act independently.  Here are some that we’ve incorporated into our iCE prediction market for concept testing:

  • No communication between market participants
  • No access to historical price information
  • Greater profit potential for “betting against the market”
  • Guaranteed market liquidity via an automated market maker

Together, we’ve found that these techniques serve well to keep speculative bubbles at bay.

Criteria 3:  Decentralization

In the case of markets, decentralization means “not following a leader.”   Markets, unlike societies, function best under anarchy.

When a market has a leader, either formal of informal, traders base their trading behavior on that leader’s opinions rather than their own individual judgement.  We see this effect in the interaction between modern stock markets and the mass media.

Economists suspect that speculative bubbles have become more frequent and severe in recent years due to the media’s tendency to exaggerate both good news and bad.  The media is essentially acting as an opinion leader, influencing the masses to buy enthusiastically when the market is “hot” and sell in a panic when the market goes “cold.”

As previously mentioned, markets function best when traders base their trades on their own unique individual knowledge and opinions.  In iCE markets, there is no mass communication to the traders other than an explanation of how the market works and exposure to the concepts that we’re testing.

Criteria 4:  A good method for aggregating opinions

This one is easy for markets, because they are by nature an excellent method for aggregating opinions.  Other methods could include surveys, open debates, and voting booths.

In closing, as long as these four criteria are met, you can bet that a market, or any crowd, will act wisely.

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Kyle Burnam

Kyle Burnam is the CEO of Infosurv and the leader of its sister company, Intengo, where he oversees all client research and R&D projects. Having been in the industry since 2005, Kyle brings a wealth of experience to the table and an innovative eye to every project.
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