Comments on: Does wisdom require markets?

By: Alan Jewell

Alan Jewell — Fri, 16 Mar 2007 03:44:01 +0000

Real money markets open up the possibility of arbitrage of various markets to other markets. For instance, a certain political party may be bad/good for certain baskets of stocks, and an arbitrage could potentially be constructed. The same could work for hurricane markets vs. insurers.

To the extent arbitrageurs can link two markets together, I think they gain more “wisdom.”

By: Mike Linksvayer

Mike Linksvayer — Mon, 22 Jan 2007 02:42:35 +0000

“Require” and “need” force a “no” answer.

I more or less agree with Alex Forshaw above.

Opaqueness of non-market mechanisms probably looks good to managers who will be using the information produced (participants don’t see prices). I’d keep this in mind if I were selling “collective intelligence” expertise to corporations.

Shareholder activists on the other hand…

By: Chris Masse

Chris Masse — Sat, 20 Jan 2007 18:51:58 +0000

“opaqueness”

Exactly. There’s a strong philosophic argument for open markets, which empower traders, as opposed to mechanisms relying on secrecy and hierarchy.

—

Other links on the non-market Wisdom of Crowds:

How and When to Listen to the Crowd
http://www.overcomingbias.com/.....en_to.html

The wisdom of the ProbabilitySports crowd
http://blog.oddhead.com/2007/0.....rts-crowd/

The Wisdom Of Crowds: James Surowiecki on the predictive accuracy of the horse race betting markets
http://www.midasoracle.org/200.....g-markets/

By: Jason Ruspini

Jason Ruspini — Sat, 20 Jan 2007 18:33:53 +0000

Alex has it right, and Tom Bell makes a good point although BRAIN, for example, does reward participants for performance. BRAIN actually doesn’t get a whole lot of respect in the PM world, but using some sort of calibrated averaging makes sense in corporate environments and where information isn’t very dispersed.

One reason why people might be suspicious of mechanisms like BRAIN is their relative opaqueness. There is the worry that administrators will be able to vary parameters to datamine whatever answer they’re looking for.

By: George Tziralis

George Tziralis — Sat, 20 Jan 2007 00:59:29 +0000

I totally agree with Pennock’s view: We should be colored as biased when we propose “Markets for everything”.

Professor Bell comments that the use of markets is justified if the discovery of relevant information is costly.

I could add that the markets are able to aggregate only those information that have a cost of discovery which is lower than the market’s monetary incentive.

I think that the need for a framework on when to use markets is highlighted.

In an earlier work of mine ( http://gtziralis.googlepages.c.....EC2006.pdf ) I quoted Schrieber’s ( https://dspace.mit.edu/bitstream/1721.1/28514/1/57345537.pdf ) empirical formula:

Forecast_value = (Importance x Quality x Acceptance) / Effort

Schrieber is pointing to the right direction, we should use markets for forecasts of significant value, but further work is highly needed.

By: Alex Forshaw

Alex Forshaw — Sat, 20 Jan 2007 00:33:47 +0000

Competitive forecasting would probably be better than internal prediction markets for all but the largest enterprises, just because even a semi-efficient market has its own high fixed costs (market makers, decent population of traders, maintaining liquidity blah blah blah). Prediction markets would be reign supreme in a public exchange setting, because that eliminates issues of trader population sizes and liquidity. But the capricious ruthlessness with which US regulations are enforced makes that impossibly risky.

By: Daniel Horowitz

Daniel Horowitz — Sat, 20 Jan 2007 00:05:58 +0000

“Indeed, after many person-hours spent playing with probability judgments from the ProbabilitySports contest — trying all kinds of fancy expert-weighting schemes and machine learning algorithms — my colleagues and I found it exceedingly difficult to consistently produce a better forecast than by simply averaging everyone’s probabilities. Moreover, averaging came within striking distance two prediction markets — TradeSports and NewsFutures — performing a hair worse, but statistically insignificantly so.”

Except

A) These markets are biased by the larger sports betting markets. I’m guessing if you mapped their prices aganst the prices of the sharpest online books you would have similar numbers.

B) The larger “markets” are “inefficient” as to exploit public bias and increase the profits of the all knowing sportsbooks.

c) I can beat your “market” simply by playing the same probability as the market and deviating slightly in situations where I know there is bias.

In fact, empirical evidence strongly indicates to me that the average of true experts is clearly superior to the average of all. The *problem* with this, and the reason why it is not necessarily supported in the literature is that, most people aren’t really experts. And there is no easy way to identify “true experts” (So Average of True Experts (AOTE) is not an actionable strategy in most cases.

” trying all kinds of fancy expert-weighting schemes and machine learning algorithms” - Not surprising t

But, when markets are viable, I agree that *real money* markets should yield better results than “averaging”

By: Chris Masse

Chris Masse — Fri, 19 Jan 2007 18:54:03 +0000

Christopher Thompson:

No, wisdom does not require markets

http://www.midasoracle.org/200.....e-markets/

By: Chris Masse

Chris Masse — Fri, 19 Jan 2007 18:31:03 +0000

Besides MSR (Inkling and WSX), can you cite examples of popular, public probability judgment websites (other than ProbabilitySports)?? Thanks. Just curious. I want to see things on the public place, as opposed to behind walls.

By: Tom Bell

Tom Bell — Fri, 19 Jan 2007 17:49:51 +0000

In order to get a fair assessment of the value of prediction markets compared to probability-averaging schemes, I think we ought to consider two functions separately: 1) expressing information that lies relatively ready-at-hand; and 2) stimulating investment in the costly discovery of information. See, e.g., the paper you co-authored, “Prediction Markets: Does Money Matter?” I’d suppose that merely averaging guesses would do pretty well at the former, but not so well at the latter. Your own work, as well as sound theory, suggests that to encourage research, we would probably prefer not just PMs, but real-money ones.