Meet again James Surowiecki, author of The Wisdom Of Crowds.

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James Surowiecki

James Surowiecki, author of The Wisdom Of Crowds

Previously: James Surowiecki’s The Wisdom Of Crowds… still stands.

Previous blog posts by Chris F. Masse:

  • A second look at HedgeStreet’s comment to the CFTC about “event markets”
  • Since YooPick opened their door, Midas Oracle has been getting, daily, 2 or 3 dozens referrals from FaceBook.
  • US presidential hopeful John McCain hates the Midas Oracle bloggers.
  • If you have tried to contact Chris Masse thru the Midas Oracle Contact Form, I’m terribly sorry to inform you that your message was not delivered to the recipient.
  • THE CFTC’s SECRET AGENDA —UNVEILED.
  • “Over a ten-year period commencing on January 1, 2008, and ending on December 31, 2017, the S & P 500 will outperform a portfolio of funds of hedge funds, when performance is measured on a basis net of fees, costs and expenses.”
  • Meet professor Thomas W. Malone (on the right), from the MIT’s Center for Collective Intelligence.

James Surowieckis The Wisdom Of Crowds… still stands.

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James Surowiecki&#8217-s 4 comments at Overcoming Bias (in October 2007), responding to accusations that he got it all wrong about Francis Galton:

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James Surowiecki&#8217-s 1st comment:

&#8220-Galton did not even bother to calculate a mean, as he saw his data was clearly not normally distributed. He used the median (of 1207), which was much further off than the mean, but by modern standards clearly the better estimator. It was Karl Pearson in 1924 who calculated the mean.&#8221-

Robin [Hanson], before repeating falsehoods, you might want to go back to the original sources &#8212- or, in this case, to the footnotes to my book. Galton did, in fact, calculate the mean, long before Karl Pearson did. Galton&#8217-s calculation appeared in Nature, Vol. 35, No. 1952 (3/28/07), in a response to letters regarding his original article. One of the correspondents had gone ahead and calculated a mean from the data that Galton had provided in his original piece, and had come up with the number 1196. Galton writes, &#8220-he makes it [the mean] 1196 lb. . . . whereas it should have been 1197 lb.&#8221-

I find the fact that Levy and Peart wrote an entire article about Galton (and, to a lesser extent, about my use of him), and never went back and checked the original sources is astounding in its own right. (They actually wonder in the paper, &#8220-However the new estimate of location came to be part of Surowieki’s account,&#8221- as if the answer isn&#8217-t listed right there in the footnotes.) What makes it even more astounding, though, is that they&#8217-ve written an entire paper about the diffusion of errors by experts who &#8220-pass along false information (wittingly or unwittingly)&#8221- while passing along false information themselves.

It also seems bizarre that Levy and Peart caution, &#8220-The expectation of being careful seems to substitute for actually being careful,&#8221- and yet they were somehow unable to figure out how to spell &#8220-Surowiecki&#8221- correctly. The article is a parody of itself.

I&#8217-m happy to enter into a discussion of whether the median or the mean should be used in aggregating the wisdom of crowds. But whether Galton himself thought the mean or the median was better was and is irrelevant to the argument of my book. I was interested in the story of the ox-weighing competition because it captures, in a single example, just how powerful group judgments can be. Galton did calculate the mean. It was 1197 lbs., and it was 1 lb. away from the actual weight of the ox. The only &#8220-falsehood&#8221- being perpetrated here are the ones Levy and Peart are putting out there, and the ones that you uncritically reprinted.

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James Surowiecki&#8217-s 2nd comment:

Here are the links for the letter from Galton, where he reports the mean:

http://galton.org/cgi-bin/search/images/galton/search/essays/pages/galton-1907-ballot-box_1.htm
http://galton.org/cgi-bin/search/images/galton/search/essays/pages/galton-1907-ballot-box_2.htm

There&#8217-s no reason for debate here. Levy and Peart say &#8220-Pearson’s retelling of the ox judging tale apparently served as a starting point for the 2004 popular account of the modern economics of information aggregation, James Surowieki’s Wisdom of Crowds.&#8221- It wasn&#8217-t the starting point. The starting point was Galton&#8217-s own experiment, and his own reporting of the mean in &#8220-The Ballot Box.&#8221- Robin writes: &#8220-Galton did not even bother to calculate a mean.&#8221- He did calculate it, and he did report it. This fact shouldn&#8217-t be listed as an &#8220-addendum&#8221- to the original post. The original post should be rewritten completely &#8212- perhaps along the lines of &#8220-Surowiecki and Galton disagree about which estimate is a better representation of group judgment&#8221- rather than &#8220-Author Misreads Expert&#8221- &#8212- or else scrapped.

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James Surowiecki&#8217-s 3rd comment:

I appreciate Levy and Peart admitting their mistake. But they seem not to recognize that their mistake undermines the critique that&#8217-s at the center of their paper. Their paper, they write, is about the misconstruing of Galton&#8217-s experiment. &#8220-A key question,&#8221- they write, &#8220-is whether the tale was changed deliberately (falsified) or whether, not knowing the truth, the retold (and different) tale was passed on unwittingly.&#8221- But the account of Galton&#8217-s experiment was not changed deliberately and was not falsified. It was recounted accurately. Levy and Peart want to use my retelling of the Galton story as evidence of how &#8220-experts pass along false information (wittingly or unwittingly) [and] become part of a process by which errors are diffused.&#8221- But there&#8217-s no false information here, and no diffusion of errors, which rather demolishes their thesis. If they really want to write a paper about how &#8220-experts&#8221- pass along false information, they&#8217-d be better off using themselves as Exhibit A, and tell the story of how they managed to publish such incredibly shoddy work and have prominent economists uncritically link to it.

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James Surowiecki&#8217-s 4th comment:

To finish, Levy and Peart insist that their really important point still stands, which is that &#8220-When people quote Galton through Surowiecki, they tell Surowiecki&#8217-s tale, not Galton&#8217-s,&#8221- and that this is a problem because Galton&#8217-s thinking is being misrepresented. But as I said earlier, &#8220-The Wisdom of Crowds&#8221- was not intended to be a discussion of Francis Galton&#8217-s opinions on what&#8217-s the best method to capture group judgment, nor, as far as I know, has anyone who&#8217-s &#8220-Surowiecki&#8217-s tale&#8221- used the Galton example since used it to analyze Galton&#8217-s opinions. People aren&#8217-t quoting the Galton story because they&#8217-re interested in what Galton himself thought about the median vs. mean. They&#8217-re quoting it because they&#8217-re interested in the bigger idea, which is that group judgments (and this is true whether you use the median, the mean, or a method like parimutuel markets) are often exceptionally accurate. Levy and Peart have constructed a straw man &#8212- and, in this case, a straw man based on a falsehood &#8212- and then tried to knock it down.

Robin [Hanson] writes: &#8220-it is ironic that Galton made quite an effort to emphasize and prefer the median, in part because the data did not look like a bell curve, while your retelling focuses on him calculating a mean after checking for a bell curve.&#8221- What&#8217-s ironic about this? He did check for a bell curve, and he did calculate the mean. It&#8217-s the data themselves, not Galton&#8217-s interpretation of them, that I was writing about. (If he hadn&#8217-t calculated the mean, I would have happily told the story with the median, since it was also remarkably accurate, and demonstrated the same point about the wisdom of crowds.)

Finally, on the substantive question, Robin (and Levy and Peart) seem to think that because the distribution of guesses wasn&#8217-t normal, that makes using the mean a mistake. But this is precisely what&#8217-s so interesting: if the group is large enough, even if the distribution isn&#8217-t normal, the mean of a group&#8217-s guesses is nonetheless often exceptionally good.

While TradeSports-InTrades growth seems slow, BetFair-TradeFair is poised to experience a formidable expansion in the coming years.

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The Independent of Ireland:

Betting exchange Betfair is to steal a march on its rivals with the introduction of a new service which will boost liquidity and offer punters the chance to make bets at starting prices. Up to now, betting exchanges, such as Betfair, operated by matching bets on either side. But it will now offer a guarantee that punters can get on as much as they need, as long as they are willing to plump for starting price (SP) odds. However, the SPs offered will not be those quoted in betting shops, but prices fixed by the exchange.

A spokesman said the new service was expected to give the business a big boost. &#8220-Currently, 40% of all bets are settled at SPs and this type of business tended to pass us by up to now,&#8221- he said. Betfair is already the largest exchange operation, ahead of the Dermot Desmond-owned Betdaq business. Estimates put the market share of exchanges at around 5% and this development could significantly boost that figure, the spokesman said.

Well, best wishes to BetFair-TradeFair.

Previously: The BetFair Starting Prices… explained

Previous blog posts by Chris F. Masse:

  • The marketing association between BetFair and TOTE Tasmania works better than expected.
  • The term “event markets” sucks —and the uncritical thinkers using this crappy term suck too.
  • CLIMBING HIS WAY TO THE TOP: Erik Snowberg is now Assistant Professor of Economics and Political Science at California Institute of Technology.
  • Unlike other countries, the United States of America defends the freedom to offend in speech.
  • The best research papers on prediction markets
  • 2008 Electoral Map
  • American Enterprise Institute’s Center For Regulatory And Market Studies (Policy Markets)

When your annual growth is +444%, youre not a Red Herring anymore.

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YOU&#8217-RE A BLUE WHALE, RATHER.

Blue Whale Comparison

Blue Whale (Balaenoptera musculus) with the vulcano Pico Island, Azores, in the background

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This is from Silicon Alley Insider.

Top 10 Blogs for October 2007 (U.S., Home and Work)

Please view in a fixed-width font such as Courier.+-------------------+----------+----------+-----------------+| Site              |   Oct-06 |   Oct-07 |  Percent Change ||                   | UA (000) | UA (000) |                 |+-------------------+----------+----------+-----------------+| Blogger           |   21,572 |   34,104 |             58% || WordPress.com     |    2,104 |   11,440 |            444% || Six Apart TypePad |    8,813 |   10,601 |             20% || tmz.com           |    7,107 |    7,805 |             10% || LiveJournal       |    3,366 |    4,260 |             27% || Xanga.com         |    4,760 |    2,741 |            -42% || Thatsfit          |     534* |    2,613 |            389% || Gizmodo           |     941* |    2,135 |            127% || Autoblog          |      920 |    1,949 |            112% || StyleDash         |    1,319 |    1,947 |             48% |+—-—-—-—-—-—--+—-—-—--+—-—-—--+—-—-—-—-—-–-+Source: Nielsen Online

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I made the right choice, last year. Midas Oracle is proudly powered by WordPress.org (which is the portable version of this open-source blogging software).

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Previous blog posts by Chris F. Masse:

  • The best research papers on prediction markets
  • 2008 Electoral Map
  • American Enterprise Institute’s Center For Regulatory And Market Studies (Policy Markets)
  • IIF’s SIG on Prediction Markets
  • Science
  • Why did prediction markets do well in the pre-polling era, professor Strumpf?
  • Mozilla FireFox users, do you have trouble downloading academic papers (as PDF files) from SSRN?

Justin Wolfers dreams of a prediction market land, where exchange odds are cited but not the polls.

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Knowledge @ Wharton (on polls):

The Power of Prediction Markets

The rapidly changing landscape of responders and related technology factors are two reasons why Justin Wolfers, Wharton professor of business and public policy, believes in the power of prediction, or betting, markets. Wolfers &#8212- who is associated with several prediction market sites such as InTrade.com or Tradesports.com [*], where participants buy and sell contracts on sports and potential political outcomes &#8212- argues that prediction markets are a more reliable outcome predictor than polls, for three reasons.

&#8220-First, by forcing you to &#8216-put your money where your mouth is,&#8217- they yield truthful revelation of beliefs,&#8221- Wolfers notes in a paper on pricing political risks with prediction markets. &#8220-Second, markets provide profit opportunities for those willing to gather new information that helps predict the future. And third, markets aggregate information dispersed across many traders.&#8221-

&#8220-You are not asking who they will vote for, but who they think will win,&#8221- says Wolfers. &#8220-The evidence is overwhelming that prediction markets provide a more accurate prediction than polls. On average, the final forecast from a Gallup poll is within about 2.25 percentage points, and the average for prediction markets is 1.5 percentage points.&#8221-

He points out that &#8220-the idea of betting on presidential elections is not new at all. Betting on elections has been going on for the last 100 years. If you read The New York Times from the turn of the century [**], they will report what is in the prediction markets &#8212- called &#8216-betting markets&#8217- back then &#8212- and not polls, which hadn&#8217-t yet been invented. But since 1940, the elections have been dominated by polls.&#8221-

Wolfers predicts that &#8220-within a few years and a couple of election cycles, we will be back to tracking political markets through the lens of prediction markets instead of polls. [***] In fact, in the last few election cycles, we have seen political commentators talking more and more about the race in light of prediction markets.&#8221-

[*] What kind of association is it? I take it that it is an informal association. I have never seen anything written on the InTrade-TradeSports sites.

[**] Thanks to Paul Rhode and Koleman Strumpf. PDF file

[***] I would be more prudent. I&#8217-d say that more and more commentators will follow the prediction markets, but the polls will remain the dominant barometer.

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UPDATE: Emile Servan-Schreiber (NewsFutures CEO) comments&#8230-

1) The traders themselves are the first to look at the polls to inform their trades. So the polls are here to stay.

2) Our recent experience in Western Europe seems to indicate that the superior accuracy of markets over polls when predicting elections may be a U.S. artifact that isn&#8217-t so easily reproducible elsewhere.
I&#8217-ve discussed this with Forrest Nelson of IEM [Iowa Electronic Markets], and apparently, ever since the Truman-Dewey polling debacle of 1948, U.S. pollsters have adopted a policy of reporting mostly raw numbers rather than projections based on sophisticated secret formulas, so they can&#8217-t be accused of manipulating opinion. However, raw numbers are notoriously unreliable when based on small samples, and Western European pollsters never report them, preferring instead to publish projections based on historically-informed statistical formulas. What we&#8217-ve observed in France and Holland is that it it&#8217-s very hard to beat the accuracy of such projections.

Are serial entrepreneurs the best to start up brand-new prediction exchanges or prediction software companies?

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Don&#8217-t we put too much into the &#8220-serial entrepreneur&#8221- myth?

#1. The founder of RedFin believes that serial entrepreneurs are likely to do worse, not better, than start-up newbies. Guy Kawasaki agrees.

#2. Google&#8217-s Melissa Mayer was on CNBC to talk about the You&#8217-Re The VC website.

Prediction Markets = Clear Expiry + Disperse Information + Participation Incentives

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Jed Christiansen at Forbes (just after John Delaney&#8217-s ill-written and pointless comment):

A market effectively aggregates the information from everyone participating. So anything where:

  • there is a clear result
  • information is dispersed between people and/or locations
  • people have an incentive to participate in the market

will likely provide better results than any other forecasting method. Experts just aren&#8217-t as good as they (or anyone else) think they are. It&#8217-s simply better to ask the crowd in these cases.

Missing from Jed Christiansen&#8217-s comment is the emphasis on long series for comparison. Takes time and hundreds of prediction markets to prove the wisdom of crowds.

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UPDATE: Jed Christiansen comments&#8230-

Chris, I agree that for probability assessment, a number of measurements are required to assess success. However, for metrics (ie, sales of widget X, rating of product Y) it doesn&#8217-t require a long series at all. Depending on how poor the current forecasting model is performing, a prediction market could prove successful after just a few measurements.

ads, auctions and markets: a proposal

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Ads make the web go round. US internet advertisement expenditure is expected to surpass $21 billions in 2007, while the share of web ads in the UK is already bigger than ad spending in radio and newspapers. More specifically, adwords (+adsense) is maybe the single reason behind growth and sustainability of the biggest business fairytale in our times, returning for example $2.6 (+$1.0) billions in 2006Q3 alone.

Textual ads are auction powered. Speaking of Google, let me repeat the well-known process (which is valid with some variations also in Yahoo&#8217-s Search Engine Marketing and Microsoft&#8217-s ad center -forgive my partial knowledge). Each time you view or click on an ad link, the advertiser rewards the site owner for the use of her screen real estate and the redirection of your attention span. More accessible real estate costs a lot, as the more the advertisers pay the higher their ad is ranked and exposing their message to more visitors. Ad ranking occurs mainly from a dynamic Vickrey auction model, namely cost-per-click bids is the most influential factor defining your ads rank. But, to my eyes, the system&#8217-s current status seems sub-optimal. From the ad platform engine&#8217-s perspective, earnings aren&#8217-t maximized, as the advertiser pays only for actual clicks and not for impressions. From the advertiser&#8217-s view, the ad&#8217-s impact is also sub-optimal, as high rank doesn&#8217-t guarantee more visitors, in the case of low ad relevancy to the user&#8217-s query and actual interests. Finally, and most importantly, the auction-based fundamental model doesn&#8217-t accumulate the collective intelligence of the previous visitors&#8217- behavior and probably results in a poor user experience. (Well, in practice, clickthrough rates are also evaluated and the adrank algorithm is much more complicated, but this doesn&#8217-t reduce the validity of comments on the fundamental choice of an auction model).

While the auction-based approach apparently works, let me propose a more simple, direct and transparent market-based variation. In such a case, the ad-space of the universe of all potential keywords combination consists a gigantic marketplace, while each keywords&#8217- combination will form a market in this marketplace. In each market, an advertiser&#8217-s submission triggers the creation of a stock, which is initially traded at the defined cost-per-click price. But this price is nothing but constant- it goes up each time a user clicks on the ad, or down each time a user clicks on a different ad (this second action could even be omitted). As a result, stock prices, therefore ad ranking, evolves dynamically to enhance previous visitors&#8217- choices and leverage the wisdom of crowds in forming an elegant user experience. Moreover, it maximizes engine&#8217-s gainings and advertisers&#8217- impact, while enables a fully trackable procedure for advantage of both the platform and its users.

I would like to stress my lack of extended or insiders&#8217- knowledge on the topic, but I&#8217-m more than eager to discover relevant attempts, or -even better- participate in some attempt to put this idea into reality.

cross-posted from my blog

The BetFair Starting Prices… explained

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The Guardian (which has the best coverage on BetFair-TradeFair):

The Betfair betting exchange will launch its starting price betting service in the middle of next month, after it received the approval of a number of the exchange&#8217-s biggest-staking clients at a series of demonstrations over the last seven days.

Betfair has spent two years developing a robust system to allow bets to be placed at its own SP. As a result, three extra columns will soon be added to its display for every win market on its British and Irish racing service: one for bets on a horse at the Betfair SP, one for &#8220-lay&#8221- bets against it at SP, and a &#8220-guide&#8221- price in the middle showing what the SP is likely to be.

The SP market and the normal exchange market will be separate, in an attempt to ensure that it is extremely difficult to manipulate the SP. Betfair also hopes to offset any reduction in overall liquidity – which is vital to any exchange – by attracting new clients.

The great majority of off-course bets are still settled at the official SP, derived from on-course betting markets, while even on the internet, around 55% of racing bets are settled at SP. The Betfair SP, derived from a market with a negligible profit margin, will allow punters to make a direct comparison between the bookmakers&#8217- odds and those on offer on the exchange.

SP bets will have some differences from &#8220-normal&#8221- bets on Betfair. Whereas normal bets can be cancelled until the moment when a rival gambler accepts the other side of the bet, SP bets cannot be cancelled once placed. Punters can, however, specify a minimum price at which they are willing to back, and a maximum price for lay bets.

In time, SP betting is likely to extend to the exchange&#8217-s place-only markets, and to many other sports in which the SP concept has never been used before.

&#8220-This has the potential to be the most significant step forward for Betfair since the exchange was launched,&#8221- Stephen Burn, Betfair&#8217-s director of horse racing, said yesterday. &#8220-Racing is scratching the surface. In time, we hope that we will be able to add it across football, tennis and so on. We could even return an SP on the next general election.&#8221-

Niall O&#8217-Connor has more.

NEXT: More on BetFair&#8217-s Starting Prices.