Yearly Archives: 2007

BetFair, TradeSports-InTrade and the Hollywood Stock Exchange do control what you read on Wikipedia.

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Puppet

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– BetFair has been editing Wikipedia 6 times.

– TradeSports-InTrade has been editing Wikipedia 33 times.

– Cantor (the owner of the HSX): 134 times.

– Google (of Bo Cowgill) and Yahoo! (of David Pennock and Daniel Reeves): hundreds of times.

– University of Iowa (the owner of the Iowa Electronic Markets), George Mason University (the working place of Robin Hanson): thousands of time.

– MicroSoft (of Henry Berg): DOZENS OF THOUSANDS OF TIMES.

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Wiki Scanner: Search the Wikipedia edits to spot the organizations that edited it. – [One interesting function is temporarily disabled. It would allow us to spot exactly what it is that the firms did edit on a particular Wikipedia page. When this functionality is re-instated, I will write a more detailed blog post.]

Wiki Scanner FAQ

1. Wholesale removal of entire paragraphs of critical information. (common for both political figures and corporations)
2. White-washing &#8212- replacing negative/neutral adjectives with positive adjectives that mean something similar. (common for political figures)
3. Adding negative information to a competitor&#8217-s page. (common for corporations)

[…] Overall&#8211-especially for non-controversial topics&#8211-Wikipedia seems to work. For controversial topics, Wikipedia can be made more reliable through techniques like this one. As for other approaches, I think colored text is a promising direction for combating disinformation in wikipedia. […]

List of salacious edits, by Wired

New York Times – Slate

The Wikipedia pages: prediction markets and betting exchanges.

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Hence the need for Midas Oracle as an independent and reliable source of information on prediction markets. Here, David Yu, John Delaney, Alex Costakis and company don&#8217-t control what you read.

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Previous: WIKIPEDIA CENSORS BETFAIR. &#8211-&gt- Now we can suspect why. See above.

Betchas Continuing Legal Struggles

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You can keep up with the news about Betcha, the Seattle-based betting platform suffering the continued attentions of the Washington State Gambling Commission through the Betcha blog.

Founder Nicolas Jenkins has the latest update: Now We Know Why That Search Warrant Came So Easy:

We just found out yesterday that &#8212- surprise! &#8212- the Commission wasn&#8217-t exactly forthcoming with the judge when it applied for the warrant. In its answer to our complaint, the Commission admitted that, when it made its application to Judge Paula Casey, it did not mention that we had filed suit against it the day before. In the answer they referred to it as an &#8220-alleged suit,&#8221- but it&#8217-s hard to see what was &#8220-alleged&#8221- about it. I was at the Commission&#8217-s office when our counsel handed Deputy Commissioner Sharon Reese a copy of the complaint, and we notified her again later in the day by e-mail that we had filed it.

Also recently recently posted: Now Louisiana Wants Us &#8212- For Seventy Cents.

Jenkins said that he has heard that the state of Louisiana has filed arrest warrants for him and two of his employees, and is seeking extradition to Louisiana. As of the posting the specific charges were unknown, but he speculates the allegations concern the state&#8217-s law against &#8220-gambling by computer.&#8221- Jenkins comments in response that the Louisiana law won&#8217-t apply to Betcha for the same reason that the Washington law doesn&#8217-t: the Betcha service doesn&#8217-t meet the legal requirements for gambling.

As it turns out, Jenkins reports that in the 30 days the betting platform was in operation, it took exactly 4 bets from a single Louisiana resident. Revenue after Betcha&#8217-s promotional credits? 70 cents.

The Louisiana Gambling by Computer law is available from the website of the state legislature.

UPDATES from the Betcha blog:

PREVIOUSLY on Midas Oracle:

Decision markets that give the consequences of something

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Here&#8217-s what Robin Hanson meant&#8230- when he wrote:

[…] markets that give the consequences of electing any particular candidate.

This:

Let U = the unemployment rate, D = Democrats win, and R = Republicans win. An exchange rate between “Pays $U if D” and “Pays $1 if D” gives an estimate of E[U|D]. Similarly, an exchange rate between “Pays $U if R” and “Pays $1 if R” gives an estimate of E[U|R]. We can compare E[U|D] and E[U|R] to see which candidate is expected to have a lower unemployment rate. And we know how to pay off all of these assets, no matter what happens.

More:

Since we can pay off all the assets objectively, predictions of their relative value are also predictions about objective things, not just about opinion. Any information about what employment policies a candidate would choose, and about the consequences of those policies, could be relevant.

More in Robin Hanson&#8217-s paper on &#8220-decision markets&#8221- &#8212-PDF file.

And read Mike Giberson&#8217-s comments on the Patri Friedman blog post. (He likes it and thinks I was too harsh on it.)

Jed Christiansen strongly believes that Chris Masse has a bad understanding of probabilities.

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And he could be right. :-D

The only way to evaluate accuracy of predictions is with a sufficient group or series of predictions.

I don&#8217-t disagree with that. My previous blog post on the Karl Rove prediction market simply stated that:

  1. The NewsFutures prediction on Karl Rove happened to be wrong.
  2. The resignation prediction markets are usually wrong.
  3. There are different kinds of prediction markets. The resignation prediction markets are of the kind where there are no reliable advanced indicators.

Jed Christiansen and Emile Servan-Schreiber want to deny us the right to say that an individual prediction was inaccurate. I respectfully disagree with that. Other than that, I agree with their general point about using long series and understanding the true nature of probabilities. But, in day-to-day life, we all assess the accuracy of individual predictions. While it&#8217-s not the most important angle, that&#8217-s not something to censor, in my view.

On a related note, Midas Oracle should publish more excerpts of papers that assess long series of prediction markets. We will work on it in the future.

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Karl Rove will resign from the White House.

(You will spot that the prediction market was predicting, lately, that the probability for a Karl Rove resignation was only about 20%.)

Karl Rove resignation - NewsFutures

Previous blog posts by Chris F. Masse:

  • Become “friend” with me on Google E-Mail so as to share feed items with me within Google Reader.
  • Nigel Eccles’ flawed “vision” about HubDub shows that he hasn’t any.
  • How does InTrade deal with insider trading?
  • Modern Life
  • “The Beacon” is an excellent blog published by The Independent Institute.
  • The John Edwards Non-Affair… is making Memeorandum (twice), again.
  • Prediction Markets = marketplaces for information trading… and for separating the wheat from the chaff.

Does this prediction market chart look predictive to you?

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Karl Rove will resign from the White House.

Karl Rove resignation - NewsFutures

Emile Servan-Schreiber:

Chris, how exactly do you define “predictive”? If your criterion is “last trading price above 50%”, that would betray a very limited understanding of the nature of both probability and binary markets. That’s a debate you and I have had ever since the first days of chrisfmasse.com a propos the 2004 US presidential election.

To your credit, I don’t think anyone has yet proposed a good way of assessing the “predictiveness” (predictivity?) of a single binary market after the fact. It is a very difficult question. Does anyone here have an answer?

#1. What I see on the NewsFutures chart above is that the probability of Karl Rove resigning went to about 20% previous to the official announcement in the WSJ, indicating that it was more likely than not that he&#8217-d stay at the White House. So, in terms of absolute accuracy, that particular prediction market failed.

#2. Emile-Servan-Schreiber is right that, scientifically, we should assess a series of identical prediction markets, not just one, if we want to determine whether this market-based technology has merit. (And we should assess them comparatively to competitive institutions&#8217- predictions.) Overall, the NewsFutures prediction exchange is indeed predictive.

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Just like the Olympic City prediction markets, the resignation prediction markets are rarely predictive because there aren&#8217-t any reliable advanced indicators to guide the traders. The Olympic committee is secretive and does not grant on merit but on politics (or corruption). As for the embroiled officials (politicians or CEOs), they are secretive too and send false signals (&#8221-Read my lips- I will never resign&#8221-). In both cases, the event derivative traders don&#8217-t have any access to inside information, the only one that counts. So these two types of prediction markets are of inferior quality, which explains why experienced traders don&#8217-t speculate on them. To have a better understanding of the prediction markets, in addition to the very good argument that EJSS makes, I think we should rate the advanced indicators. When they are of poor quality, we should disclose it to our readers and traders.

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NEXT: Jed Christiansen strongly believes that Chris Masse has a bad understanding of probabilities.

Karl Rove resigns abruptly.

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Makes him look like he is guilty of something, then.

Wall Street Journal + Portrait-Interview – The WSJ coverage of his resignation seems biased to me.

New York Times + NYT Editorial
Karl Rove

I haven&#8217-t seen any Karl Rove prediction market at InTrade and NewsFutures. Am I correct?

UPDATE: NewsFutures was floating a Karl Rove event derivative&#8230- which turned out not to be predictive. Resignation prediction markets are rarely predictive, in my experience.

Karl Rove will resign from the White House.

Karl Rove resignation - NewsFutures

UPDATE #2: Emile Servan-Schreiber&#8230-

Chris, how exactly do you define “predictive”? If your criterion is “last trading price above 50%”, that would betray a very limited understanding of the nature of both probability and binary markets. That’s a debate you and I have had ever since the first days of chrisfmasse.com a propos the 2004 US presidential election.

To your credit, I don’t think anyone has yet proposed a good way of assessing the “predictiveness” (predictivity?) of a single binary market after the fact. It is a very difficult question. Does anyone here have an answer?

#1. What I see on the NewsFutures chart above is that the probability of Karl Rove resigning went to about 20% previous to the official announcement in the WSJ, indicating that it was more likely than not that he&#8217-d stay at the White House. So, in terms of absolute accuracy, that particular prediction market failed.

#2. Emile-Servan-Schreiber is right that, scientifically, we should assess a series of identical prediction markets, not just one, if we want to determine whether this market-based technology has merit. (And we should assess them comparatively to competitive institutions&#8217- predictions.) Overall, the NewsFutures prediction exchange is indeed predictive.

NEXT: Does this prediction market chart look predictive to you? + Jed Christiansen strongly believes that Chris Masse has a bad understanding of probabilities.