The fact that Inkling needs five bullet points and a graph to explain short selling is a good indication it’s too complicated.

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That was Jason Trost&#8217-s comment.

But see, first, Chris Hibbert&#8217-s comment:

My main complaint about using the “short-selling” terminology in prediction markets, is that it uses a term from finance that describes a complicated scenario to describe a simple scenario it doesn’t apply to. In financial markets, short selling means that you accrue money in order to take on a conditional obligation. When you bet against a proposition (on InTrade, Foresight Exchange or (I think) Inkling), you spend money and gain a conditional asset. In the prediction market case, you don’t have any further obligation- there’s no possibility of a margin call. The asset has a non-negative value.

I actually think the way NewsFutures describes binary outcomes is the simplest. They never talk about selling unless you already own the asset. If you don’t own any of the asset, you can either buy it, or click a button to see the opposite view, which you can also buy. They don’t have “yes” and “no”, they just have complementary wordings and titles for opposing outcomes.

Go reading all the comments, there.

How to set Reverse IP Lookup to anything that you like (or dislike, should I say, in this case)… including a NewsFutures server that does not exist in reality…!!!…

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Dear readers,

Now is time to give you some background information about last week&#8217-s incident. As you all know, somebody was irked by what I said about the EPM software vendors and set up, not one, but two websites denigrating moi.

#1. I don&#8217-t care if someone makes a fool of moi. I am fair game. Plus, it gives a laughing opportunity to the Chief Economist of Midas Oracle, because it is revenge for my making fool of him when he is so wrong about the article in The Economist or else (follow the HubDub link given by Mike Linksvayer).

#2. My big concern with that attack is that it might well come from somebody I know &#8212-and who has always had the kindest words for me (including last week). So, that person might well be a hypocrite, and my trust in him (and his prediction market company, if any) will be wiped out, if my suspicion is confirmed.

#3. My secondary concern is that that attacker (who might well be a prediction market software vendor or a disgruntled employee) tried to put the blame on NewsFutures (both a prediction market software vendor and a public prediction exchange) for the 2 websites (&#8221-Chris F. Masse is a Fraud&#8221-, and &#8220-Overcoming Midas&#8221-). Just after that the 2 websites were discovered (by one innocent reader, who simply followed the web link posted by a commenter, &#8220-The Colonel&#8221-), many people e-mailed me to tell that I should do a &#8220-reverse IP lookup&#8220- to find out who is behind&#8230- I did&#8230- The result was & I was very surprised to see NewsFutures involved in this attack, and I sent the link to Emile Servan-Schreiber, who, first, expressed astonishment, and then forwarded the link to his CTO (Maurice Balick, some of you know him very well), who is a computer whiz and a master of &#8220-The Internets&#8221- &#8212-as would say former president George W. Bush. :-D

It turned out that:

– NewsFutures sent a &#8220-cease and desist&#8221- letter to the webhost of these 2 websites. Here is a very short excerpt of the NewsFutures letter:

That IP address provides a Reverse-ARP record containing However, we own the domain and we have never authorized anyone to setup this fake RARP record.

– In the meantime, following the brouhaha made on Midas Oracle when the IP address of The Colonel was revealed, the attacker cleared the RARP record during the night so that it no longer pointed to NewsFutures (the non-existent address).

– There are other technical and legal developments to this case, but I am not at liberty to talk further.

– However, I would like to explain to you how it was possible to put the blame on NewsFutures&#8230- even though Emile and his team had nothing to do with this attack.

The Reverse IP Lookup is so easy to fudge that it&#8217-s totally meaningless. It&#8217-s something that prediction market people should know about, so that, in the future, they would not be fooled into drawing conclusions from this kind of &#8220-evidence&#8221-.

To understand how one could fraudulently make a reverse IP lookup point to a domain, Emile and Maurice bought a $20 slice on the webhost where the and websites were hosted. The hosting service then lets you set the &#8220-reverse DNS&#8221- to any URL that you like, and within a few seconds the Reverse IP Lookup tool on iWebTools will point to the URL that you chose. As an example (and as a blink-blink sign to Mike Giberson and Mike Linksvayer), Emile and Maurice made the IP point to &

Try it:


CONCLUSION: Someone tried to incriminate NewsFutures (and fuck with our readers&#8217- mind) by setting up these agressive websites and having the Reverse IP Lookup point to a fake NewsFutures URL.


Did the attacker try to pin it on, not just one, but *two* prediction market software vendors?

Prediction markets compute facts and expertise quicker that the mass media do.

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Political prediction markets react (with a small delay) to political polls &#8212-just like the political experts and the mass media do, too. Hence, in order to discover their true social utility, the prediction markets (which are tools of intelligence) should not be compared to the polls (which are just facts) but to the similar meta intelligence mechanisms (the averaged probabilistic predictions from a large panel of experts, or the averaged probabilistic predictions from the political reporters in the mass media, or else). My bet is that, in complicated situations (such as the 2008 Democratic primary), the prediction markets beat the mass media (in terms of velocity) &#8212-even though the prediction markets are not omniscient and not completely objective (but who is?).

You might remember the research article that I have blogged about:

Learning in Investment Decisions: Evidence from Prediction Markets and Polls – (PDF file) – David S. Lee and Enrico Moretti – 2008-12-XX

In this paper, we explore how polls and prediction markets interact in the context of the 2008 U.S. Presidential election. We begin by presenting some evidence on the relative predictive power of polls and prediction markers. If almost all of the information that is relevant for predicting electoral outcomes is not captured in polling, then there is little reason to believe that prediction market prices should co-move with contemporaneous polling. If, at the other extreme, there is no useful information beyond what is already summarized by the current polls, then market prices should react to new polling information in a particular way. Using both a random walk and a simple autoregressive model, we find that the latter view appears more consistent with the data. Rather than anticipating significant changes in voter sentiment, the market price appears to be reacting to the release of the polling information.

We then outline and test a more formal model of investor learning. In the model, investors have a prior on the probability of victory of each candidate, and in each period they update this probability after receiving a noisy signal in the form of a poll. This Bayesian model indicates that the market price should be a function of the prior and each of the available signals, with weights reflecting their relative precision. It also indicates that more precise polls (i.e. polls with larger sample size) and earlier polls should have more effect on market prices, everything else constant. The empirical evidence is generally, although not completely, supportive of the predictions of the Bayesian model.


You might also have watched Emile Servan-Schreiber&#8217-s videos. Emile is a smart man, and those videos are truly instructive.

  1. In the first part (the lecture), our good doctor Emile Servan-Schreiber sold the usual log lines about the prediction markets &#8212-blah blah blah blah blah.
  2. In the second part, Emile Servan-Schreiber took questions from the audience in the room. &#8220-Aren&#8217-t political prediction markets just following the polls?&#8221-, asked one guy. Emile&#8217-s answer was long and confused. However, in my view, Emile actually did answer that question (before it was ever asked) in his preceding lecture when, at one point, he made the point that the media were slower than the prediction markets to integrate all the facts about the 2008 Democratic primary, around May 2008. That is the right answer to give to a conference attendee who enquires about prediction markets &#8220-following&#8221- the polls. Both the mass media and the prediction markets do follow the polls (since the polls are facts that can&#8217-t be ignored), during political campaigns. Let&#8217-s compare the prediction markets with the mass media, instead, and let&#8217-s see who&#8217-s quicker to deliver the right intelligence..

Lance Fortnow gives a good insight about the relationship between polls and prediction markets (see his last paragraph).

Yesterday the Electoral College delegates voted, 365 for Barack Obama and 173 for John McCain. How did the markets do?

To compare, here is my map the night before the election and the final results. The leaning category had Obama at 364. The markets leaned the wrong way for Missouri and Indiana, their 11 electoral votes canceling each other out. The extra vote for Obama came from a quirk in Nebraska that the Intrade markets didn&#8217-t cover: Nebraska splits their votes based on congressional delegations, one of which went to Obama.

Indiana and Missouri were the most likely Republican and Democratic states to switch sides according to the markets, which mean the markets did very well this year again. Had every state leaned the right way (again), one would wonder if the probabilities in each state had any meaning beyond being above or below 50%.

Many argue the markets just followed the predictions based on polls like Nate Silver&#8217-s True to a point, Silver did amazingly well and the markets smartly trusted him. But the markets also did very well in 2004 without Silver. [Chris Masse’s remark: In 2004, (another poll aggregator) was all the rage.] One can aggregate polls and other information using hours upon hours of analysis or one can just trust the markets to get essentially equally good results with little effort.

The polls are facts. Prediction markets are meta to facts. Prediction markets are intelligence tools. Let&#8217-s compare them with similar intelligence tools.

Lance Fortnow&#8217-s post attracted an interesting comment from one of his readers:

to provide an exciting collection of political and other prediction markets.

These markets are as much a &#8220-prediction&#8221- tool as a wind vane or outdoor thermometer are. They moved up and down according to the daily trends, with very little insight of the longer place phenomena underlying them.

When the weather was hot (Palin&#8217-s nomination announcement) the market swinged widely towards McCain, while ignoring the cold front on the way here (the economic recession + Palin inexperience).

The value of weather forecast is in telling us things we didn&#8217-t know. We don&#8217-t need to trade securities to believe that if McCain is closing on the polls then his chances of wining are higher (duh!), which is what the markets did. We need sophisticated prediction mechanisms to tell us how the worsening economic conditions, the war in Iraq and Palin ineptitude (which in pre-Couric days wasn&#8217-t as well established) will impact this election, today poll&#8217-s be damned.

Looking at the actions by the republican teams, who were trying to read past the daily trend all the way to November 4th, it is clear that they thought all along they were losing by a fair margin. Because of this is they choose moderate, maverick McCain, went for the Palin hail mary fumble^H^H^H^H^H pass and the put-the-campaign-on-hold move.

A full two weeks before the election the McCain team concluded the election was unwinnable, while the electoral college market was still giving 25-35% odds to McCain.

As highlighted in bold, the commenter says two things:

  1. The prediction markets are just following the polls.
  2. The prediction markets have a minimal societal value.

My replies to his/her points:

  1. That&#8217-s not the whole truth. The polls are just a set of facts, whereas the prediction markets are intelligence tools that aggregate both facts and expertise. The commenter picks up a simple situation (the 2008 US presidential election) where, indeed, anybody reading the latest polls (highly favorable to Barack Obama) could figure out by himself/herself what the outcome would be (provided the polls wouldn&#8217-t screw it).
  2. That&#8217-s true in simple situations, but that&#8217-s wrong in complicated situations (such as the 2008 Democratic primary).

The emergence of the social utility of the prediction markets will come more clearly to people once we:

  1. Highlight the complicated situations-
  2. Code the mass media&#8217-s analysis of those complicated situations, and compare that with the prediction markets.


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Collective Intelligence – Prediction Markets – NewsFutures

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Emile Servan-Schreiber of NewsFutures

YouTube videos:






Q&#038-A 1: Aren’t political prediction markets just following the polls?


Q&#038-A 2: Why did prediction markets fail to predict the lack of weapons of mass destruction in Irak?


Q&#038-A 3: Would market predictions still be accurate if everyone believed them?


Q&#038-A 4: Is Democracy ready for prediction markets?


Q&#038-A 5: How can trading prices translate into probabilities if individual traders don’t trade accordingly?

The one thing I enjoy every Monday morning

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As a prediction market aficionado, what lights me up are stories about&#8230- (of course)&#8230- how the prediction markets are assessing important news. The HubDub blog publishes, every Monday morning, a post that rounds up the 5 most prominent (that&#8217-s subjective) news stories of the week, with the prediction market charts, so we can spot which outcome is the more likely, for each issue.

I find this weekly newsletter addictive. I read it with attention each Monday. It is simple, short, but well done and effective.

I wish InTrade, BetFair, and NewsFutures would publish such a prediction market blog.

Are prediction markets useful?

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According to Alan Abramowitz, John Tierney has been &#8220-greatly exaggerating the accuracy of the betting markets.&#8221- &#8220-They follow the polls. That’s it.&#8221-

My comment to Alan Abramowitz and John Tierney:

&#8220-They follow the polls. That’s it.&#8221-

Yes, they follow the polls. No, that&#8217-s not it.

Traders also dig the news of the day and make anticipations about the outcome. For instance, towards the end of the 2008 Democratic primary, the polls and the mass media were still giving Hillary Clinton a very good standing, whereas the prediction markets (informed by a bunch of political experts who did the counting of the delegates and super-delegates) were telling us that she was as toasted as Lehman Brothers in the middle of the credit crunch crisis.

Are prediction markets useful? If John Tierney wants to answer this question, he should pick up a prediction market and put it in the social context of that day. Some prediction markets are more useful than others. In the case of the 2008 Democratic primary (a complicated matter), the prediction markets sided with the best informed political experts against the mass media and the polls. So to speak, they were an umpire. In that case, we see the emergence of a social utility. We now have the case for the media citing more the probabilities of the liquid (play-money and/or real-money) prediction markets.

Previously: #1 – #2 – #3 – #4 – #5

External Link: Club of Growth

The fact that Emile Servan-Schreiber (usually, a smart man) treats the 2008 US presidential elections, as seen thru the lens of the NewsFutures prediction markets, so lightly, making it a race of spermatozoids swimming their way to the Oval Room, shows you that the prediction market luminaries are i

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Download this post to see the NewsFutures widget below.

The Objectivity -according to BetFair

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BetFair Predicts (a blog run by BetFair) titled &#8220-The Power Of Objectivity&#8221- a post giving the latest odds produced by BetFair on the race for the White House.

The real &#8220-objectivity&#8221- would have been to quote the odds produced by the other prediction exchanges, too &#8212-InTrade, Iowa Electronic Markets, Betdaq, NewsFutures, HubDub, etc.

Midas Oracle is the only blog that lists prices and probabilities from all the prediction exchanges. No wonder, our daily readership is much, much bigger than the audience of all the other prediction market blogs combined. A blog that gives the odds of one exchange only is like a dead end &#8212-no one trusts a dead end.

Please, do support Midas Oracle.

The proper way to predict Obamas electoral vote count

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I&#8217-m puzzled by the way Intrade projects the electoral vote count on its home page. Two methods are proposed: (a) add up the votes of all the states that are &#8220-leaning&#8221- (&gt-50%) for a candidate, or (b) compute a price-weighted average. The latter is obviously meaningless because electoral votes are winner-take-all in pretty much every state.

But what about the &#8220-leaning&#8221- method? Well, it only makes sense if you believe that market prices do not represent probabilities. In fact, the &#8220-leaning&#8221- method treats the 15 electoral votes from a swing state like North Carolina (65% chance to go blue) the same way it treats the 15 votes from a true-blue state like New Jersey (95% chance to go blue), tossing them both equally in the Obama column.

Now, Intrade has been known to want it both ways: interpreting its prices as probabilities most of the time, but then also claiming that it correctly predicted all 50 states in 2004 because all the contracts priced over 50% eventually expired at 100%. This claim conveniently ignores the fact that if prices are probabilities, then at least some of the states priced &#8220-red&#8221- or &#8220-blue&#8221- over 50% should in fact have gone the other way on election day.

It may very well be that, given the 2004 data, the prices of election markets (on Intrade and elsewhere) should not be interpreted as probabilities. Perhaps our academic friends can come up with another meaningful way of looking at those prices. But in the meantime, assuming the price/probability correlation holds, the proper way to project the electoral vote count from the market prices is to run monte-carlo simulations based on individual state prices.

Here&#8217-s an example using this morning&#8217-s prices on NewsFutures. The histogram shows the results of 1 million simulated elections where each state goes red or blue according to its market-derived probability of doing so. Note how the &#8220-most likely&#8221- outcome, 364 votes for Obama – which is the number the &#8220-leaning&#8221- method would report – is at the same time very unlikely with just 5% chance of happening.