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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Why InTrade CEO John Delaney, TradeSports acting CEO John Delaney, BetFair CEO David Yu, HubDub CEO Nigel Eccles and NewsFutures CEO Emile Servan-Schreiber should supplicate me to develop my prediction market journalism project

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200 web visitors (coming from Google) reached my John Edwards post, published yesterday afternoon (ET).

10% of them followed my links to the 2 HubDub prediction markets on John Edwards.

Remember that those web stats count only the web visitors, not the feed subscribers &#8212-who are more numerous, and whom I focus more on.

TAKEAWAY: A popular PMJ website, which would associate fresh news and betting recommendations, would send many people to the prediction markets.

The mainstream media and the classic bloggers will never deal with real-money prediction markets the way they should be dealt with &#8212-for multiple reasons (moral, ethical, legal, etc.). And for other reasons, they will never link to the play-money prediction markets.

Look Justin Wolfers at the Wall Street Journal: He is the most excited about prediction markets. Yet, he does not link to InTrade directly. He does not link to the InTrade real-money prediction markets. Hence, his blah blah blah does not translate into more revenues for InTrade.

What it takes is a brand-new media organization, entirely devoted to prediction markets, and run by die-hard prediction market people.

Please, guys, help me.

  • cfm |-at-| midasoracle |.|-com-|
  • chrisfmasse |-at-| gmail |.|-com-|

Prediction market journalism cant be practiced by the mainstream media. What we need is a revolution.

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The eyes-wide-opened Alexis Perrier notes that many &#8220-mainstream media&#8221- do talk about political prediction markets, these days.

But that&#8217-s a superficial coverage &#8212-basically, explaining to morons (surfacing from their Afghan cave) what InTrade does. The real thing is prediction market journalism &#8212-and to this day, only Justin Wolfers does practice it (once a month).

To get real PMJ done, we will need brand-new digital publications and brand-new people &#8212-just like the newly created tech blogs (like TechCrunch) are employing a new batch of writers, using new tools and new methods.

If you look at the 87 feeds I subscribe to, I get my IT news from professional blogs &#8212-not from mainstream media.

Prediction market journalism has a future only if professional blogs adopting this approach are to be created.

Columbia Journalism Review not much convinced by Wall Street Journals Justin Wolfers

No GravatarTo say the least.

[&#8230-] Unfortunately, by the eve of the New Hampshire primary, Wolfers was back in the Journal, writing this time that the newspaper’s own prediction market, WSJ Political Marketplace, run by Intrade, was showing that New Hampshire might be the “death knell” for Clinton and a couple other candidates. After a bet like that, in Vegas they’d say, &#8220-craps.&#8221- 

Humm&#8230- I don&#8217-t like this CJR piece, but it shows that many in the non-business press are skeptical of prediction markets.

Read the previous blog posts by Chris F. Masse:

  • I get a kick each morning out of spying on the rich, famous, and powerful people updating their LinkedIn profile and connections. (Go to “InBox”, and click on “Network Updates”.)
  • ??? BetFair bet-matching logic ???
  • Eliot Spitzer has simply demonstrated once again that those who rise to the top of organizations are very often the most demented, conflicted individuals in any group.
  • Business Risks & Prediction Markets
  • Brand-new BetFair bet-matching logic proves to be very controversial with some event derivative traders.
  • Jimmy Wales accused of editing Wikipedia for donations.
  • What the prediction market experts said on Predictify

Care to revise your statement, sir?

No GravatarJustin Wolfers:

In a few years, we may regard the second half of the 20th century as the aberration in which the press used polls rather than markets to track political races,” Justin Wolfers, a business professor at the University of Pennsylvania’s Wharton School, wrote in an e-mail message. “And in the 21st century, we may return to the habits of the early 20th century, reporting on political races through the lens of prediction markets rather than polls.

MP3 file

Previously: Prediction markets are forecasting tools of convenience that feed on advanced indicators.

Read the previous blog posts by Chris F. Masse:

  • Bzzzzzzzzz…
  • Bzzzzzzzzz…
  • “No offense, but I think Radley Balko is the most valuable blogger in America right now.”
  • Are you a better predictor than John McCain?
  • What does climate scientist James Annan think of InTrade’s global warming prediction markets?
  • Inkling Markets, one year later
  • One trader’s view on BetFair’s new bet-matching logic

Prediction Markets as Content, Part 2

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Cross posted from UsableMarkets

Back in April I started talking about how Prediction Markets will be part of many news organizations&#8217- &#8220-citizen-generated&#8221- content strategy going forward.

To quote myself (which seems kind of a rude thing to do, doesn&#8217-t it &#8230-?):

It seems as if no self-respecting news organization can ignore the Web 2.0 movement these days. Many now have some sort of &#8220-wisdom of the crowds&#8221- style content, in addition to RSS feeds, blogs, and so on.

Midas Oracle has covered some of the new relationships that are developing. I recently talked about MarketWatch.

Expect more to happen &#8230- and perhaps quickly, too.

That was nine months ago. Since then we&#8217-ve seen the WSJ, the FT, Reuters, CNN, and others (perhaps everyone can think of a couple or three) begin to dabble in or seriously consider prediction markets. With Inkling and InTrade in the white label prediction market business, the barriers to setting one up are obviously low enough that a certain amount of me-too-ism can easily prevail.

But there is a risk, and those of us who care about the success of the prediction market industry shouldn&#8217-t get too excited about these developments just yet.

First, it remains to be see whether these new prediction markets can attract significant numbers of users. The prediction market industry is already saturated with prediction markets and games. So, despite their powerful brands, I&#8217-m not confident that the FT or the WSJ can attract large followings (although I&#8217-d be happy to be wrong about that).

Ah ha, you may say, we don&#8217-t need a lot of users to generate accurate predictions. The MSR, and automated market makers will help solve the problem. But the problem is not one of generating accurate predictions, but about generating page views. Newspapers (even online) are advertising driven. If you can&#8217-t generate sufficient page views, and you&#8217-re paying too much to manage the prediction market on your site, then it&#8217-s vulnerable to being cut. In fact, I wouldn&#8217-t be surprised if once this US election cycle is over that some of these markets fall away.

And, if the news organizations are really interested in the predictions for predictions sake, they can always simply use someone else&#8217-s.

As always, thanks for listening.
~alex (UsableMarkets)

The Racing Post and TimeForm/BetFair are two competitors in the UK horseracing data publication business.

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The Racing Post and TimeForm compete in the same space- they make money from horse racing data. The Racing Post through its newspaper- TimeForm through its database publications. On the Web, they compete head to head in many respects &#8212-and both give away a certain proportion of their content for free.

The Racing Post model is heavily skewed towards the old betting market model- fixed odds bookmakers- price comparison etc- while BetFair (the new owner of TimeForm) is based on the Web. On top of that, BetFair does not need The Racing Post that much, whereas The Racing Post needs BetFair. The fact that BetFair&#8217-s prices are dynamic (and, 99% of the time, the best prices on offer) fucks up The Racing Post&#8217-s model.

Signed: Deep Throat

External Links: BetFair (the owner of TimeForm) + The Racing Post

Previously: In the UK, BetFair is pushing the bookmakers into the betting museum.