I have been chatting with a prediction market practitioner (I won’-t tell you who, and no, it’-s not whom you think of) —-shooting the breeze, and talking about the current state of the prediction market industry…- taking about things and people…- talking up some people…- and badmouthing others ( ).
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At the end, the conversation barged on the issue of “-advisory boards“-. And he told me that Robin Hanson and Justin Wolfers have helped him TREMENDOUSLY —-in terms of solving problems with new software features, case studies, applied research, etc.
Any Wikipedian out there willing to start off his page?
http://en.wikipedia.org/wiki/Justin_Wolfers
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Robin Hanson, Tyler Cowen, Steve Levitt, and even Don Luskin and Robert Scoble, have their own Wikipedia entry. Why not Wolfers???…- I realized that when I updated my “-acknowledgments”- page:
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Acknowledgments
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– Friedrich August Von Hayek (an economist who introduced, among other things, the concept of the market as an information aggregation tool in The Use of Knowledge in Society, and the 1974 co-winner of the Nobel Prize in economics)-
– Professor Vernon Smith (an experimental economics pioneer, and, as such, the 2002 co-winner of the Nobel Prize in economics)-
– Professor Robin Hanson (one of the contemporary co-inventors of the prediction markets)-
– Doctor James Surowiecki (author of The Wisdom Of Crowds)-
– Professors Justin Wolfers and Eric Zitzewitz (meta analysts of the prediction markets)-
– Professor Steve Levitt (co-author of Freakonomics)-
– Professor Tyler Cowen (co-author of Marginal Revolution and author of Discover Your Inner Economist)-
– Donald Luskin (author of The Conspiracy To Keep You Poor And Stupid)-
– The GNU, Linux, WordPress, World Wide Web Consortium, Mozilla, Opera, Yahoo!, Google, Wikipedia, Creative Commons and Free Software Foundation people (among others) for freeing our information-based society.
My yesterday’-s post about the Obama–-Clinton prediction markets was the most popular Midas Oracle story of that Monday. Hummmm…- No idea why…- I was not helped by Google Search or by an external blogger. Sounds like our Midas Oracle web readers and feed subscribers liked it …- for some reasons I have yet to discover fully.
Anyway.
I’-m minding a grand “-Midas Oracle Project“-, and you can join it.
The idea is this: We need to put the charts of prediction markets inside news stories, and those stories should incorporate the meaning of the probability fluctuations (a la Justin Wolfers).
I don’-t think that much will come out of the prediction exchanges. The BetFair blog and the InTrade newsletter are 2 pieces of crap —-they compete in content quality with the Mongolian edition of the News Of The World.
If you look at the evolution of the media, you see that the old-school, dead-tree publications are slowly dying, and are replaced by professional blog networks —-look especially in the IT industry, with TechCrunch, etc. What you have is writers who publish only for the Web, and who fill a vertical niche. (And, the Washington Post is now publishing content from…- guess who.)
Needless to say, prediction market journalism is costly. Now, go directly to point #8, because that’-s where the beef is.
Yes, I have “-heard of Christmas”- , and I understand Robin Hanson’-s reasoning. [*] That’-s where my funding idea lays. The idea is to think hard about who “-might actually be willing to pay”-. I am thinking of a class or organizations that “-might actually be willing to pay”-, provided 2 things. Number one, that I operate a certain twist on my form of prediction market journalism. Number two, that this project becomes the project of many prediction market people, or, better, of the whole prediction market industry —-not just Chris Masse’-s one. Those 2 things are essential.
Chris, you’ve heard of Christmas I presume. Many people circulate lists of items they might like for Christmas. If you did, would you circulate a list of million franc/dollar gift ideas for people to give you? Would you consider that list more honest/logical than a list of gifts of roughly the price you think others might actually be willing to pay?
Via Emile Servan-Schreiber of NewsFutures, John Auters in the Financial Times.
[…] This leads to [Justin Wolfers]‘- claim that [prediction markets] are the best way to aggregate information. This is true of any given amount of information. Take three economists and make them trade out a market over their predictions for next month’-s inflation number, he suggests, and they will arrive at a more accurate prediction than a poll of the same three economists. In a market, those with stronger conviction (or inside information) can express that conviction- those less confident will not be willing to stake money. […]
Prediction markets remain subject to the same weaknesses as other markets. The principle of “-garbage in, garbage out”- [*] applies. If there is only poor information to aggregate, they will be as wrong as everyone else. […]
It would make sense to incorporate these odds when making investments. […]
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Excellent.
(I don’-t get his micro slam against the wisdom of crowds. Anyway.)
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[*] As explained in the prediction market explainer published on the frontpage of Midas Oracle.
Freakonomics, the famous blog on economics, is powered by WordPress, which is known [*] to have grave security vulnerabilities. Yesterday, a dangerous hacker managed to get access to their blogging software, and published an opinion on the regulation of prediction markets, which represents the total opposite of what Steve Levitt believes in. No doubt the hacker (who signed as “-The Australopithecus“-) will get caught by the Police. No doubt Steve Levitt will get out of his torpor soon and re-establish the truth. We will then give airtime to Steve Levitt’-s arguments, on Midas Oracle. We’-re with you, doctor Levitt.
[*] I know that for a fact. Midas Oracle was hijacked yesterday by a dangerous hacker who signed as “-The Barbecue”-. I’-m not responsible for what he said.
Some of our academics, consultants, and exchange executives have sold the prediction markets as the ultimate forecasting tool —-which is true, but people translated that as “-this is an omniscient tool for forecasting”-–
The best usage of the prediction markets is that they do average what the experts think (see Justin Wolfers’- mention of a “-useful counterweight”-) —-but that’-s a far cry from being an omniscient oracle (which is what people are expecting).
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Some people would enjoy the usage of a “-useful counterweight”- —-but not that many.
The “-useful counterweight”- thing is not a hot-selling proposition.
You don’-t draw crowds with that.
You draw crowds with an over-selling proposition.
You draw crowds by manufacturing hype.
As a result of the collective intelligence of more than 77,000 bettors on Intrade, the prices on the site may be a good way to predict the outcome of current events —- more accurate than some polls and pundits. In 2004, the market odds on Intrade predicted the presidential vote of every state but Alaska. In 2006, the odds correctly indicated the outcome of every Senate race.
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Our Explainer On Prediction Markets
Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that traders bring when they agree on prices. Prediction markets are meta forecasting tools that feed on the advanced indicators (i.e., the primary sources of information). Garbage in, garbage out…- Intelligence in, intelligence out…-
A prediction market is a market for a contract that yields payments based on the outcome of a partially uncertain future event, such as an election. A contract pays $100 only if candidate X wins the election, and $0 otherwise. When the market price of an X contract is $60, the prediction market believes that candidate X has a 60% chance of winning the election. The price of this event derivative can be interpreted as the objective probability of the future outcome (i.e., its most statistically accurate forecast). A 60% probability means that, in a series of events each with a 60% probability, then 6 times out of 10, the favored outcome will occur- and 4 times out of 10, the unfavored outcome will occur.
Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism.
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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.
Lawrence O’-Donnell (a leftist journalist –-but a good one, whom I appreciate):
A senior campaign official and Clinton confidante has told me that there will be a Democratic nominee by June 15. […] Yes, Clinton spokespersons publicly seem to be lost on gravity-free planet Clinton, but privately they know the end is near.
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There’-s a quasi consensus among the political pundits to say that Hillary Clinton will not be the Democratic nominee in November 2008.
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Tim Russert:
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That was Wednesday night. I have just watched NBC Nightly News this Thursday, and the same Tim Russert appeared with 2 white boards full of calculations, which all pointed to Hillary Clinton being toasted.
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My general thoughts about the place of the political prediction markets in this primary election season:
The weight of the political prediction markets in the US political scenery is close to epsilon. I have been monitoring Memeorandum (the Web’-s best political news and opinion aggregator), and it has never featured one piece of political prediction market journalism —-not only that, but none of the popular popular pieces, featured by Memeorandum, has ever mentioned the political prediction markets and their probabilities. The people who breathe politics on a daily basis (the experts and the bloggers) don’-t give the first fig about the prediction markets. They couldn’-t care less.
The prediction market luminaries who predicted that the prediction markets were to become a tool used in political campaigns were dead wrong. I have never read that campaign staffers use actively the political prediction markets. Campaigns use private polls, only.
Like in 2004 (when Howard Dean was crowned, early on), the prediction markets, at the start of the primary season, were incapable of foreseeing who would be each party’-s nominee, ultimately —-Barack Obama and John McCain both came out of the blue. But the polls and the political experts didn’-t see them, too.
Nothing surprising in that. While the idiots emphasize the supposed magical power of the prediction markets (using adjectives such as “-fascinating”- or “-intriguing”- when writing about them), the well informed people know for a fact that they simply aggregate information from the primary, advanced indicators and the opinions expressed by the political experts. Nothing more than that. The prediction markets are incapable of foretelling upsets, by essence.
The last weeks were particularly interesting, in that regard, because the Obama-vs-Clinton polls have been of no interest —-only the views of the political experts who could count in terms of delegates and super-delegates were of interest. The political prediction markets on the Democratic side, these last weeks, have been a reflection of the pundits’- calculations.
Outside of our blog, the only person who has aimed at practicing prediction market journalism is Justin Wolfers. He has understood the concept.
I would have my own concept of prediction market journalism, and I don’-t agree with the way he executes, but that’-s a detail. The main thing is that he has gotten the concept. That’-s what is important, and that’-s what makes all the difference between Justin Wolfers and the HubDub bloggers (for instance). The concept. The concept. The concept. The idea is to center the narrative around the inputs given by the relevant prediction market(s) —-not just gluing artificially news bits and a prediction market chart (or a link to a prediction market).
InTrade, BetFair and NewsFutures are, in my view, the 3 prediction exchanges that matter for prediction market journalism —-as of now.
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Now, the charts of the expired prediction markets —-starting with Pennsylvania (of 2 weeks ago):
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Yesterday’-s North Carolina:
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Yesterday’-s Indiana:
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Sources: InTrade &- BetFair
(Go there for the remaining primaries and caucuses. I don’-t put them on, here, because they don’-t matter anymore.)
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Now, the charts of the prediction markets, going forward:
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2008 US Presidential Election Winner – Individual
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2008 US Presidential Elections
Source: Dynamic, compound prediction market charts from InTrade
Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that traders bring when they agree on prices. Prediction markets are meta forecasting tools that feed on the advanced indicators (i.e., the primary sources of information). Garbage in, garbage out…- Intelligence in, intelligence out…-
A prediction market is a market for a contract that yields payments based on the outcome of a partially uncertain future event, such as an election. A contract pays $100 only if candidate X wins the election, and $0 otherwise. When the market price of an X contract is $60, the prediction market believes that candidate X has a 60% chance of winning the election. The price of this event derivative can be interpreted as the objective probability of the future outcome (i.e., its most statistically accurate forecast). A 60% probability means that, in a series of events each with a 60% probability, then 6 times out of 10, the favored outcome will occur- and 4 times out of 10, the unfavored outcome will occur.
Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism.
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More Info:
– The Best Resources On Prediction Markets = The Best External Web Links + The Best Midas Oracle Posts
– Prediction Market Science
– The Midas Oracle Explainers On Prediction Markets
– All The Midas Oracle Explainers On Prediction Markets
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Previous blog posts by Chris F. Masse:
Prediction Markets
Meet professor Justin Wolfers.
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.
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