Don’-t you love the Web? Within 15 minutes after my posting my absolute and definitive refusal to publish any bits about the VP prediction markets, I received a long rebuttal by Google’-s Bo Cowgill —-whose great prediction market paper is still for you to download (PDF file), by the way.
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.
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.
1. She lost the delegate derby. 2. She essentially tied Obama in the popular vote. 3. She lost more states. 4. She lost the January cash war. 5. The calendar is her enemy.
1. It really was an upset – As it has been pointed out elsewhere, the Clinton victory was a surprise to everyone. Favorites can lose. But so what? Ordinarily, that’s not a market flaw or a reason to doubt the odds shown in the market.
Justin Wolfers article in the WSJ had the best summary:
Against this background, it is no exaggeration to term the result truly historic. Not that there haven’-t been more dramatic upsets or come-from-behind wins that carried more significance —- this was just an early primary, albeit a pivotal one. But in terms of unpredictability, or at least the failure of everyone to predict it, it may have no modern match. … Historical comparisons are already being drawn between the New Hampshire primary and the famous 1948 presidential race…Yet the magnitude of the Clinton surprise is arguably even greater…-Thus, Sen. Clinton’-s victory on Tuesday was more surprising than President Truman’-s in 1948.
Given the above, were the Clinton prices on Intrade very far off? It’-s not obvious that they were.
2. Pundits/Critics are NOT traders – If I believe a contract should be trading around 30 and I see it trading at 7, it would make my day. As a trader, seeing a contract that is clearly mispriced is a good thing. Traders who remember the French politician Le Pen’s strong showing in 2002 vs his polls or who read Steve Sailer’s blog should not be surprised that people are dishonest with pollsters. However, to a pundit, an isolated incident of mispricing means the entire concept of prediction markets is faulty.
Since NH results, pundits have been asking, “Are prediction markets flawed?” The traders who make and move the market don’t believe so- they are trading more than ever. In any case, there were no postings on the 7th of January about how wrong the prediction markets are, only after-the-fact postings demonstrating perfect 20/20 hindsight. Traders, not critics, will determine the success of the prediction markets.
Let us not forget that pundits have an agenda too. For some, especially political ones, they need to present themselves as being able to offer insight that no one else has. Since prediction markets allow events to be quantified in real time, the pundits have less to add. This makes critics especially eager to take some of the shine off prediction markets and make themselves look smarter by comparison.
Additionally, there is a contingent of commentators and bloggers with an anti-market bias who delight in seeing any market based tool be wrong. They will be the first to loudly smear PM errors but no where to be found when the market turns out to be right.
3. PMs are not polls – This common mistake is exemplified by this quote from the Chicago Tribune, “The New Hampshire primary was a reminder that prediction markets, where bettors are putting money on the line, can have no more value than opinion polls, where participation costs nothing.” This critic missed the point and doesn’-t realize he is comparing apples and oranges.
Most commentators have focused on the accuracy of the market prices without touching on the underlying purpose of the market: speculation and hedging. Even if the polls are no more accurate than the market, they still can’t be used for trading functions.
4. Regulations have hurt the accuracy and liquidity of PMs – The inconvenience of opening a trading account at Intrade has excluded many Americans from participating. What is the cost of accuracy to the PMs? Surowiecki’s The Wisdom of Crowds lists four factors necessary for a wise crowd: diversity of opinion, independence, decentralization, and aggregation. At least two of these have been highly restricted due to regulations. Even so, the market is usually more accurate than the polls. None of the critics has pointed out that with so many potential traders cut off from trading, the market is surely excluding informed participants.
5. “Serious people who study or work with these markets are not in the ‘-markets are magic’- camp” – Prediction markets are like other financial markets: fat tails, black swans, bubbles, “manipulations” etc. These are all visible in housing, equities, and fixed income markets as well and no one speculates about the end of those instruments. As Eric Zitzewitz pointed out, the “markets are magic” crowd is just a strawman and not a logical basis to attack prediction markets.
Why were the political prediction markets so wrong about Barak Obama and Hillary Clinton in New Hampshire?
…-asks Slate’-s Daniel Gross —-via Mister Usability (Alex Kirtland), who needs to go and get his own gravatar.
So, I’-ve been watching the action in one of the political futures markets this evening, Intrade. And the action in this prediction market has reinforced my opinion that these are less futures markets than immediate-past markets. The price movement tends to respond to conventional wisdom and polling data- it doesn’-t lead them.
Throughout the day and into the early evening, while polls were still open, Democratic investors, mimicking the post-Iowa c.w. and polls, believed Obama was highly likely to be the Democratic nominee. The Obama contract was trading in the lows 70s, meaning investors believed he had a 70 percent chance of being the nominee, while Hillary Clinton contracts were in the 20s. […] At 6 p.m., this market had written Hillary Clinton’-s entire presidential campaign off. At 9:30 p.m., it was calling a dead heat. What caused investors to change their minds so drastically in the space of a couple of hours? A few data points that went against the day’-s prevailing conventional wisdom and polls. […]
See also Niall O’-Connor’-s assessment:
I am looking forward to the post New Hampshire Caucus, when all you prediction market advocates crawl out from under your stones. For the record at one point the market on Intrade and Betfair was suggesting that Obama had a 95% probability of winning the caucas- whilst Intrade had him at 77% to win the nomination.A case perhaps of both the foolery of crowds and, the market biting back.
New Hampshire will go down as the Black Wednesday of prediction markets and unless there is now objective transparent debate (as opposed to the usual biased sabre rattling) – prediction markets will be dead in the water.
My answer to Dan Gross’- legitimate question and to Niall O’-Connor’-s snarky comment:
Prediction markets are forecasting tools of convenience that feed on advanced indicators. When those advanced indicators are wrong, the prediction markets are wrong.
If you prefer the polls or the pundits, your call —-but polls and pundits were also wrong, this time, right? Required reading for mister Niall O’-Connor: “-New Hampshire’-s Polling Fiasco”- + “-Analysis: pundits eat crow“-.
The ultimate forecasting tool would be a way to reverse our psychological arrow of time —-so as to remember the future instead of the past. Only science-fiction writers and some imbecile ( ) believe in that.
The prediction market approach is to stick with the markets, on the long term. Take their successes. Take their failures. Unlike Donald Luskin and Markos Moulitsas, Chris Masse will not turn against the prediction markets when they fail punctually. What counts is the long series.
My first point should be included in the prediction markets approach definition, in my view, but others (like economist Michael Giberson) might have different opinions.
With respect to my first point, I bet that the prediction markets will never replace the polls as the forecasting tool of choice for political analysts —-on that particular point (but not on a myriad of others), I break away from Justin Wolfers’- irrational exuberance and I side with Emile Servan-Schreiber of NewsFutures (my preferred play-money prediction exchange). Prediction market reporting will have a function, indeed (as suggests Justin Wolfers), but not the dominant function.
Going forward, prediction market journalism should emphasize relative accuracy (as opposed to absolute accuracy) —-that is, comparing prediction markets with polls and pundits, which is what Robin Hanson has said from day one. Our good friend Niall O’-Connor has difficulty to compute that, apparently. He should eat more fish.
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Justin 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.”
Emile Servan-Scheiber:
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’t so easily reproducible elsewhere. I’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’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’ve observed in France and Holland is that it it’s very hard to beat the accuracy of such projections.
[I don’t make mine Emile Servan-Schreiber’s second point, but that’s a minor.]
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InTrade’-s expired prediction markets:
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New Hampshire
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The Democrats
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The Hillary Clinton event derivative was expired to 100.
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The Republicans
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The John McCain event derivative was expired to 100.
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Iowa
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The Democrats.
The Barack Obama event derivative was expired to 100.
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The Republicans
The Mike Huckabee event derivative was expired to 100.
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Source: InTrade
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[A more complete prediction market reporting should have included expired contracts from NewsFutures and BetFair. Sorry for that. Note that InTrade-TradeSports is the only exchange to offer a “closed contacts” section.]
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NEXT: Prediction Markets 101 + Who did best in explaining the prediction markets to the lynching crowd? + After the New Hampshire fiasco, 16 people came to defend the prediction markets, so far. + The prediction markets deserve a fair trial. + Prediction Markets = the greatest time-saving invention of this century
[…] Through this process of different people trading based on their own observations about the race, prediction markets prices come to aggregate disparate pieces of information into a single summary measure of the likelihood of various outcomes. Moreover, if this market operates efficiently, it will appropriately summarize all of this information and the price will become the most statistically accurate forecast of the election outcome. […]
If I may, I would like to jot down some thoughts related to my concept of prediction market journalism.
The explainer on prediction markets is pretty good.
WSJ did list (in one of the sidebar boxes) BetFair along with InTrade —-good point.
WSJ didn’-t list NewsFutures and Inkling Markets but listed their own play-money, bots-driven prediction exchange (WSJ Political Market) —-bad point (conflict of interest).
No external links embedded in Justin Wolfers’- text —-there are very good resources listed in the sidebar boxes, though (but the links use JavaScript and are not direct).
No static or dynamic prediction market charts, even though Justin Wolfers spent a good deal of air time analyzing the recent prediction market events —-a concept he formalized with Eric Zitzewitz.
No tips —-”-I can’-t predict what these trends will be […]“-. Sounds like the prediction market approach (declaring that the market is a better forecasting tool than the polls or the experts) kills any anticipation and scenario planning. It shouldn’-t be like that. Prediction market journalism can’-t be only about analyzing the past. More on that in the coming weeks on Midas Oracle —-not in the WSJ.
For all these reasons, I can give more than a straight B to Justin Wolfers’- copy. You can do better than that, prof.
In financial markets there is strong evidence to suggest that news gets priced into markets within 15 minutes of its release and sometimes even more quickly. Recent research into prediction markets suggests that they aren’t nearly as efficient with researchers from University of Pennsylvania showing that prices on IEM can be predicted using public news flow.
Doing a simple analysis of some the key events in the 2008 Presidential Elections against prices on Intrade shows that on discrete events there is a clear relationship between prices and news flow. However over longer periods the relationship is not always clear.
On the 4th of March CBS announced the results of a straw poll conducted at the conservative PAC convention in Washington DC. They picked Romney as their favourite. Romney’s price on Intrade lifted immediately where it stayed for about a week.
On the 11th of April the Fred Thompson revealed on Fox News and ABC Radio that he had been diagnosed with non-Hodgkin’s lymphoma nearly three years prior. The New York Times and other publications picked up the story the next day. Looking at his price chart shows he opened on the 12th of April at 19 but then closed at 15. The next day he opened at 11.2 but then closed at 17, as the story died down.
In both these cases, the news stories the media considered to be the important ones correspond with the news flow that traders thought was important.
However, the most interesting market movement of the year must be the Obama August slide. On the first of August Obama opened on Intrade at 35.5 but by the 24th of that month he had slide to 17.2. He continued sliding hitting a rock bottom of 10.7 on the 14th of October.
The question is what was the news flow on Obama from the 1st of August to the 24th of August? Analysing the news articles in the New York Times suggests a disconnect between what was reported and how the market was reacting. Obama started August badly with a bungled comment on use of nuclear weapons.
Additionally, his continued line that stabilisation of Iraq had been a ‘complete failure’ may also have cost him some points.
However in sum these news items don’t seem to correlate with an 18 point slide. This could lead us to two possible conclusions:
The New York Times didn’t report the most market sensitive news affecting Obama in August
Obama was over-sold in August and his price did not reflect his true value
I’-m happy to report the launch of the Yahoo! Election ‘-08 Political Dashboard. Using the dashboard, you can navigate through a wealth of election-related data, including prediction market data from intrade.com, polling data from Real Clear Politics, search buzz data from Yahoo!, and financial contributions data, regional demographic data, and historical voting records from AP. You can view the election landscape from the national level or dive in deeper to investigate trends state by state.
Yiling, Tej, Lance, and I played supporting roles among a cast that includes fantastic teams at Yahoo! News, UI/Design, Ops, Q&-A, and more.
We’-ve come a long way since 2006.
See also coverage from TechCrunch and the Yahoo! corporate blog.
Previous: From Chris “-Outrageous Spin”- Masse.
) believe in that.
