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New Hampshire – The Democrats

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The Hillary Clinton event derivative was expired to 100.

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New Hampshire – The Republicans

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The John McCain event derivative was expired to 100.

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“a handful of methodological missteps and miscalculations combined to undermine the accuracy of predictions about presidential primary winners in New Hampshire and three other states.”

Via Mister the Great Research Scientist David Pennock –who is an indispensable element of the field of prediction markets.

As I blogged many times, prediction markets react to polls… See the addendum below… – [UPDATE: See also Jed's comment.] – Prediction markets should not be hyped as crystal balls, but simply as an objective and continuous way to aggregate expectations. So, if you think of it, their social utility is much smaller than what the advocates of the “idea futures”, “wisdom of crowds” or “collective intelligence” concepts told us. Much, much, much, much smaller… They all make the mistake to put accuracy forward. (By the way, somewhat related to that issue, please go reading the dialog between Robin Hanson and Emile Servan-Schreiber.)

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Addendum

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California Institute of Technology economist Charles Plott:

What you’re doing is collecting bits and pieces of information and aggregating it so we can watch it and understand what people know. People picked this up and called it the “wisdom of crowds” and other things, but a lot of that is just hype.

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New Hampshire – The Democrats

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The Hillary Clinton event derivative was expired to 100.

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New Hampshire – The Republicans

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The John McCain event derivative was expired to 100.

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Nate Silver on November 3rd, 2008:

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Nate Silver on August 21, 2008:

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Today, InTrade CEO John Delaney is trying to milk out this get-rich-quick story (or a similar enough story). His message: You, too, can get rich quick… —what it takes is just registering your credit card with InTrade.

What the InTrade CEO doesn’t tell you is that luck was a factor in Bethan’s sudden enrichment. Nothing wrong with tapping chance —but honesty should have prompted John Delaney to mention it. And you will notice the absence of information for the x axis (the time). Marketing and honesty are 2 words that don’t mix well in Ireland.

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ADDENDUM:

ABC video

YouTube video

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

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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.

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You might also have watched Emile Servan-Schreiber’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 —blah blah blah blah blah.
2. In the second part, Emile Servan-Schreiber took questions from the audience in the room. “Aren’t political prediction markets just following the polls?”, asked one guy. Emile’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 “following” the polls. Both the mass media and the prediction markets do follow the polls (since the polls are facts that can’t be ignored), during political campaigns. Let’s compare the prediction markets with the mass media, instead, and let’s see who’s quicker to deliver the right intelligence..

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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’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’s fivethirtyeight.com. 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, Electoral-Vote.com (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.

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The polls are facts. Prediction markets are meta to facts. Prediction markets are intelligence tools. Let’s compare them with similar intelligence tools.

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Lance Fortnow’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 “prediction” 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’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’t know. We don’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’t as well established) will impact this election, today poll’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.

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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.

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My replies to his/her points:

1. That’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’t screw it).
2. That’s true in simple situations, but that’s wrong in complicated situations (such as the 2008 Democratic primary).

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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’s analysis of those complicated situations, and compare that with the prediction markets.

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APPENDIX:

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My second remark to John Tierney:

“I was impressed to see”
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You are too easily impressed. The nature of the prediction markets is to aggregate information quickly. Traders are very well informed (they do read Nate Silver and Electoral-Vote.com), and do anticipate quickly. That’s a given. From there, if you want to demonstrate the real social utility of the prediction markets, you should tell what is the benefit of watching the probabilities of the prediction markets in a context where the polls, the state poll aggregators and the political blogs did a very good job in the 2008 US elections. Just to say that the prediction markets did aggregate the new information quickly is not enough —that’s what the prediction markets do as a day job. To assess the prediction markets, you should put them in a social context.

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Previously

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InTrade got it [almost] spot on because they were wrong on Missouri (which was predicted to go for Obama but went to McCain) and wrong too on Indiana (which was predicted to go for McCain but went to Obama) —and those 2 opposite mistakes canceled themselves because those 2 states have the exact same number of electoral votes (11). Hence, I disagree with your method.

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APPENDIX:

Here’s a visual post-mortem of the 2008 US presidential elections.

Pay attention to Missouri and Indiana.

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A) InTrade, on November 5, 2008 (screen shot taken at 2:00 am):

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Prediction Markets & State Polls, on November 4, 2008:

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B1) Prediction Markets (on November 4, 2008)

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InTrade (screen shot taken at mid-day ET, November 4, 2008):

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InTrade (screen shot taken in the morning, November 4, 2008):

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BetFair (screen shot taken in the morning, November 4, 2008):

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HubDub (screen shot taken in the morning, November 4, 2008):

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B2) State Polls (on November 4, 2008)

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Karl Rove (on November 4, 2008):

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CNN (on November 4, 2008):

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Pollster (on November 4, 2008):

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Electoral-Vote.com (on November 4, 2008):

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Nate Silver (on November 4, 2008):

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PREDICTION MARKET PROBABILITIES

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Explainer On Prediction Markets

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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 represents the imputed perceived likelihood of the partially uncertain event (i.e., its aggregated expected probability). A 60% probability means that, in a series of events each with a 60% probability, the favored outcome is expected to occur 60 times out of 100, and the unfavored outcome is expected to occur 40 times out of 100.

Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism —with or without an automated market maker.

Prediction markets enable us to attain collective intelligence. Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that the traders bring when they agree on prices. The event derivative traders are informed by the primary indicators (i.e., the primary sources of information), like the polls, for instance. These informed speculators then execute their transactions based on their anticipations about the future —anticipations that will be either confirmed or infirmed.

The value of a set of prediction markets consists in the added accuracy that these prediction markets provide relative to the other forecasting mechanisms, times the value of accuracy in improved decisions, minus the cost of maintaining these prediction markets, relative to the cost of the other forecasting mechanisms. According to Robin Hanson, a highly accurate prediction market has little value if some other forecasting mechanism(s) can provide similar accuracy at a lower cost, or if very few substantial decisions are influenced by accurate forecasts on its topic.

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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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John McCain won Missouri.

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Nigel Eccles is calling HubDub.co.uk his home.

Let’s scan his Press release for interesting bits:

We’re delighted to be able to offer our UK Hubdubbers their very own UK Edition of Hubdub. Now Hubdubbers based in the UK can now see news stories that other UK users are predicting on, simply by selecting the UK Edition at the top right of the home page.

Interestingly, the US site’s most popular stories today are all around the Presidential Inauguration and Obama’s cabinent appointments, while the UK site’s top listings are X-Factor, Strictly Come Dancing and Everton v Middlesborough. What does this say about the UK, I wonder? [1]

Here is the press release that we issued today in the UK:

Edinburgh, 10 November 2008:

News junkies in the UK can now get an additional fix, by predicting the outcome of news stories – engaging in news stories instead of just reading them.

Users of Hubdub, which launches in the UK today, use a pot of virtual money to place bets on the outcome of any of over 2000 running news stories, covering the likes of politics, sport, business and entertainment.

Since launching earlier this year in the US, Edinburgh-based Hubdub has garnered a substantial and loyal following, with over 200,000 unique visitors per month, 800,000 predictions to date and over 2 million Hubdub dollars staked every day. Some users are spending several hours a day on the site, with many of them confessing to a definite Hubdub “addiction” on the site’s forum.

The fact that it’s Hubdub dollars at stake is apparently irrelevant [2] – Hubdub users are so competitive that the most important thing is that they prove they were right to the rest of the vibrant community. How much is won or lost depends on not only how the news story turns out, but how others have predicted the outcome. Groups of friends can set up their own, dedicated leaderboard to show who has predicted most accurately.

Globally, prediction markets, the mechanism behind Hubdub, are becoming increasingly popular. In the US, the Presidential election sent the numbers of users soaring. They have proven to be more accurate than polls [3], and because they respond in near real-time to developing stories [4], more agile too. Indeed, Hubdub successfully predicted the final voting results of the US election where the majority of polls and pundits failed. [5]

Lesley Eccles, one of the founders of Hubdub, commented: “It’s great to be launching in the UK, despite the recession. People are going to be looking for free entertainment and will turn to the web to find it. Hubdub is free, exciting and keeps you informed. In addition, news sites are looking to engage and interact further with their readers and Hubdub gives them a fantastic means to do so.”

Having secured partnerships with leading media news sites including Reuters and The Independent, Hubdub is taking prediction markets more mainstream and making them easier for casual browsers to appreciate. Sitting beside high quality news content, Hubdub provides news sites with additional ways to engage their readers, keeping them online longer and returning on a regular basis.

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[1] Interesting stats. Does it tell more about the Americans versus the British, or more about the HubDub’s SEO results?

[2] I agree with that, in part. I would like to see HubDub offering prizes to traders, as NewsFutures does.

[3] Scottish approximation. It should be said that prediction markets do slightly better than the polls, in a very long series of comparisons.

[4] Yes, a prediction market is an information aggregation mechanism, but its value is limited. It is valuable to the busy people. But the real value of the prediction markets have yet to be demonstrated. (I have my own idea.)

[5] Scottish exaggeration. I don’t like this way of assessing the electoral college predictions. The InTrade and HubDub prediction markets got both Missouri and Indiana wrong (so to speak, in a non-probabilistic way), but, as those 2 states has the exact same number of electoral votes (11), this double mistake cancels itself when you assess only the total number of electoral votes. The InTrade and HubDub prediction markets can claim that they got the number for Barack Obama (almost) spot on (they predicted 364, with the “leaning” method –he will get 365, actually, because of one additional Nebraska electoral vote) —but that’s because their mistakes on Missouri and Indiana cancel themselves perfectly. I call that “luck”.

TAKEAWAY: To find the real social utility of the prediction markets, we need to go beyond the propaganda churned out by the exchange executives and their courtesans.

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APPENDIX:

Here’s a visual post-mortem of the 2008 US presidential elections.

Pay attention to Missouri and Indiana.

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A) InTrade, on November 5, 2008 (screen shot taken at 2:00 am):

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Prediction Markets & State Polls, on November 4, 2008:

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B1) Prediction Markets (on November 4, 2008)

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InTrade (screen shot taken at mid-day ET, November 4, 2008):

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InTrade (screen shot taken in the morning, November 4, 2008):

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BetFair (screen shot taken in the morning, November 4, 2008):

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HubDub (screen shot taken in the morning, November 4, 2008):

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B2) State Polls (on November 4, 2008)

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Karl Rove (on November 4, 2008):

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CNN (on November 4, 2008):

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Pollster (on November 4, 2008):

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Electoral-Vote.com (on November 4, 2008):

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Nate Silver (on November 4, 2008):

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-

PREDICTION MARKET PROBABILITIES

-

Explainer On Prediction Markets

-

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 represents the imputed perceived likelihood of the partially uncertain event (i.e., its aggregated expected probability). A 60% probability means that, in a series of events each with a 60% probability, the favored outcome is expected to occur 60 times out of 100, and the unfavored outcome is expected to occur 40 times out of 100.

Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism —with or without an automated market maker.

Prediction markets enable us to attain collective intelligence. Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that the traders bring when they agree on prices. The event derivative traders are informed by the primary indicators (i.e., the primary sources of information), like the polls, for instance. These informed speculators then execute their transactions based on their anticipations about the future —anticipations that will be either confirmed or infirmed.

The value of a set of prediction markets consists in the added accuracy that these prediction markets provide relative to the other forecasting mechanisms, times the value of accuracy in improved decisions, minus the cost of maintaining these prediction markets, relative to the cost of the other forecasting mechanisms. According to Robin Hanson, a highly accurate prediction market has little value if some other forecasting mechanism(s) can provide similar accuracy at a lower cost, or if very few substantial decisions are influenced by accurate forecasts on its topic.

-

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

-