Tag Archives: prediction markets

Google vs. Prediction Markets – Which of the 2 will detect the flu, first?

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An Irish research team hopes to make accurate forecasts of key public health indicators.

University College Cork (UCC) School of Medicine + Intrade

Dr Dylan Evans:

Prediction markets are [specialized], small-scale financial markets operated to predict future events. The idea is that the collected knowledge of many people, each with a different perspective, will be more accurate than an individual or small group or even experts.

When they have been used to predict the outcomes of political elections, prediction markets have been found to be more accurate than alternative methods of forecasting.

The obvious area to look at in the first instance is infectious disease, but we plan to extend our research into many other areas of public health. At the moment, people do not get data on infectious disease until it&#8217-s a couple of weeks out of date and we need to get it quicker.

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Dylan Evans&#8217- website

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My opinion:

  • To assess the benefits (if any) of the prediction markets used as forecasting tools for public health, researchers will have to compare them with the experts&#8230- and with the &#8220-Google Flu Trends&#8221- web service, which is entirely free of charge and free of advertising (being sponsored by the Google Foundation). Does not sound good for the prediction markets.
  • The irony is that it&#8217-s our prediction market researchers (David Pennock and his accomplices) who gave weight to this non-market tool. &#8212- Pennock = Treator &#8230-!!&#8230- [ :-D – Joke. ]

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APPENDIX:

– Iowa Health Prediction Market

– Google Flu Trends

– See also: Google Foundation on &#8220-Predict and Prevent&#8221-.

– Google Trends

– David Pennock on the fact that flu-related searches on the Web are precise predictors of the upcoming influenza outbreaks.

– BBC

– New York Times

– WSJ Health blog

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Are prediction markets on deaths and assassinations SOMETIMES acceptable?

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BELOW IS THE CHART OF A SETTLED PREDICTION MARKET:

Will Patrick Swayze die before April 15, 2008?

It was settled on &#8220-no&#8221-.

HubDub CEO Nigel Eccles thinks that his traders &#8220-quickly came to the conclusion that the [early 2008] story [giving him 5 weeks to live] was bogus.&#8221- And Nigel Eccles asks, &#8220-Is this an example where a death pool prediction market is actually socially valuable?&#8221-

In my view:

  1. It&#8217-s the opinion makers external to HubDub who should decide this. If most people and/or lawmakers decide that prediction markets on deaths and assassinations are disgusting and unacceptable, then they should be pruned. We need goodwill towards the prediction markets if we want the real-money prediction markets to be legalized everywhere.
  2. Would Nigel Eccles accept a prediction market about when his wife (or kid) is going to die?
  3. Is there a social utility in knowing when exactly a celebrity is going to die (supposing that such a prediction market could be accurate)? For a head of state, a running politician, or a Justice, that information might have a value. However, in the case of a Hollywood celebrity, I don&#8217-t see where the value lays. A prediction market on the upcoming death of a celebrity would participate in that big, stupid circus that occurs today, with paparazzi and tabloids taking an importance that they shouldn&#8217-t have in the first place. Our youth would be better off browsing and betting on prediction markets about science and technology. We should elevate our global civilization. I don&#8217-t see any (social or individual) benefit about knowing in advance when exactly Patrick Swayze is going to die. I am scratching my head right now &#8212-and I still don&#8217-t see any reason why we should spend our precious time blogging on this issue, betting on that, or collecting probabilistic predictions on that. I just don&#8217-t. (If you have a counter argument, do publish a comment below.)
  4. The very best wishes to Patrick Swayze, by the way.

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Are prediction markets useful to you?

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It&#8217-s &#8220-pretty clear&#8221- that the prediction markets on political elections aggregate information from the polls &#8212-and from the political experts.

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Previously: #1 – #2 – #3 – #4 – #5 – #6

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It&#8217-s &#8220-pretty clear&#8221- that:

  1. InTrade has been over-selling the predicting power of its prediction markets.
  2. The prediction markets are information aggregation systems &#8212-not magical tools.
  3. The main benefit of a prediction market is to express an aggregated expected probability. Most of the times, this is of low utility.
  4. In complicated situations, this aggregation will contrast well with a poor reporting. In these instances, the prediction market is a useful source of information.

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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.

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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-

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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.

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Previously: #1 – #2 – #3 – #4 – #5

External Link: Club of Growth

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Still, as noted, it was a good election for [the] prediction markets and another piece of evidence of their superiority over the pundit[s] (and at least parity with the poll).

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Dixit Nigel Eccles in a comment.

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at least parity with the poll

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I agree with the above.

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their superiority over the pundits

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What documented evidence do you have about that, mister the cocky entrepreneurial Scotsman?

John Tierney linked to that Huffington Post that listed the pundits&#8217- predictions about the total number of electoral votes that each presidential candidate would take. But I disagree with that way of predicting the electoral college and assessing these predictions. With this completely flawed method, if you are damn wrong on a state and damn wrong (in the opposite way) about another state that has the exact same number of electoral votes, then you are a bright genius worth the Nobel prize of forecasting. Gimme a break. Enough with that voodoo way of assessing predictions about the electoral college. Do the assessment state by state.

InTrade and HubDub got lucky that their 2 mistakes (so to speak, in a non-probabilistic way) on Missouri and Indiana (both with 11 electoral votes) canceled themselves perfectly. IT WAS PURE LUCK. If their 2 mistakes had been made in the same direction (say, betting on Obama with the outcome going eventually to McCain), and/or their 2 mistakes had been done on 2 very dissimilar states (say, one with 6 electoral votes and the other one with 27 electoral votes), then we would have had reporters and bloggers bashing the prediction markets for the whole month of November.

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Dont pump up the features of the prediction markets -instead, put the emphasis on their benefits.

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John Tierney and Jed Christiansen are making the same mistake: they think that people and experts should be impressed by the information aggregation functionality of the prediction markets. They are not &#8212-people still prefer reading Nate Silver and Electoral-Vote.com over InTrade, and the political experts have not added InTrade in their toolbox. (On this last point, do read the very last sentence of that interview.)

You won&#8217-t be impacting if you publish enthusiastically about the features of the prediction markets &#8212-yes, they do incorporate the latest news quickly, they quantify reasonable anticipations, they output probabilities, and they are relatively unbiased. You will be impacting the day you are able to demonstrate the benefits of the prediction markets &#8212-for people, on one hand, and for the experts, on the other hand.

This would require a new focus, and a much bigger effort.

The social utility of most prediction markets is minimal &#8212-busy people (who don&#8217-t have time to read extensively the news) get relatively objective probabilities, real quick. But very few companies are using enterprise prediction markets, as of today. If these new IAM tools were magical (as some sur-excited free-market proponents think they are), all the Fortune-500 companies without any exception of any kind would be using them today.

If you want to discover the true benefits of the prediction markets, you should first be able to rank them by degree of utility. Which ones are more useful than others? Why? To answer this last question, you have to lay out the panorama of all the information sources that people and expert have access to, these days. What were the specific instances where the prediction markets were a tie breaker between the experts and the mass media, or between the decision makers and the experts, or between 2 opposite groups of experts? You should build an airtight, documented case. I haven&#8217-t seen such a case, yet. If some of my readers are interested in such a project, let&#8217-s talk.

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The Intrade bettors expected Mr. Obama to end up with 364 votes in the Electoral College -one less than he actually got.

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My remark to John Tierney:

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&#8217-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 &amp- 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 &#8212-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 &#8212-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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