Professor Thomas Rietz (Iowa Electronic Markets) was so wrong on the usefulness of prediction markets about the 2016 Summer Olympics in Chicago.

Chicago Olympic Market Might Have Value, Says Reitz (Chicago Tribune, April 17)
A credible source of information about Chicago&#8217-s chances of hosting the 2016 Olympics would have value, says columnist Bill Barnhart. Local real estate developers, hotel operators, employment agencies, vendors of products and services to major events and others have a direct stake in whether or not an Olympics is staged here. Politicians and civic leaders presumably would want to know whether the city&#8217-s bid has a chance, so that they wouldn&#8217-t throw good money after bad. An auction market centered on whether Chicago will win could provide that information, even if there were no huge payoff for hedgers or speculators, said finance professor THOMAS RIETZ at the University of Iowa, a board member of the popular Iowa Electronic Markets. The Iowa market limits wagers to $500 but has an enviable track record in picking the winners of national elections. &#8220-Our goal is to aggregate information, which is a different goal than being able to hedge the economic risk associated with something like this,&#8221- Rietz said. &#8220-I don&#8217-t think it&#8217-s an outlandish idea.&#8221-

http://www.chicagotribune.com/business/yourmoney/chi-0704160447apr17,0,2547860.column?coll=chi-business-hed

Prof, you were 100% wrong.

Prediction markets on which country will host the Olympics have never worked.

BetFair&#8217-s event derivative prices (on the far right of the chart, you can see that the price went down to zero):

chicago-olympics-betfair

InTrade&#8217-s event derivative prices (on the far right of the chart, you can see that the price went down to zero):

chicago-olympics-intrade

– HubDub&#8217-s event derivative prices:

Who will recieve the winning bid to host the 2016 Olympics?

Combinatorial Prediction Markets – David Pennock Edition

No Gravatar

ACM:

[…] Prediction markets are gaining interest because the Internet allows greater worldwide access to them, as well as to the ever-increasing amount of data stored on any topic imaginable (which theoretically allows participants to make more informed predictions, individually and in aggregate). These factors, plus the enormous amount of computing power that will make it possible to instantly calculate exponentially small odds, are stimulating new research on advanced computational models in prediction markets. These models could be capable of analyzing entire events such as the annual NCAA collegiate basketball tournament, which begins a 63-game schedule with 263 possible outcomes by the tournament&#8217-s end. […]

Growing opportunities in internal private-sector prediction markets are also revealing divergent philosophies among the markets&#8217- designers. Many of the public markets feature price-adjustment algorithms built around answering discrete multiple-choice outcomes, such as which candidate will win an election or if a product will launch in month x, y, or z. […]

IEM steering committee member Thomas Rietz, a professor of finance at the university, says the aggregate zero-risk design of the IEM allows the markets to perfectly reflect the aggregate forecast opinions of its participants. By aggregate zero-risk, Rietz explains that when a trader enters a particular bilateral (either/or) market, he or she must buy one share of each choice, called a bundle, for a total cost of $1. If the trader holds the bundle until the market concludes, there is neither profit nor gain. If the trader guesses the outcome successfully, and sells the losing unit of the bundle to another trader while the market is running, he or she picks up the original $1 bet plus whatever price was agreed upon for the losing share that was sold. If the trader chooses to hold onto the loser and sell the eventual winner, however, they will incur the $1 loss at payout time. At any given time, the number of eventual winning shares and losing shares is equal and held by the traders. So, the university bears no counterparty risk and there is no need to provide hedging margins that irrationally affect outcomes. &#8220-The price you would be willing to buy or sell for today is your expectation of its value in the future—the prices can be directly interpreted as a forecast,&#8221- Rietz says. &#8220-In ordinary futures markets, there is a long-lasting debate, going back to John Maynard Keynes in the 1930s, over whether prices can legitimately be used as forecasts, and it all hinges on whether or not people demand a return or face a risk in aggregate when they&#8217-re investing in these contracts.&#8221- […]

One enduring research problem on combinatorial markets is mitigating the effects a virtually unlimited spectrum of outcomes will have on creating markets that are so thin in trades they do not serve their purpose of aggregating information. In such markets, which might bear a resemblance to an enterprise prediction market in that there are not enough participants to provide a statistically valid spread of opinion, Pennock says a market-maker algorithm might serve as a price setter within widely acceptable limits. &#8220-I believe that approximation algorithms will be fine for the market maker, because people don&#8217-t really care about making bets on things that are incredibly unlikely, like 10?6 chance,&#8221- Pennock says. &#8220-But as long as you&#8217-re betting on something with a 10% chance of happening, we&#8217-ll be able to approximate pretty quickly with a market-maker price.&#8221- […]

David Pennock&#8217-s website and blog

Flu prediction markets can correct Google Flu Trends.

No Gravatar

2 practicing physicians laugh at using collective intelligence for nation-wide flu detection:

[…] Flu Trends tracks almost perfectly with data on influenzalike illnesses that the CDC obtains from doctors&#8217- offices. And as an added bonus, Flu Trends detects outbreaks up to two weeks earlier, when people are still sitting at home sneezing into their keyboards. […]

But if officials monitored only Flu Trends, it would be difficult to sort the signal from the noise —in addition to losing critical details on who is sick. Things besides an actual flu outbreak can cause people to search the Internet for flu information. We would imagine that Flu Trends would spike on the release date for a flu-related movie —maybe Outbreak 2: Electric Booga-Flu. And what happens if a pandemic flu scare hits the nightly news? Flu Trends&#8217- ability to detect when the real pandemic hits will be obliterated when people, including those without symptoms, start to search the Internet. Monitoring drugstore sales has the same issue: A jump in cold-medicine sales may mean a flu outbreak, but it could also mean that CVS is running a sale or that flu fear is causing people to stock their medicine cabinets. […]

They end their articles saying that Google can&#8217-t cure the flu, anyway. [???]

The response to the objections they jot down in the 2nd paragraph above is easy:

  • Informed by all other means, the event derivative traders can determine whether the spikes in Google Flu Trends are due to abnormalities (see the 2nd paragraph in the excerpt above) or due to the real spreading of influenza.
  • Hence, the flu prediction markets have a much higher social utility than Google Flu Trends. Chris Masse said so.
  • David Pennock, go writing another research paper about that.
  • History will retain that David Pennock was research scientist under Chris Masse&#8217-s reign in the field of prediction markets.

Google Flu Trends

Iowa Health Prediction Market

The “predict flu using search” study you didn’t hear about – by our good Doctor David Pennock

BBC

New York Times

WSJ Health blog

University College Cork (UCC) School of Medicine + Intrade

Dylan Evans&#8217- website

Previously: #1 + #2 + #3

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

No Gravatar

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.

Dylan Evans&#8217- website

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. ]

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

The Objectivity -according to BetFair

No Gravatar

BetFair Predicts (a blog run by BetFair) titled &#8220-The Power Of Objectivity&#8221- a post giving the latest odds produced by BetFair on the race for the White House.

The real &#8220-objectivity&#8221- would have been to quote the odds produced by the other prediction exchanges, too &#8212-InTrade, Iowa Electronic Markets, Betdaq, NewsFutures, HubDub, etc.

Midas Oracle is the only blog that lists prices and probabilities from all the prediction exchanges. No wonder, our daily readership is much, much bigger than the audience of all the other prediction market blogs combined. A blog that gives the odds of one exchange only is like a dead end &#8212-no one trusts a dead end.

Please, do support Midas Oracle.

The New York Times on InTrades US political election prediction markets

No Gravatar

The NYT writers discusses 2 (different?) issues.

#1. There was market arbitrage opportunies in the recent past between InTrade and BetFair &#8212-unlike 4 years ago, and contrary to the laws of economics.

– The price of the Barack Obama event derivative was cheaper on InTrade than on BetFair and the Iowa Electronic Markets. Conversely, the price of the John McCain event derivative was more expensive on InTrade than on BetFair and the Iowa Electronic Markets.

#2. The NYT writer reports (without linking to it) the findings of the InTrade investigation about the behavior of their unnamed &#8220-institutional investor&#8221-.

– InTrade CEO John Delaney suggests that that institutional investor:

  1. might operate on InTrade at specific times where it might not be able to find liquidity on BetFair and/or IEM-
  2. might be a bookmaker willing to hedge its risks on a prediction exchange (a.k.a. betting exchange).

– Justin Wolfers&#8217- PHD student remarks that that institutional investor is not making an effort to shop around for the best prices, within each InTrade political prediction market.

RELATED: See the comments on Midas Oracle here, here, here, and here.

InTrade has surpassed BetFair and TradeSports (and the Iowa Electronic Markets, too).

No Gravatar

InTrade&#8217-s PageRank is now 7 / 10 &#8212-while all the other major prediction market firms are at 6 / 10.

  1. It shows that the prediction market approach is paying off. Do provide journalist-friendly objective probabilistic predictions (expressed in percentages &#8211-not those fucking decimal odds), and the media will link to you, thanks to all the free-market economists who love your model and act as unpaid publicists for you. Make sure your website can resist under heavy traffic loads on Election Day, and during the occasional days where important news break. Then, milk out all this free publicity. Run registration ads allover your exchange website to attract new traders. Make money. Invest in IT &#8212-but don&#8217-t let the IT maniacs complicate your prediction exchange too much (as BetFair did).
  2. Long-term, the InTrade model (based on the prediction market approach) should be more profitable, in theory. Because of legal impediment, InTrade is not as profitable as it should be, alas.