According to Alan Abramowitz, John Tierney has been “-greatly exaggerating the accuracy of the betting markets.”- “-They follow the polls. That’s it.”-
My comment to Alan Abramowitz and John Tierney:
“-They follow the polls. That’s it.”-
Yes, they follow the polls. No, that’-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.
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 —-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’-t be impacting if you publish enthusiastically about the features of the prediction markets —-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 —-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 —-busy people (who don’-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’-t seen such a case, yet. If some of my readers are interested in such a project, let’-s talk.
Let’-s not confuse media visibility with utility. Aside from the depressed Obama-to-win prices on one exchange, prediction market and polling aggregation results for the 2008 election were essentially the same using squared errors. Despite his insane schematics, Emile Servan-Schreiber has a good point about capturing the interest of the public, something that nerdy academic and libertarian-types aren’-t necessarily good at. An Obama-backing baseball statistician out of Daily Kos nailed that part this year, a year where people were especially skeptical of markets, not to mention unregulated “-offshore”- ones. Likewise, if you put down the lens of considering markets as commission generators, you’-ll see the value of contracts tied to social and cultural outcomes. Of one the biggest assets of prediction exchanges is media goodwill, which should be fostered by distilling information on subjects like global development and art prices.
Other things to keep in mind:
This year happened to have a lot of favorite-longshot States, which turned-out to be favorable to 538’-s error relative to markets.
Prediction markets register information in real time. Since the difference in error is small, this is important.
Markets are more flexible, and useful in situations where you don’-t have a rich data set and obvious statistical analyses. Elections are just one type of question. Even if you have data, it might be less expensive to set up a new contract than to undertake the analysis.
And of course, prediction markets have functions aside from forecasting, and provide incentives for uncovering new information.
Congrats for the launch of AskMarkets. Best wishes to your prediction exchange and consulting firm.
Here’-s the perfect opportunity to ask you the “-question that kills”-:
What was the social utility of the political election prediction markets during the 2008 campaign?
In other words, why should the media have informed people about the InTrade probabilities at a time Nate Silver did a near-perfect job forecasting the 2008 US elections?
What’-s the added value of the political election prediction markets over the poll aggregators?
Can you cite one prediction market (other than the “-who’-s gonna become president?”- prediction market) that has a high social utility?
Each time I ask this question to one of the prediction market luminaries (or so they think they are), I get back the same glance I would get from a dead trout —-so I would appreciate if you could attempt to answer my question by publishing a blog post on Midas Oracle.
The key, now, is to go beyond the accuracy issue and to move on to the utility issue.
It’-s a much complex problematic, which those who have been over-selling the prediction markets are unwilling to undertake. [*]
Maybe a small bunch of prediction market people, maybe assembled in a new prediction market structure, might go for that lofty goal of fingering the specific instances where prediction markets create real social utility.
[*] Yelling across the harbor, like an illuminated Jesus Christ, that prediction markets can help “-avoiding future [financial] crisis”- is a sign that some prediction market practitioners have lost their intellectual compass. To my knowledge, InTrade hadn’-t had any prediction market focused on the “-looming credit crunch crisis”-, last summer. Its CEO should be careful about making any grand statement. As I wrote many times, at best, the prediction markets are the best umpire you can have between either the mass media and the politicians, on one hand, and a group consisting of the best experts, on the other hand. An umpire is only useful during critical times, in a game. But, other than that, most of the times, the umpire is not the determinant of the game —-the players are.
The researchers and practitioners should make a solid case for each of these critical instances where the prediction markets have a real social utility.
Stop the over-selling. Let’-s start the real work.
John Delaney states rightfully that the prediction markets are a mechanism that aggregates information dispersed among the population. Then, he goes on at full throttle and states that prediction markets can help “-avoiding future [financial] crisis.”-
Jesus, Mary, Joseph, that’-s quite an extraordinary statement.
John Delaney writes that crucial information is buried deep in the accounting books. That’-s true, but that’-s up to the financial analysts to decipher this problematic —-our event derivative traders can then just pick up on what those experts conclude. The financial experts were unable to prevent the current financial cataclysm. Adding more event derivative traders and more prediction markets won’-t solve any problem.
Prediction markets are only a reflection of the current knowledge of the best experts in town. At best, they are the best umpire you can get between, on one hand, the mass media or the politicians and, on the other hand, the best experts. But when nobody knows anything (or when nobody listens to Nouriel Roubini), the prediction markets are of no help.
What the prediction market industry needs right now is not an ill-informed, bragging rant.
What the prediction market industry needs is a way to discriminate between accuracy and utility.