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At the end, the conversation barged on the issue of “advisory boards“. And he told me that Robin Hanson and Justin Wolfers have helped him TREMENDOUSLY —in terms of solving problems with new software features, case studies, applied research, etc.

Wow.

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There are several prediction marketplaces out there for the upcoming U.S. election season and probably more to come. All the ones we know of are intended for participation by the general public. But what if a Presidential campaign ran an internal marketplace? How could prediction markets be used to give a campaign a competitive advantage? We put our political operative hats on for a few minutes and came up with some scenarios:

Resource Allocations

Speaking to veterans of previous presidential campaigns, one of the biggest issues mentioned was building consensus internally on resource allocation across the primaries, then for the general election. Conflicting polling data and infighting among advisors often led to the abandonment of several states where post-mortem analysis of actual voting patterns showed the candidate would have had a chance. Using prediction markets as input to resource allocation decisions, questions could be asked that compare performance metrics across different states, i.e. levels of support among certain voter blocs, predicted endorsements, outcomes of local elections that could impact the general election, etc. This type of information is hard to gather through traditional polling mechanisms but could easily be captured across participants from individual states, locales, and the general campaign.

Fundraising Forecasts

We assume existing forecasting methods used by campaigns are fairly accurate at anticipating how much money will be raised on a quarterly basis from a defined donor list. What may not be as well defined, however, is the impact of various campaign maneuvers on donation levels. For example, a campaign could internally test various scenarios with national campaign staff, field workers, even undecided voters to see if certain activities drive increased fundraising. If the campaign goes through with the activity, the campaign could evaluate the market and pay it out. If not, the market could simply be refunded. Of course, a campaign could also use prediction markets as further input to official forecasts across the different fundraising channels, allowing a more diverse group of people who may have additional insight beyond the “MBA types” at campaign headquarters crunching numbers.

Risk Management

(Using Inkling,) questions in a prediction market could be generated by the national campaign and staff at the local level. This “web of questions” would be especially useful when trying to anticipate risks to the campaign. The prediction market could be a clearing house of the whispers, rumors, and self-perceived weaknesses of the campaign to continuously test their merit or impact on the campaign. For example, someone from the local staff may be aware of a negative perception the candidate suffers from in a particular voting district. They could run a prediction market about its impacts in an upcoming primary, i.e. “Will the candidate be perceived as weak on X in analysis of post-appearance local media coverage?” If the stock price remains low, that issue probably does not need to be dealt with specifically. If it’s high, it may be an issue the campaign chooses to address proactively ahead of the predicted negative coverage.

Policy Predictions

Given the interest shown to any major candidate, a prediction market gives a campaign an outlet for those supporters wishing to participate in a more meaningful way than simply donating money. A market geared towards public policy across a wide range of issues, both national and local, would be an excellent resource to send people to. Currently most candidate’s online presence is focused largely on networking, information dissemination, event notifications, and fundraising. A broadly available prediction market would allow people to provide input on what they think will happen from a policy perspective, i.e. will a particular bill pass? How much funding will an initiative receive, etc.? The campaign could then take these predictions as input to shape policy. A similar marketplace could also be set up with a more limited audience of dedicated national and local campaign staff. This marketplace could be augmented with policy experts from around the world to provide additional perspective.

Competitive Analysis

Intended for a tightly controlled group of trusted participants, prediction markets could be run on the performance of the other candidates related to their fundraising levels, endorsements, primary performance, etc. to see how one candidate compares to another. This information would be very useful for strategy formulation. Four years ago some of the candidates tapped the blogosphere to drive early campaign participation and fundraising success.

This year most candidates are trying to build up and leverage their online social networks a la Facebook. Will this campaign season also be the year we see a candidate tapping the collective wisdom of his/her sprawling campaign apparatus?

My name is Brian Shiau. I have been working on applying prediction markets to finance and consulting applications for the past couple of years. My advisors and I have discussed in depth how prediction markets can serve as great information aggregating tools for consulting and market research. However, participants in such prediction markets often get bored and so the markets cannot garner sufficient trading interest to maintain liquid trading and therefore do not predict any useful information.

Instead, I have decided to experiment by launching a prediction market for trading something fun–video games. I’m a gamer myself. I enjoy reading about upcoming games and gauging whether a game will catch enough buzz so that their multiplayer experience will be worthwhile when the game comes out.

I agree 100% with Brian Shiau. Let’s develop prediction exchanges with event derivatives contracts that are fun to trade (sports, movies, games), and once a critical mass is attained, it then becomes possible to trade socially relevant event futures markets.

I said that “vertical prediction exchanges (a la HSX) are performing a better service than vertical lines in a generalist prediction exchange.” I still agree with my self. However, I also said in the past that it is silly to compartmentalize a brand in one industry segment —it’s better to have a brand name that is not heavily linked with one activity; that way, you can easily diversify or branch out, later on.

Here we are today with one big, public, vertical, play-money prediction exchange (the Hollywood Stock Exchange), which size now rivals a financial exchange from a poor country. Is its activity perimeter sealed forever in the movie business? No. Here’s the trick: The HSX publicist could sing the song that “Hollywood” refers, not to the movie business, but to the location of its incorporation. And HSX could go on floating soccer, music, US politics, etc.

Same idea for the Sim Exchange. I see them diversifying, later on —the word “sim” is not too segmenting, in my view.

Anyway.

You can DIGG the Brian Shiau blog post —DIGG.com is a service that uses people to vote for or against stories; that way, only the most popular stories appear on its frontpage.

Brian Shiau’s blog post: An invitation to join the simExchange beta.

By the way, yesterday, Marginal Revolution linked to Midas Oracle .ORG for the seventh or eighth time —I stopped counting.