Friday, September 18, 2015

A Research Agenda for Prediction Markets

Patrick Buckley

This article outlines the usage of prediction markets to enable collaborative intelligence by first discussing the general concept of prediction markets and then diving deeper into its methodology, and concludes with a research agenda that can address certain shortcomings. The purpose of prediction markets is to find and aggregate trader (participant) information, and use that information to “make predictions about specific future events”. This method is essentially created by participants buying into one of two outcomes. Prediction markets are different from financial markets in two ways: 
  • Prediction markets allow participants to share information and trade contracts with each other
  • “Its primary concern is the elicitation of information”
In other words, the shared information and forecast estimation are the main goals of prediction markets, not the financial gain or risk.

There are three broad divisions of operational prediction markets:
  • Public prediction markets using real currency
  • Public prediction markets using virtual currency
  • Private prediction markets
Public prediction markets are open to the general public whereas private prediction markets have a sponsor who recruits participants from a specific group of people.

  • Provide participants with incentive to share truthful information
  • Provide an algorithm for automatic information communication and aggregation
  • Can be conducted on a very large scale with up to hundreds or even thousands of participants
  • Can operate over long periods of time
  • Provides trader anonymity
  • Might only attract individuals with certain personality traits (i.e. high risk tolerance individuals)
  • Participants may manipulate the system by buying into an outcome that contradicts their truthful information because voting for that option may provide a better incentive

Although the strengths are talked about in great detail, the weaknesses are barely mentioned, and there are only a few. Also there could be more detail about the public and private prediction markets and how they operate. This article’s conclusion is that there needs to be more collaborative research on prediction markets in regards to intelligence and decision making.


  1. In section 3, the author mentions predication markets are prone to manipulation by individuals with certain key personalities, or groups of people. In Section 4, the author outlines a study which can be done in a classroom environment to determine the behavior of individuals who would try to manipulate impacts on the market as a whole. Though the author discusses technicalities of the technique, the results from such a study would likely give analysts from various fields new means to examine their estimates.

    For example, in the financial world, AML (Anti-Money Laundering) researchers can use the findings to conduct further research into the attitude/rationalization element of the fraud triangle, which is severely lacking in literature, Hogan et al. (2008) and Murphy and Dacin (2011). As a result of the additional studies, AML analysts can use the findings to refine existing or develop new techniques to detect financial fraud.

    Link to the post:

  2. The article asserts that the shared information and forecast estimation are the main goals of prediction markets, not the financial gain or risk. Then, what is the role of financial gain in prediction markets? Is it just an encouragement or more?

    1. The role of financial gain in prediction markets likely occurs when real currency or some sort of “market good” is involved, hence why the authors mentioned prediction markets are prone to manipulation. Researches use incentives to encourage participation during research projects. However, incentives may not be necessary with online communities. The article Amanda posted gives a brief background on incentives.

    2. Seeing how Bitcoin would factor into this would be interesting.

    3. I think the financial gain is one way to view it, but I look at it more like being accountable for your decision. For example when we produce our intelligence reports in class, sometimes we sign them taking ownership for product. We are responsible for our recommendations just as people on prediction markets are responsible for the money they bet with. It does give people incentive because they might get a pay-out, but it also penalizes them if they are wrong.

    4. Devon, I agree with you. The financial scenario, specifically the money laundering use case is difficult to apply it to because of the behavioral/environmental/political factors surrounding the issue. I agree with Oleg in that he said 'incentives may not be necessary'. I wonder how prediction markets quantify these inconsistencies.

  3. The article I read also mentions about the market manipulation aspect of prediction markets. It says it isn't plausible since every person's share is limited to $500. It doesn't detail it. Does the study you assessed detail how can prediction markets be manipulated? And does it really work?

    1. Unfortunately this article did not go into much detail about how they can be manipulated but instead called for further research on prediction markets as a whole. What it did say about the manipulation is that there are some people who would bet against the information they knew to be true because they viewed the other outlook as more profitable.

  4. I think this article has an important point in that there is a selection bias in the participants. Those participating might have a higher risk tolerance than those that don't which would color their perspective. Do you think that this would effect the end accuracy of the market?

    1. I honestly don't feel read on the subject enough to say for sure but what I do think is this is a method that can be used in conjunction with other methods. The end accuracy may be affected, especially regarding public prediction markets which is why I would use other methods to back up my estimate.

  5. I find it interesting that one of the weaknesses mentioned is that prediction markets can easily be manipulated because something I had read said the opposite. I agree with you though after thinking about it, prediction markets are 100% reliant on the info fed into them so they are easily manipulated. Where I would say they do a good job of overcoming manipulation is that they will overcome bets by people who don't know what they are doing and are betting/predicting based on emotions or intuition. Even though gamblers are often highly risky, high level gamblers eliminate emotion from their bets.

    1. I also like the sample sizes prediction markets use. They have an upwards of thousands of individuals with all different knowledge bases which is a good thing for the most part (especially with private prediction markets). I do think there needs to be more research explicitly on the manipulation of these markets, however.