Here is my comment regarding the article on the uncertain future of prediction markets that appeared in The Economist, recently:
After having reviewed much of the available literature on the theories supporting prediction markets and the few publicized cases of corporate pilot projects, I still believe that prediction markets can play a very valuable role in business decision-making. In addition to the reasons cited in this article for prediction markets not catching on in the corporate world, here are a few more.
In theory, for prediction markets to work properly, there must be a fairly large number of diverse traders, (who trade on their own private information), they must remain as independent as possible in their decision-making, they must be motivated to reveal their true opinions through their trading activities, and there must be a mechanism for aggregating their trades.
In practice, the prerequisites for successful predictions have been relaxed. It is difficult to find (and keep interested) a large enough number of participants to keep markets trading, in order to reach an “equilibrium”. Some are designed with an automated market maker, to ensure that all bids and asks can be fulfilled, even if there is no willing seller or buyer. Combined with incentives, this system skews market behaviour, exhibits “herding”, and ultimately, distorts the price mechanism that they are trying to achieve. Even where there are a large number of total participants, if there are too many markets available in which to invest, there will be individual markets with insufficient trading activity. Other markets will suffer from a trade-and-forget style of investor behaviour, resulting in illiquid markets shortly after opening. A quick review of many online (public) markets reveals a surprising number with “thin” trading, exhibiting large spreads between the bid and ask prices. Such markets may not reach their equilibrium prices, and the inability to make trades quickly saps participants’ interest.
To be useful in the corporate world, prediction markets must provide valuable predictions of future events, actions or conditions. It is of little use to know the likelihood of an outcome immediately before it occurs. Companies need to know the likelihood of various events at the earliest possible moment, so that contingency plans may be activated in time. The difficulty is in motivating participants to trade in an outcome that will not be revealed for a considerable period of time.
Undoubtedly, as the corporate world experiments further with these tools, valuable prediction markets will be found and exploited. One promising avenue that might be followed is the derivation of probability distributions surrounding the predictions. Management could obtain a clearer picture of the uncertainty surrounding each key forecast metric or event. More contingency planning could be devoted to those areas that exhibit the most uncertainty.