Prediction Markets are here…

Well they always were. We are beginning to realize the presence.

Dus Ka Dum (power of 10) is a reality show hosted by popular Indian actor, Salman Khan. The show progresses by asking the player a question, the answer of which tries to predict a percentage. A possible question is “What percentage of votes will the Congress Government win if India has a general election today?”. Answering five correct questions would bring Rs. 10 crores ($2.5M). The correctness of the answer is measured by the fact that it falls in a particular range of the correct answer. The first question allows a 40% window around the correct answer and wins you $250, the second allows a 30% window and wins $2500, the third allows 20% with $25,000 return, the fourth returns $250,000 with a 10% window. The bull’s eye is for the fifth answer with a $2.5M cash prize.

What makes this show interesting for me is how close it comes to a prediction market. Prediction Markets are simulated systems that allow different people to predict an event or a fact. DARPA initiated one of the first prediction markets in 2003 through a policy analysis market. A policy analysis market allows people to make predictions around geopolitical risks (more details). In a recent McKinsey roundtable survey and Google’s report on the use of prediction markets for better product management, innovation and competition guidance has generated recent interests in the avid use of prediction market technologies.

Dus Ka Dum (and other similar shows) is an example when individuals trade in real money. The presence of real money on the outcome of prediction markets is an ongoing discussion. A useful article from is here. The analysis seems to suggest that the presence of real money doesn’t cause any changes to the market behavior. A possibility is that the bias for/against real money gets offset in a crowd. In the case of ‘Dus Ka Dum’, it will be interesting to sample the history it creates after one season of telecast and see how the predictions of individuals playing for money compare to that of the studio audience, who are not playing for money.

Prediction markets seem to work – the crowd is getting wiser than the experts. This collective wisdom aided by greater, easier collaboration (internet and all the noise around social networking) is working out in favor of prediction markets. With an ever increasing internet penetration in India, I am getting excited to see how the ideas surrounding the world of prediction markets start becoming realities.

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