Prediction Markets

Case: Coles, Peter, Lakhani, Karim and McAfee, Andrew, “Prediction Markets at Google” Harvard Business School Case No. 9-607-088, August 20, 2007

Case preparation: Prediction Markets”, February 2016

Textbook Reading: Chapter 4 (Section 4.5; pp. 127-134)

I am an academic not an entrepreneur, but if there’s one area that I think is ripe for a successful venture it’s creating the go to prediction market. By the early 2000s we had established that prediction markets were an effective tool for corporate management, and we also learnt how useful they could be for a broad range of policy issues. It’s a scandal that governments – and the US in particular – have been so opposed to their use. (The reason is that they’re treated either as gambling firms or futures traders which are two of the most targeted and heavily regulated and industries). According to Scott Alexander:

There ought to be a billion dollar prediction market, maybe a ten billion dollar one. Smart VCs clearly believe something like this, or Kalshi wouldn’t have gotten $30 million+ in investment. Sometimes people who incorrectly believe I know things about prediction markets ask me if know the missing secret sauce. I don’t think there’s any secret. A prediction market will strike it big when it gets three things right at the same time:

    • Real money
    • Easy to use
    • Easy to create your own subsidized markets

It’s a dream of mine that I may have students who manage to put those things together, solve the regulatory issues, and launch a killer app. So far the closest is probably Polymarket but also see Prediki.

To read more about the “Policy Analysis Market” (PAM) which was designed by Robin Hanson as a tool for the US Department of Defense, but got cancelled in July 29th 2003 having been described as a “terrorism futures market” by the Washington Post, see:

Recommended reading
Recommended video

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Why There Aren’t So Many Hotel Fires Anymore” Stuff You Should Know.

Points to consider:

    • Key technology = fire doors, sprinklers, and alarms that anyone can set off. Imagine how many major hotel fires would occur if staff had to wait to inform senior management before receiving authorisation to call the fire brigade.
Learning Objectives: Understand how to operate a prediction market.