Prediction Market at Google

Submitted by: Submitted by

Views: 773

Words: 2771

Pages: 12

Category: Business and Industry

Date Submitted: 09/22/2011 06:02 PM

Report This Essay

N 9 -6 0 7 -0 8 8

MARCH 07, 2007

PETER COLES KARIM LAKHANI ANDREW MCAFEE

Prediction Markets at Google

In late March of 2007, Bo Cowgill, Ilya Kirnos, Doug Banks, Patri Friedman, and Piaw Na sat down to lunch at Google’s headquarters in Mountain View, California, and reviewed the most recent results from the company’s internal prediction markets. The five Googlers (as Google employees referred to themselves) had launched the company’s prediction markets, built the information systems that supported them, and overseen them during the previous seven quarters, all while working at their “normal” jobs. The markets had grown in popularity and demonstrated their accuracy during that time, and the team was proud of its accomplishments. Prediction markets were very much like stock markets. They contained securities, each of which had a price. People used the market to trade with each other by buying and selling these securities. Because traders had differing beliefs about what the securities were worth, and because events occurred over time that altered these beliefs, the prices of securities varied over time. In a stock market like the New York Stock Exchange the securities being traded were shares in companies, the price of which reflected beliefs about the value of the company. In a prediction market, in contrast, the securities being traded were related to future events such as an American presidential election. In this case, the market could be designed so that each security was linked to a candidate, and its price was the same as the estimated probability that the candidate would win, according to the markets’ traders. Prediction markets on the Internet had proved to be remarkably accurate at predicting the results of political elections and other events, and the Googlers had wanted to see if they could also be productively used within companies to forecast events of interest such as the launch date of a product, or whether a competitor would take a specific...