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Tag Archives: Google Using Prediction
Do Google’s enterprise prediction markets work? — Using Prediction Markets to Track Information Flows: Evidence from Google
Using Prediction Markets to Track Information Flows: Evidence from Google – (PDF file – PDF file) – by Bo Cowgill, Justin Wolfers, and Eric Zitwewitz – 2008-01-06 – VIDEO — Bo Cowgill on Google’s enterprise prediction markets — O’Reilly Money:Tech … Continue reading →
Posted in All Best Posts Ever, Analysis (Accuracy & Precision), Analysis (Market Efficiency), Analysis (Meta), Business, Cases, Exchanges & Markets
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Tagged accuracy, active trader, advanced researcher, anonymous trading, architect, Bo Cowgill, CDA model for their markets, CEO, Chief Economist, computer-aided facility management systems, corporate applications, corporate prediction markets, crowd-wisdom applications, demographic networks, Doug Banks, economist, efficieny, Enterprise prediction market consultant, enterprise prediction markets, Eric Schmidt, Eric Zitwewitz, Eric Zitzewitz, event derivative markets, event derivatives, gas prices, Google, Google Using Prediction, Google's enterprise prediction markets, Google's prediction exchange, Google's prediction markets, GPS, Hal Varian, high profile applications, Ilya Kirnos, implicit social networks, internal prediction markets, James Surowiecki, Jed Christiansen, Justin Wolfers, language networks, Linux, Michael Giberson, open-source software, Patri Friedman, Piaw Na, prediction markets, Prime Minister, Private, private prediction markets, real estate management group, Robin Hanson, Social Networks, social/professional networks, software engineers, software-and-consulting model, the New York Times, Tim Harford, Trader, ubiquitous communication technology, United States, USD, value applications, Zubin Jelveh
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