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Experience from hosting a corporate prediction market: benefits beyond the forecasts

Published: 11 August 2013 Publication History

Abstract

Prediction markets are virtual stock markets used to gain insight and forecast events by leveraging the wisdom of crowds. Popularly applied in the public to cultural questions (election results, box-office returns), they have recently been applied by corporations to leverage employee knowledge and forecast answers to business questions (sales volumes, products and features, release timing). Determining whether to run a prediction market requires practical experience that is rarely described.
Over the last few years, Ford Motor Company obtained practical experience by deploying one of the largest corporate prediction markets known. Business partners in the US, Europe, and South America provided questions on new vehicle features, sales volumes, take rates, pricing, and macroeconomic trends.
We describe our experience, including both the strong and weak correlations found between predictions and real world results. Evaluating this methodology goes beyond prediction accuracy, however, since there are many side benefits. In addition to the predictions, we discuss the value of comments, stock price changes over time, the ability to overcome bureaucratic limits, and flexibly filling holes in corporate knowledge, enabling better decision making. We conclude with advice on running prediction markets, including writing good questions, market duration, motivating traders and protecting confidential information.

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Cited By

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  • (2021)Stock Price Analysis with Deep-Learning Models2021 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)10.1109/ColCACI52978.2021.9469554(1-6)Online publication date: 26-May-2021
  • (2017)Understanding Voluntary Knowledge Provision and Content Contribution Through a Social-Media-Based Prediction Market: A Field ExperimentInformation Systems Research10.1287/isre.2016.067928:3(529-546)Online publication date: Sep-2017
  • (2015)Corporate Prediction Markets: Evidence from Google, Ford, and Firm XThe Review of Economic Studies10.1093/restud/rdv01482:4(1309-1341)Online publication date: 2-Apr-2015

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      cover image ACM Conferences
      KDD '13: Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
      August 2013
      1534 pages
      ISBN:9781450321747
      DOI:10.1145/2487575
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      Published: 11 August 2013

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      Author Tags

      1. artificial markets
      2. forecasting
      3. organizational knowledge
      4. prediction markets
      5. social media

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      View all
      • (2021)Stock Price Analysis with Deep-Learning Models2021 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)10.1109/ColCACI52978.2021.9469554(1-6)Online publication date: 26-May-2021
      • (2017)Understanding Voluntary Knowledge Provision and Content Contribution Through a Social-Media-Based Prediction Market: A Field ExperimentInformation Systems Research10.1287/isre.2016.067928:3(529-546)Online publication date: Sep-2017
      • (2015)Corporate Prediction Markets: Evidence from Google, Ford, and Firm XThe Review of Economic Studies10.1093/restud/rdv01482:4(1309-1341)Online publication date: 2-Apr-2015

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