Anomalies in Probability Estimates for Event Forecasting on Prediction Markets-Reference-Cited by-同舟云学术

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Anomalies in Probability Estimates for Event Forecasting on Prediction Markets

Published:2020-08-14 Issue:9 Volume:29 Page:2077-2095
ISSN:1059-1478
Container-title:Production and Operations Management
language:en
Short-container-title:Prod Oper Manag

Author:

Lee Ho Cheung Brian¹,Stallaert Jan²,Fan Ming³

Affiliation:

1. Smeal College of Business Pennsylvania State University University Park Pennsylvania16802 USA

2. School of Business University of Connecticut Storrs Connecticut 06028 USA

3. Foster School of Business University of WashingtonBox 353226 Seattle Washington 98195‐3226 USA

Publisher

Wiley

Subject

Management of Technology and Innovation,Industrial and Manufacturing Engineering,Management Science and Operations Research

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/poms.13175

Reference84 articles.

1. The Interrelation of Stock and Options Market Trading-Volume Data

2. Another look at the instrumental variable estimation of error-components models

3. Distilling the Wisdom of Crowds: Prediction Markets vs. Prediction Polls

4. The Effect of Collaborative Forecasting on Supply Chain Performance

5. A model of investor sentiment1We are grateful to the NSF for financial support, and to Oliver Blanchard, Alon Brav, John Campbell (a referee), John Cochrane, Edward Glaeser, J.B. Heaton, Danny Kahneman, David Laibson, Owen Lamont, Drazen Prelec, Jay Ritter (a referee), Ken Singleton, Dick Thaler, an anonymous referee, and the editor, Bill Schwert, for comments.1

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1. Challenges in Collective Intelligence: A Survey;2023 46th MIPRO ICT and Electronics Convention (MIPRO);2023-05-22

2. To Subsidize Or Not to Subsidize: A Comparison of Market Scoring Rules and Continuous Double Auctions for Price Discovery;Information Systems Frontiers;2023-04-26

3. Are CDS spreads predictable during the Covid-19 pandemic? Forecasting based on SVM, GMDH, LSTM and Markov switching autoregression;Expert Systems with Applications;2022-05

4. Put your money where your forecast is: Supply chain collaborative forecasting with cost-function-based prediction markets;European Journal of Operational Research;2021-09

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