Towards a Theory of Confidence in Market-Based Predictions
Abstract
Prediction markets are a way to yield probabilistic predictions about future events, theoretically incorporating all available information. In this paper, we focus on the confidence that we should place in the prediction of a market. When should we believe that the market probability meaningfully reflects underlying uncertainty, and when should we not? We discuss two notions of confidence. The first is based on the expected profit that a trader could make from correcting the market if it were wrong, and the second is based on expected market volatility in the future. Our paper is a stepping stone to future work in this area, and we conclude by discussing some key challenges.
Cite
Text
Freeman et al. "Towards a Theory of Confidence in Market-Based Predictions." Proceedings of the Twelveth International Symposium on Imprecise Probability: Theories and Applications, 2021.Markdown
[Freeman et al. "Towards a Theory of Confidence in Market-Based Predictions." Proceedings of the Twelveth International Symposium on Imprecise Probability: Theories and Applications, 2021.](https://mlanthology.org/isipta/2021/freeman2021isipta-theory/)BibTeX
@inproceedings{freeman2021isipta-theory,
title = {{Towards a Theory of Confidence in Market-Based Predictions}},
author = {Freeman, Rupert and Pennock, David and Reeves, Daniel and Rothschild, David and Waggoner, Bo},
booktitle = {Proceedings of the Twelveth International Symposium on Imprecise Probability: Theories and Applications},
year = {2021},
pages = {365-368},
volume = {147},
url = {https://mlanthology.org/isipta/2021/freeman2021isipta-theory/}
}