An In-Depth Analysis of Information Markets with Aggregate Uncertainty (2006)
| Venue: | ELECTRONIC COMMERCE RESEARCH |
| Citations: | 2 - 1 self |
BibTeX
@ARTICLE{Chen06anin-depth,
author = {Yiling Chen and Tracy Mullen and Chao-Hsien Chu},
title = {An In-Depth Analysis of Information Markets with Aggregate Uncertainty },
journal = {ELECTRONIC COMMERCE RESEARCH},
year = {2006},
volume = {6},
pages = {201--220}
}
OpenURL
Abstract
The novel idea of setting up Internet-based virtual markets, information markets, to aggregate dispersed information and predict outcomes of uncertain future events has empirically found its way into many domains. But the theoretical examination of information markets has lagged relative to their implementation and use. This paper proposes a simple theoretical model of information markets to understand their information dynamics. We investigate and provide initial answers to a series of research questions that are important to understanding how information markets work, which are: (1) Does an information market converge to a consensus equilibrium? (2) If yes, how fast is the convergence process? (3) What is the best possible equilibrium of an information market? and (4) Is an information market guaranteed to converge to the best possible equilibrium?







