Information aggregation in exponential family markets
Information aggregation in exponential family markets
复制标题
指数级家庭市场的信息聚合
DOI：
10.1145/2600057.2602896
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Rahul Sami
中科院分区：
文献类型：
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作者：
Jacob D. Abernethy;Sindhu Kutty;Sébastien Lahaie;Rahul Sami
我们考虑称为自动做市商的预测市场机制的设计。我们证明，我们可以通过指数族分布的模型来设计这些机制，指数族分布是统计学中使用的一种流行且经过充分研究的概率分布模板。我们充分发展这种关系并探索一系列好处。我们在市场价格的信息聚合和依赖于指数族分布的学习代理的信念聚合之间建立了联系。假设交易者根据指数效用表现出风险厌恶情绪，我们对市场行为和价格均衡进行自然分析。我们还考虑替代模型下的类似方面，例如预算有限的交易者。
We consider the design of prediction market mechanisms known as automated market makers. We show that we can design these mechanisms via the mold of exponential family distributions, a popular and well-studied probability distribution template used in statistics. We give a full development of this relationship and explore a range of benefits. We draw connections between the information aggregation of market prices and the belief aggregation of learning agents that rely on exponential family distributions. We develop a natural analysis of the market behavior as well as the price equilibrium under the assumption that the traders exhibit risk aversion according to exponential utility. We also consider similar aspects under alternative models, such as budget-constrained traders.