We consider mechanisms for truthfully eliciting probabilistic predictions from a group of experts. The standard approach -- using a proper scoring rule to separately reward each expert -- is not robust to collusion: experts may collude to misreport their beliefs in a way that guarantees them a larger total reward no matter the eventual outcome. Chun and Shachter (2011) termed any such collusion "arbitrage" and asked whether there is any truthful elicitation mechanism that makes arbitrage impossible. We resolve this question positively, exhibiting a class of strictly proper arbitrage-free contract functions. These contract functions have two parts: one ensures that the total reward of a coalition of experts depends only on the average of their reports; the other ensures that changing this average report hurts the experts under at least one outcome.

中文翻译：

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严格正确的合约函数可以是无套利的

我们考虑从一组专家中真实地引出概率预测的机制。标准方法——使用适当的评分规则来分别奖励每个专家——对串通并不有效：专家可能会串通错误地报告他们的信念，以保证他们无论最终结果如何都能获得更大的总回报。Chun 和 Shachter (2011) 将任何此类合谋称为“套利”，并询问是否存在任何真实的引出机制使套利变得不可能。我们积极地解决了这个问题，展示了一类严格合适的无套利合约函数。这些合约函数有两个部分：一是确保专家联盟的总回报仅取决于他们报告的平均值；