英文标题：
《Election predictions are arbitrage-free: response to Taleb》
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作者：
Aubrey Clayton
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最新提交年份：
2019
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英文摘要：
  Taleb (2018) claimed a novel approach to evaluating the quality of probabilistic election forecasts via no-arbitrage pricing techniques and argued that popular forecasts of the 2016 U.S. Presidential election had violated arbitrage boundaries. We show that under mild assumptions all such political forecasts are arbitrage-free and that the heuristic that Taleb\'s argument was based on is false.
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中文摘要：
Taleb（2018）提出了一种通过无套利定价技术评估概率选举预测质量的新方法，并认为2016年美国总统选举的流行预测违反了套利界限。我们证明，在温和的假设下，所有这些政治预测都是无套利的，塔勒布的论点所基于的启发是错误的。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Mathematical Finance        数学金融学
分类描述：Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法，包括随机、概率和泛函分析、代数、几何和其他方法
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一级分类：Mathematics        数学
二级分类：Probability        概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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