Taleb Nassim Nicholas, Bar-Yam Yaneer, Cirillo Pasquale
Universa Investments, Miami, United States of America.
Tandon School of Engineering, New York University, New York City, NY, United States of America.
Int J Forecast. 2020 Oct 20. doi: 10.1016/j.ijforecast.2020.08.008.
We discuss common errors and fallacies when using naive "evidence based" empiricism and point forecasts for fat-tailed variables, as well as the insufficiency of using naive first-order scientific methods for tail risk management. We use the COVID-19 pandemic as the background for the discussion and as an example of a phenomenon characterized by a multiplicative nature, and what mitigating policies must result from the statistical properties and associated risks. In doing so, we also respond to the points raised by Ioannidis et al. (2020).
我们讨论了在对厚尾变量使用朴素的“基于证据”的经验主义和点预测时常见的错误和谬误，以及使用朴素的一阶科学方法进行尾部风险管理的不足。我们以新冠疫情为讨论背景，并将其作为一个具有乘法性质的现象的例子，以及根据统计特性和相关风险必须采取哪些缓解政策。在此过程中，我们也回应了Ioannidis等人（2020年）提出的观点。
