2020/07/31 by Taleb, Nassim Nicholas, Bar-Yam, Yaneer, Cirillo, Pasquale · 1 citation
#Applications (stat.AP) #FOS: Computer and information sciences #FOS: Economics and business #FOS: Physical sciences #General Economics (econ.GN) #Methodology (stat.ME) #Physics and Society (physics.soc-ph)
paper · doi:10.48550/arxiv.2007.16096
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).