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On Single Point Forecasts for Fat-Tailed Variables
Published 31 Jul 2020 in physics.soc-ph, econ.GN, q-fin.EC, stat.AP, and stat.ME | (2007.16096v1)
Abstract: 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).
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