How much data do you need? An operational, pre-asymptotic metric for fat-tailedness

Nassim Nicholas Taleb

International Journal of Forecasting, 2019, vol. 35, issue 2, 677-686

Abstract: This paper presents an operational metric for univariate unimodal probability distributions with finite first moments in [0,1], where 0 is maximally thin-tailed (Gaussian) and 1 is maximally fat-tailed. It is based on the question, “how much data does one need to make meaningful statements about a given dataset?”

Keywords: Heavy tails; Limit theorems; Risk management; Large deviations (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:35:y:2019:i:2:p:677-686

DOI: 10.1016/j.ijforecast.2018.10.003

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