Paper: Tail risk of contagious diseases

Pasquale Cirillo & Nassim Nicholas Taleb

The COVID-19 pandemic has been a sobering reminder of the extensive damage brought about by epidemics, phenomena that play a vivid role in our collective memory, and that have long been identified as significant sources of risk for humanity. The use of increasingly sophisticated mathematical and computational models for the spreading and the implications of epidemics should, in principle, provide policy- and decision-makers with a greater situational awareness regarding their potential risk. Yet most of those models ignore the tail risk of contagious diseases, use point forecasts, and the reliability of their parameters is rarely questioned and incorporated in the projections. We argue that a natural and empirically correct framework for assessing (and managing) the real risk of pandemics is provided by extreme value theory (EVT), an approach that has historically been developed to treat phenomena in which extremes (maxima or minima) and not averages play the role of the protagonist, being the fundamental source of risk. By analysing data for pandemic outbreaks spanning over the past 2500 years, we show that the related distribution of fatalities is strongly fat-tailed, suggesting a tail risk that is unfortunately largely ignored in common epidemiological models. We use a dual distribution method, combined with EVT, to extract information from the data that is not immediately available to inspection. To check the robustness of our conclusions, we stress our data to account for the imprecision in historical reporting. We argue that our findings have significant implications, including on the extent to which compartmental epidemiological models and similar approaches can be relied upon for making policy decisions.

Link to the Paper – Tail risk of contagious diseases

Bloomberg: Black Swan Author Spars With Quant Legend Over Tail Risk Hedges

“Black Swan” author Nassim Nicholas Taleb and quant investing pioneer Cliff Asness have engaged in a vitriolic Twitter dispute over the esoteric world of tail-risk hedging that descended into personal insults.

The spat began when Taleb sent a pair of tweets accusing the $143 billion AQR Capital Management LLC of issuing flawed reports that say tail-risk hedging doesn’t work.

Link to Bloomberg article: Black Swan Author Spars With Quant Legend Over Tail Risk Hedges

Never use Single-point Estimates for Pandemics

Never produce a point estimate for risk management, esp. in a fat-tailed domain, rather show statistical properties. Never judge a risk management stance from point forecasts.

Informational Rescaling of PCA Maps with Application to Genetics

Nassim Nicholas Taleb∗, Pierre Zalloua, and Dan Platt
∗Corresponding author, [email protected] Dec 2019

We discuss the inadequacy of covariances/correlations and other measures in L-2 as relative distance metrics. We propose a computationally simple heuristic to transform a map based on standard principal component analysis (PCA) (when the variables are asymptotically Gaussian) into an entropy-based map where distances are based on mutual information.

PDF Download Link:…

[YouTube] On Warnings over Systemic Risks from Global Pandemics

Nassim Taleb, Universa Investment’s scientific advisor and distinguished professor of risk engineering at NYU, warned of an acute virus spreading throughout the planet in his 2007 book “The Black Swan.” In January, he also warned of the systemic risks of the coronavirus pandemic. He joins “Squawk Box” to discuss.

Note: If viewing this as an email please click through to the post to view content.

[YouTube] Tutorial: Simple Trick to see the effect of Power Laws

A simple tutorial explaining how in the presence of power laws (with low exponent) most of the body of the distribution becomes noise. Once you establish that a variable is in the power-law class, some necessary consequences come out. To debunk that history is dominated by tail events, you must show it does not follow a power law.

Note: If viewing this as an email please click through to the post to view content.