How to Forecast an Election and a Practical Measure of Fat-Tailedness from the Preasymptotic Behavior of Sums
We are delighted to announce the upcoming lecture for Nassim N. Taleb who will discuss: "How to Forecast an Election and a Practical Measure of Fat-Tailedness from the Preasymptotic Behavior of Sums."
Nassim Nicholas Taleb spent two decades as an option trader. He is currently a researcher in practical and technical problems with probability and studies how to build systems that can handle disorder. He is the author of the Incerto, a 4-volume investigative essay on uncertainty (which includes The Black Swan and Antifragile). The Incerto has for back-up more than 50 scholarly papers in medicine, decision science, statistical physics, quantitative finance, statistics, philosophy, international relations, and war/peace studies. He is currently a professor in the Department of Finance and Risk Engineering of the Tandon School at NYU.
Taleb’s work has close to 130 translations in 36 languages.
How to Forecast an Election: Introduces continuous time martigale approach to an election forecasting process and shows arbitrage bounds. Contrary to common practice, under high uncertainty, forecasts should vary minimally and stay close to 50%.
A Practical Measure of Fat-tailedness from the Preasymptotic Behavior of Sums: Introduces a measure of fattaildness based on the volatility of the behavior of the average of a sum of random variables. Shows that finite-variance Pareto distributions can be fatter-tailed than those in the Lévy-Stable distribution class.
Attendees must register and seating is limited. This lecture is for FRE faculty and students only. We look forward to seeing you at the event.
To attend this seminar, please follow the link below to request an invitation: