.org (UNOFFICIAL news site)
Modern financial theory assumes that distributions are elliptical. We show what happens if the assumption doesn’t hold. And the assumption doesn’t hold.
Diversification does NOT reduce risks in the financial market; it causes near-certain long term blowups under any leverage.
Nassim Taleb joins EndCoronavirus.org Founder, Yaneer Bar-Yam, for a Town Hall discussion.
Website: EndCoronavirus.org
Join Us: EndCoronavirus.org/join
Take Action: Community.EndCoronavirus.org
Twitter: twitter.com/endCOVID19
Instagram: instagram.com/end_covid19
Facebook Page: facebook.com/endcoronavirus.org
Facebook Group: facebook.com/groups/endcoronavirus
For n observations, what is the hidden moment? What are you missing from the “empirical” distribution?
Say the maximum flood was 3 meters or maximum loss was 22%. What are we missing in the statistical properties?
Link to the Paper mentioned in the video – What You See and What You Don’t See: The Hidden Moments of a Probability Distribution
In this conversation, Nassim Taleb and Dr. Pasquale Cirillo speak about their paper on the tail risk of contagious diseases and other related things.
The paper will be available on this link on Monday, May 25 at 5pm (CET):
Link to the Paper – Tail risk of contagious diseases
ERRORS 101
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.
The history of Universa Investments featuring Nassim Taleb and Mark Spitznagel discussing tail hedging, their 20+ years of working together, and the importance of risk mitigation in investing.
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.
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.
For fat tailed distributions, the empirical distributions does not reflect the true statistical properties, particularly for extremes. This is a simplified side note to a paper with Mark Spitznagel on why people make a mistake by looking at raw historical data as “empiricism”.
So I am fed up with academics who say “we know it is fat tails” yet not understand the consequences.
This tutorial presents the intuitions of the randomness of sample correlation (spurious correlation) and the methodologies in derivations. Some later sections are somewhat technical as Nassim rederived an old equation with more precise functions (in order to apply to fat tails) and showed the distribution of the maximum of d variables with n points per variable.
This paves the way to the real scientific work on random matric theory under fat tails and the failure of Marchenko-Pastur.