At the 2022 Greenwich Economic Forum-Miami, Black Swan author, Nassim Nicholas Taleb explains why correlation is unreliable as a due diligence tool. Coming as it does during an ongoing pandemic and in the middle of Vladimir Putin’s invasion of Ukraine, Taleb also discusses Wars and Pandemics and puts them into their proper risk buckets.
We are not naturally good at dealing with information.
Disinformation artists confuse you by focusing on noise over signal by playing on saliency, the same effect as the one discussed in Fooled by Randomness. We mistake the particular for the general, details for the ensemble, and noise for signal –all from the same mental bias.
The first part explaining the Bachelier equation and how options were priced traditionally.
Yaneer Bar-Yam and Nassim discuss the COVID-19 situation with some disagreements.
A first, very introductory presentation of fragility as linked to both nonlinearity and dislike of variations. Antifragility is almost the opposite, limited to a specific range of variations.
- Why everything fragile must be concave.
- The medical S curve.
- Why harm to the climate is necessarily nonlinear in dose response.
- How hospitals can be overcrowded unless there are redundancies.
Further discussions will be more technical.
Technical Appendix to the paper on violence: What do you do when the data looks like it is power law distributed over a broad range, but cannot be technically a power law? We use dual distribution and transport parameters between one and another.
Violence is from Extremistan, hence requires some more sophisticated tools since LLN works slowly. We see how Pinker’s thesis is bogus. We look at ways to integrate the factual unreliability of historical accounts. We look at transformations to analyze violence using Power law tools since the worst case is bounded at the contemporary population level.
Links to Papers with Pasquale Cirillo
On the statistical properties and tail risk of violent conflicts [TECHNICAL, PHYSICA A]
The Decline of Violent Conflicts: What Do the Data Really Say? [NONTECHNICAL, NOBEL FOUNDATION]
How to look at the risks of Covid vaccines, why they are much lower than you think. We never had a larger monitored sample size in history and it allows events that on average show up later to manifest themselves very early on. Rationale: It takes a long time in a casino for someone to win 8 times in a row. But if 8 billion people played at the same time you would certainly witness a minimum of such events every day.
Quick presentation of drawdowns and the necessity to use logarithms for returns.
Explaining path dependence and maximum drawdown. I made a mistake in terminology. What I called max drawdown is a local or “window drawdown” or “peak to the subsequent valley”. The real max drawdown is the one that goes from the peak to 80.