How to build by tinkering with a positive definite correlation matrix for Monte Carlo simulations for a given dimensionality.
Category: MOOCs
[YouTube] MINI LECTURE 17: Maximum Ignorance Probability (a bit more technical)
What do you do when you must estimate a probability and there is ZERO information? A surgeon did 60 operations with 0 failure. What’s her or his failure rate? I didn’t realize that the trick wasn’t in the literature until John Hughes wrote a paper in Statistics and Probability Letters based on my blog post presenting the idea.
[YouTube] MINI LECTURE 16: On the Absurdity of Standard Genetics Reports
Why reports from genetic firms saying you are 30% Greek, 15% Sicilian, and 5% Martian are complete misrepresentations?
[YouTube] MINI LECTURE 15 – Conditional vs. unconditional correlation: twin studies overestimate heredity
The genetics of twin studies have a bias showing more heredity than in reality, owing to a statistical artifact. The twin studies for heredity are based on comparing the correlation between 2 identical twins minus that between 2 fraternal ones (assumed to be sharing half their genes). The use of fraternal twins as control is assumed to extract the “environmental” factors. Problem: Correlation is conditional and psychologists think it is unconditional. We show how the math is entirely different. The core error is that genes and environment are not separable and additive.
[YouTube] First Course on Fragility, Convexity, and Antifragility (Nontechnical)
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.
Explains:
- 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.
[YouTube] Ellipticality (Technical)
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.
What is Invisible in the Probability Distribution?
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
[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.
[YouTube] Explaining both the XIV trade and why forecasting is BS
Antifragile explains why understanding x is different from f(x) the payoff or exposure from x. Most of the harm/gains come from f(x) being convex or concave not understanding x. Forecasting is off an average, and average is for academics and other morons.
This video illustrates the point with XIV that went bust while being correct about volatility –and why people who make money are usually wrong.
[YouTube] Jouer sa peau, le nouveau livre de Nassim Nicholas Taleb
Pourquoi devrait-on cesser d’écouter ceux qui parlent au lieu d’agir ? Pourquoi les entreprises font-elles faillite ? Comment se fait-il que nous avons plus d’esclaves aujourd’hui qu’au temps des Romains ? Pourquoi imposer la démocratie aux autres pays ne marche jamais ?
Réponse : trop nombreux sont ceux qui dirigent le monde sans mettre leur peau en jeu.
Dans son livre le plus provocateur à ce jour, Taleb donne sa définition et ébranle les nôtres : qu’est-ce que comprendre le monde, réussir sa vie professionnelle, contribuer à une société juste ou injuste, détecter les non-sens et influencer les autres ?
D’Hammourabi à Sénèque, du géant Antée à Donald Trump, de Kant à Gros Tony, Taleb choisit ses exemples et montre qu’avoir quelque chose à perdre, vouloir accepter le risque, y voir une question de justice, d’honneur et de sacrifice, est pour les héros, les saints et bon nombre d’êtres humains épanouis… une essentielle règle du jeu.