⭐ Key Notes

1. We underestimate the share of randomness in everything.
2. We are blind to probabilities.
3. We attribute success to skill, but failure to randomness.
4. Think in terms of expected value.
5. Life is nonlinear and small acts can have disproporionate consequences.
6. Consider alternative hisories and what could have happened.

Part I: Solon’s Warning

• That which is gained by chance, can also be taken away by luck.
• Things that require little luck are more resistant to randomness.

🎸 Chapter 1: if you’re so rich, why aren’t you so smart?

• Mild success can be explainable by skill.
• Wild success is attributable to variance.
• Risk-conscious hard work and discipline can result in a comfortable life.
• Lucky fools benefit from disproportionate luck, but attribute their success to non-random reasons.
• One of the reasons that people become leaders is not from skill, but rather from superficial impression, such as charisma.
• We must take into account both the observed and unobserved possible outcomes.
• Entrepreneurs and rockstars appear considerably richer than a dentist, but we must consider the average of all people who enter, not only the ones that succeed.

🔫 Chapter 2: a bizzare accounting method

• One cannot judge a performance in any given field by the results, but by the costs of the alternative.
• $10m earned through Russian roulette does not have the same value as $10m earned through diligent dentistry.
• Although the result may be the same, one has a greater dependence on randomness and consequences.
• Few people are gratefil for insurance that protects them from something that did not take place.
• People are terrible at assessing abstract risk, compared to specific risks.
• Risk is mediated by our emotional mind, not our rational mind.
• Theatrical displays – the existence of a risk manager has less to do with actual risk reduction, rather than the impression of risk reduction.

Simplification and journalism

• Arguments should be simplified to their full potential.
• Risk detection and risk avoidance are mediated in the emotional part of the brain, not the thinking part.
• Rational thinking mostly rationalises one’s actions by fitting some logic to them.
• Journalism plagues simplification by training our mind to seek complexity.
• What sounds intelligent is often suspicious.
• Most smart things that have been proven by science appeared as lunacies originally.

🎲 Chapter 3: a mathematical meditation on history

• Monte Carlo
  • Create artificial history.
  • Alternative sample path – invisible histories that could have happened, but did not.
  • Random sample path – a succession of historic events that start and end at given dates, but are subject to some varying uncertainty.
  • Monte Carlo simulation – generate thousands of random paths and look at the prevalent characteristics of their features.

• Learning from history
  • Learning from history does not come naturally to humans.
  • Reading history will not help you learn from other’s mistakes.
  • We do not even learn from our own history.
  • People attribute emotional reactions to past experiences and retain biases.
  • We create flawed causal event chains to make sense of previous events.

• Hindsight bias
  • Overestimation of knowledge due to subsequent information.
  • A mistake is not something to be determined after the fact, but in the light of the information until that point.
  • Those who are good at predicting the past will think that they are good at predicting the future.

• Distilled thinking
  • Progress means that some new information is better than past information.
  • People infer that because some inventions have revolutionised our lives, that we should favour new over old.
  • The opportunity cost of missing a new thing is miniscule compared to the garbage one has to go through to get to these jewels.
  • The many hours spent studying the news does not impact your current knowledge of the world.
  • Survival of the fittest will be the oldest, because older people have been exposed and are more resistant to rare events.

• Time scale
  • Time scale is important when judging events.
  • A 15% return with 10% volatility per annum translates into a 93% probability of success in any given year.
  • A narrower timescale drastically reduces the probability of success.
  • In the short term, one observes variance, not returns.

• Loss aversion bias
  • The pain of losing $100 is greater than the satisfaction of earning $100.
  • The negative effect can be up to 2.5x greater than the magnitde of a positive effect.

• Ergodicity
  • A point of a moving system will eventually visit all parts of the space that the system moves in.
  • Random samples from a process will represent its average statistical properties.
  • In the short-run the lucky fool may benefit from randomness.
  • In the long-run, the lucky would regress to the mean.

🖼 Chapter 4: randomness, nonsense, and the scientific intellectual

• Pleasurable randomness
  • If you are going to be fooled by randomness, let it be the beautiful and harmless kind.
  • We do not need to be rational and scientific with every detail – only those that could harm us.
  • Irrationality can be pleasurable – in art, poetry, religion.

• Deductive reasoning
  • Knowledge that stems from defined thinking.
  • Eg 2 + 2 = 4

• Inductive reasoning
  • Knowledge that flows from verifiable experience or observation.
  • Eg it rains in Spain.
  • Inductive statements can be difficult or even impossible to verify.

🧬 Chapter 5: survival of the least fit

• The cross-sectional problem
  • At a given time in the market, the most successful traders are likely to be those that best fit to the latest cycle.
  • Thos does not happen with dentists. Their profession is more immune to randomness.
  • What randomness gives, randomness can also take away.

• Market fools of randomness
  • Overestimation of the accuracy of beliefs.
  • Loyalty to ideas and over-attachment.
  • Changing the story to justify changing circumstances. Eg postponing a sale as part of denial.
  • No precise plan ahead of time, in the event of losses.
  • Absence of critical thinking – you method of determining value may be wrong, rather than the market failing to accomodate.
  • Denial and no clear acceptance when losses occur.

• Naive evolution
  • Many believe that organisms reproduce on a one-way route to perfection.
  • Negative mutations can survive, although usually do not last more than a few generations.
  • Darwinian fitness applies to species developing over a long time, not in the short-term.
  • We do not live in a world where everything continuously converges toward betterment.

⚖ Chapter 6: skewness and asymmetry

• Asymmetric outcomes
  • Median is the midpoint of a frequency distribution.
  • Expected value is a weighted average of possible outcomes.
  • Whenever asymmetry exists, the average has nothing to do with the median.
  • The probability of the loss needs to be judged in connection with the magnitude of the outcome.
  • It is not the likelohood of an event that matters, we must factor in the magnitude of the outcome.
  • History teaches us that things that never happened before do happen.
  • Greater information leads to greater confidence, which may or may not be justified.

🦢 Chapter 7: the problem of induction

• Induction
  • No amount of white swans can allow the inference that all swans are white.
  • The observation of a single black swan is sufficient to refute such a claim.
  • Data can be used to disprove a proposition, but never to prove one.
  • Maximising the probability of winning does not maximise the expected value from the game.

• Types of theories
  • Theories that are known to be wrong and have been adequately tested and rejected.
  • Theories that have not yet been known to be wrong, but are exposed to the possibility of falsification.
  • A theory can never be right. It can only be provisionally accepted.

• Pascal’s wager
  • It is optimal for humans to believe in God.
  • The upside is tremendous if God exists.
  • The downside is minimal.

Part II: Monkeys On Typewriters

🏡 Chapter 8: too many millionaires next door

• Survivorship bias
  • We only see winners and this skews our understanding of the odds.
  • Survivorship bias implies that the highest performing realisation will be the most visible.
  • We mistake one realisation among all possible random histories as the most representative one.

• Sample sets
  • Our opinions are defined by sample sets.
  • A couple that lives in a wealthy neighbourhood may feel unsuccessful, because they are surrounded by other successful people.
  • Sample sets include visible observations – we must find the invisible observations.

🎂 Chapter 9: it’s easier to fry an egg than to buy and sell

• Machiavellian luck
  • Machiavelli ascribed luck a 50% roles in life – the rest was cunning and bravura.
  • There are fields where skill is the driving force and randomness is low, such as dentistry.

• Population of investment managers
  • Even if the long-term expected return is negative, some money managers will exhibit great track records.
  • The expectation of the best track record depends more on the size of the sample, than the individual odds per manager.
  • The top performers are what we see due to survivorship bias.
  • In most cases, we are unaware of the true sample population.

• Hot hand fallacy
  • A random sequence of success that people believe will continue into the future.
  • The larger the deviation from the norm. the larger the probability of it coming from luck rather than skill.

• Reversion to the mean
  • Large outliers will revert to the mean.
  • When the deviation is disproportionate, the reversion effect will be more potent.
  • Not all deviations are caused by randomness, but luck does account for a large portion.
  • Human nature ascribes luck to failure, and skill to individual success.

• Data snooping
  • Misuse of data analysis to find patterns in data that can be presented as statistically significant.
  • Increases the risk of false positives.

• Birthday paradox
  • There is a one in 365 chance that you share a birthday with someone you meet randomly.
  • In a room with 23 people, there is a 50% chance that a pair shares the same birthday.

🦋 Chapter 10: losers take all – the nonlinearities of life

• Chaos theory
  • Small inputs can lead to a disproportionate response.
  • Chance events coupled with positive feedback will determine economic superiority – not and edge in expertise.
  • Our brain is not cut out for nonlinearities.
  • There are routes to success that are nonrandom, but very few people have the mental stamina to follow them.
  • There is a nonlinear effect behind success.

🦌 Chapter 11: randomness and our mind: we are probability blind

• Two sides of probability
  • We have different perceptions of the same probabilities.
  • Consumers consider a 75% fat-free hamburger different to a 25% fat burger.

• Satisficing
  • You stop when you get a near satisfactory solution.
  • It is an adequate result, not the optimal one.
  • We follow rules not because they are the best, but because they save time and effort.
  • If we were to optimise every step in life, it would cost us an infinite amount of time and effort.

• Emotional decisions
  • We cannot make decisions without emotions.
  • We feel emotions then find an explanation.
  • People overvalue their knowledge and underestimate their probability of being wrong.
  • The confidence interval matters more than the expected value.

• Normative vs positive
  • Normative – considers how things should be.
  • Positive – considers how things actually are.
  • Someone with $1m should be happy. But not if they started with $5m or everyone around them has more.

• System 1 vs system 2 thinking
  • System 1: effortless, automatic, associative, rapid thinking.
  • System 2: slow, deliberate, deductive, controlled thinking.

• Shades of probability
  • Conditional: the probability of an event occuring, given that another event has already occured.
  • Unconditional: probability irrespective of another event.
  • Joint: the compounding probability of evidence. The probability of a 1/10 event and a 1/10 event both happening is 1/100.

• Evidence vs evidence of absence
  • Absence of evidence – not yet found or unavailable.
  • Evidence of absence – observation that something or some effect does not exist.

• Signal and the noise
  • Significane – determining is something is meaningful or important.
  • Causality – determining if there is a cause-and-effect. Often confused with correlation.
  • Confidence level – determining the reliability of a statistical conclusion.

• Heuristics
  • Anchoring – comparison to a given reference.
  • Availability – estimating the frequency of an event according to the ease with which the event can be recalled.
  • Representativeness – gauge the probability that a person belongs to a particular social group by assessing how similar their characteristics are to the typical group member.
  • Simulation – the ease of mentally undoing and event and playing the alternative scenarios.
  • Affect – the emotions elicited by events determine their probability in your mind.

Part III: Wax In My Ears

• We are not intelligent or strong enough to fight our emotions.
• We are predisposed to be fooled by randomness.
• A book review is often far more descriptive of the reviewer than informational about the book itself.

• Wittinger’s ruler
  • Unless you have confidence in a ruler’s reliability – if you use the ruler to measure a table, you may also be using the table to measure the ruler.

🐦 Chapter 12: gambler’s ticks and pigeons in a box

• Skinner box
  • Skinner created a box that delivered food randomly to birds.
  • The birds developed dances in an attempt to influence the delivery of food.
  • We are not aware that events may be independent from each other.
  • Our bias is to immediately establish a causal link.
  • Gamblers are known to develop behavioural distortions as a resort of pathological association.

🔀 Chapter 13: probability and skepticism

• Skepticism
  • Nothing can be treated with certainty.
  • Various degrees of probability can be used to draw conclusions.
  • Remain open to changing your mind and self-contradiction.
  • We are programmed to build loyalty to ideas in which we have investes time.
  • One of George Soros’ strengths is that he revises his opinion rapidly and without embarassment.
  • Beliefs are path dependent if the sequence of ideas is such that the first one dominates.

• Ten sigma events
  • Probability is not about the odds – it is about the belief of an alternative outcome, cause, or motive.
  • We have been getting things wrong in the past and we laugh at our past institutions.
  • It is time to figure out what we should avoid enshrining the present ones.

• Attribution bias
  • We attribute success to skill, but failures to randomness.
  • It is a human heuristic that we believe to protect our self-esteem and keep going through adversity.
  • Scinece evolves from funeral to funeral.

🕊 Chapter 14: Bacchus abandons Anthony

• Stoicism is the attempt by man to get even with probability.
• The only article that Lady Fortuna has no control over, is your behaviour.
• The stoic is immune from life’s gyrations, as he will be superior to the wounds from life’s dirty tricks.

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