Excellent summary of many important investment and management principles.
Book to be read more as a checklist.
Summary of main items of the book follows:
Part 1 Investment Philosophy
1. Be the house: Process and Outcome in Investing
Munger: mental models
Rober Ruffin 4 principles on decision making:
1. The only certainty is that there is no certainty
2. Decision are matter of weighting probabilities
3. Despite uncertainty we must act
4. Judge decision not only on results but also on how they were made
2. Investing - profession or business
average fund performance has no resemblance to actual investor returns
what should investment firm do
3. Frequency vs magnitude in Expected Value
the frequency of correctness does not matter; it is the magnitude of correctness that matters
emotionally loss has about two and half times the impact of gain of the same size
expected value = frequency x magnitude
Successful games features: 1. focus 2. lots of situations 3. limited opportunities 4 ante (bet only if your odds are good)
4. sound theory for the attribute weary: The importance of circumstance based categorization
attribute vs. circumstance
Theory building rules:
1. describe what you want to understand in words and numbers
2. classify the phenomena into categories based on similarities. The most important step.
3. build theory that explains the behavior of the phenomena, under what circumstances
4. must be falsifiable
5. Risky business: Risk, Uncertainty and Prediction in Investing
risk vs. uncertainty. Risk= known loss potential, uncertainty = unknown
Gigerenzer: Calculated risks rules:
1. degree of belief
2. Propensities
3. Frequencies.
pari-mutuel systems
6. Experts and Markets
For rules based systems with limited degrees of freedom, computers consistently outperforms individual humans. No computer is even close on beating top player in Go, a game with simple rules but 19 x 19 board.
In probabilistic domain with high degrees of freedom collectives outperform experts.
Tetlock study of investors. Poor results overall.
Hedgehogs know one big thing, foxes know little of everything and are not wedded to a single explanation.
7. hot hand investing: what streaks tell us about perception probability and skill
across domains, long streaks typically indicate skill
8. time is on my side: myopic loss aversion and portfolio turnover
Value of inactivity, impact of costs
9. Low down on the top brass: management evaluation
leadership, incentives and capital allocation skills
leadership: learning, teaching and self-awareness
learning: confront facts with brutal honesty, visit employees and clients, ask questions and listen the responses. Create environment that everyone in the organisation feels they can voice their thoughts and opinions without the risk of being rebuffed, ignored or humiliated. Management should encourage and reward intellectual risk taking.
Teaching is the ability to communicate a simple, clear vision to the organisation
Self-awareness requires both self confidence and humility. Self confidence means that given a set of facts, an executive can draw on his or her knowledge, experience and inputs,
Part 2 Psychology of Investing
10 Good morning: let the stress begin
Short term vs long term stress. Humans have no adaptation to long term stress.
Loss of predictability and loss of control are some of the main triggers of loss.
Stress causes shortening of the horizon.
11 all I really need to know I learned at Tupperware party
Free shoeshine, tupperware
Cialdini six tendencies: reciprocity, consistency, social validation, liking, authority, scarity
combine them to lollapalooza effect.
One useful technique to mitigate consistency is to think word as ranges of values with probabilities attached instead of series of single points.
mitigate scarity: figure out what the market already knows
12 all systems go: emotion and intuition in decision making
Kahneman system 1. generate impressions of the objects, system 2 is involved in judgements
Affect is "goodness" or "badness" we feel based on stimulus
Research: when the opportunity does not have strong affect, we tend to overweight the probability, when it does we tend to overweight the outcome. Lottery players tend to play as much if change of winning is one in ten million or one in ten thousand.
13. guppy love: The role of imitation in Markets
Imitation is built in to humans.
Good if: asymmetric information, agency costs, preference for conformity
Herding. Tipping point after which positive information takes over in feedback loop.
Men think in herds, men go mad in herds, while they recover their senses slowly and one by one.
14. beware of havioral finance: misuse of behavioral finance can lead to bad thinking
Markets can still be rational when investors are individually irrational as long as there is diversity of investor strategies. So the issue is not if investors are irrational, but whether they are irrational in the same way at the same time.
15. Long term expectation, El farol bar and kidding yourself
If no one else is rational it does not pay for you to be.
Hindsight bias.
16. Investing with naturalistic decision making
Use the first satisfactory idea that comes to mind and then look for the next one and so on.
People do not maximize, they satisfice.
Robert Olson five conditions for naturalistic decisions:
1. ill-structured and complex problems
2. information is incomplete, ambiguous and chancing
3. ill-defined, shifting and competing goals
4. stress because of time constraints, high stakes or both
5. decisions may involve multiple participants
Naturalistic decision making:
1. rely heavily on mental imagery and simulation in order to assess the situation and possible alternatives
2. ability to recognize problems by pattern matching
3. reason through analogy.
When problem is covered by rules and is just complicated, classical deductive models work well.
Collective diverse group of individuals solve the problem better than average individual.
17 weighted watcher: what did you learn from the last survey
strength or extremeness of evidence (how many blue balls)
weight or predictive validity of evidence (how many items sampled)
low strength, high weight: underconfidence
high strength, low weight: overconfidence
much of what passes as incremental information adds very little or no value, because investors do not properly weight information, rely on unsound samples or fail to recognize what the market already knows.
Part 3 Innovation and competitive strategy
18 The Wright Stuff: why innovation is inevitable
Romer value creation process: 1. those who create new instructions and 2. those who carry out instructions
Rival and non-rival goods
Recombine idea building blocks: More idea building blocks -> more innovation
19 Pruned for perfection: brain development
Starting with lots of alternatives and winnowing down to most useful ones turns out to be robust process
Utter-back: industry innovation: Fluid phase, transition phase, specific phase.
20 staying ahead of curve: linking creative destruction and expectations
new leader is always the challenger
excess returns come in the first 5 years of new entrant.
21. Is there a fly in your portfolio?Fruit flies and futility
The most direct consequence of rapid business evolution is that the time a company can sustain a competitive advantage is shorter now than in the past
clockspeed: product clockspeed and process clockspeed:
fast: pc, toys, semiconductor, cosmetics: product 1y, process 2-4y
medium: auto, fast food, machine tools, medical: product 4-10, process 10-20
slow: aircraft petro tobacco paper: product 10-20, process 20-40
Effects:
1. period of persistent performance are decreasing in time
2. hypercompetition is not limited to high tech
3. build series of competitive advantages
4. market consolidation, large market share negatively associated with superior returns
22 All the right moves - how to balance long term with short term
Chess master rules:
1. do not look too far ahead
2. develop options and continuously revise them based on changing conditions
3. know your competition
4. seek small advantages: slightly, slightly, slightly
Ability to read others and understand oneself
Eisenhardt and Sull strategy as rules:
1. how to rules. What makes process unique?
2. Boundary rules: what to pursue and what not
3. Priority rules
4. Timing rules
5. Exit rules
Establish between 2-7 rules.
23 survival of the fittest: Fitness landscape and Competitive Advantage
Improving fitness is about becoming more adapted to your environment.
Since fitness landscape has lots of peaks and valleys, even if species reach one peak, it may not be the global peak. To get to higher peak, the species must reduce it's fitness in the short term to improve it long term.
Fitness landscapes: stable, coarse or roiling
short jumps vs. long jumps
Companies that compete in roiling landscape must focus on long jumps because even if they find themselves at peak, the shifting landscape assures that the peak quickly disappears.
24 You'll meet a bad fate if you extrapolate
Data changes in models. Think of social security.
Big drivers in PE ratio are taxes and inflation.
25. I've fallen and can't get up: mean reversion and turnarounds
only appr 30% of fallen tech/retail companies sustained recovery.
26 Trench cooperation: considering cooperation and competition through game theory
trench warfare in WW1
Robert Axelrod prisoner's dilemma competition: tit-for-tat, tit-for-two-tats
27 great growth expectations
Compounding.
Average growth rates are independent of company size but growth rate variance declines with size
Part 4 Science and Complexity Theory
28 Diversify your mind
In complex adaptive systems the magnitude of the outcome may be disproportional to magnitude of input
29. Wisdom and whims of the collective thinking
ants: balance on exploiting existing food source and finding new ones
30 vox populi
Horace Barlow: intelligence is all about making a guess that discovers some new underlying order
In well defined systems, experts are useful because they can provide rules based solutions. In complex systems collection of individuals solves the problem better.
expert in complex system:
1. create simulation in your head. create many models
2. populate models from many sources
31 tail of two worlds: fat tails and investing
Experience and exposure in insurance business:
Experience: something learned based on history
Exposure: likelihood that something may happen
fat tails: large changes in prices are far more common than they should
32 integrating outliers: St. Petersburg paradox
St. Petersburg paradox: value of playing heads/tails 2 4 8 16,...
normal distribution vs. fractal distribution.
winner take most -> St. Peterburg paradox on valuing growth stocks
33 The Janitors dream: why listening to individuals can be hazardous to your wealth
Reductionism vs. janitors dream.
When systems have low complexity and define interactions linearly, reductionism is very useful.
Centralized control fails when systems have sufficent complexity.
Complex adaptive systems have the following features:
1. aggregation is the emergence of complex, large scale behavior from the collective interactions of many less complex agents
2. adaptive decision rules: agents take information from the environment and combine it with their own to make decisions
3. feedback loops where input of one iteration becomes input for next iteration.
4. nonlinearity. behavior is more complex than its parts
Efforts to top-down complex adaptive systems generally lead to failure.
Adaptive system is in stark contrast to classical economic theory.
Investors who view stock market as complex adaptive system avoid two traps:
1. constant search for cause for all effects
2. dwell on input of any individual on expense of understaning the market itself
On time pressure investors and managers often rely on heuristics and rules of thumb because they save time. Traps for using heuristics is availability heuristics. You use what is available, not what is useful
34 chasing laplace's demon: the role of cause and effect in markets
Complex adaptive systems: whole does not equal to sum of the parts. As a result, cause and effect defies simple explanation.
Laplace's demon: being knowing all particles and velocities in university may know how it plays.
complex adaptive systems do not accommodate such simple calculations. Many systems are self-organised critical systems. Criticality suggests non-linearity. Effect may be disproportionate to the cause. Think sand pile. Pitfalls:
1. confuse correlation to causation. Butter production to Bangladesh predicts S&P 500 index best.
2. anchoring. Say any number and people anchor their next answer to it.
35 Power laws
zipf law: rank x size = constant -> 1, 1/2, 1/3, 1/4, etc.
mandelbrot generalization:
1, 1/(1+constant), 1/(2+constant), ...
1/(1+constant) 1+constant, 1/(2+constant) 1+constant,
Applies to city sizes and company sizes.
36 pyramid of numbers; firm size, growth rates and valuation
studies show:
1. firm size distribution follows zipf law
2. variances of firm growth rates decrease with size
3. growth of large companies often stall
4. most industries follow identifiable life cycle
37 turn tale: exploring the Market's mood swings
flu spread: 1. contagiousness (how easily spread) and 2. degree of interaction (how many people bumb each others)
adoption threshold. market sentiment.
Mr. Market.
Mr. Market does not mind if you ignore him, you should never fall under his influence.
38 self affinity
Fractals: part resemble the whole. Looks the same no matter what is the scale. Price data looks the same, let scale be years, months, week, days or minutes.
how:
1. consider why returns are less than cost of capital
2. look for changes in returns not anticipated by markets
3. judge the likely longevity of the excess returns
4. strategy matters, how does management allocate it's time.
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Andrew Chappell
Do not listen to your friends. Read this before investing your money.
Reviewed in the United Kingdom on September 19, 2019