Pre 1200: Beginnings
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Probability and risk was borne out of gambling
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It begun in Greece, when their philosophers were at the forefront of intellectual discussion
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Counting and numbers were needed before probability could be known
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Fibonacci and his series
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The golden ratio
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The abacus
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The number system was developed by hindus
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The centrepeice of the hindu number system was the invention of the number 0
1200 – 1700: A Thousand Outstanding Facts
The Renaissance Man
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Girolamo Cardano
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Extracted the first ideas of probability from gambling
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Was also a gambling addict
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Did a lot of work on combinations of numbers
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Luca Paccioli
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Came up with the “problem of Balla”, in which two players are playing a game of balla and it is cut short.
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The question is, how do you divide the pot among the two players?
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Evenly? But what about the player who is clearly winning?
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How much more should you give the winning player?
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The French Connection
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Blaise Pascal & Pierre de Fermat
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Spoke about Paccioli’s problem of Balla
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How should the pot be split?
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Very famous sets of letters were echanged between them
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Pascals triangle
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Pascals wager
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If hell is as bad as it is described and heaven as good, then no matter how small the probability of it being real, you should beleive just in case
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This is a probabilistic view of religion
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The Remarkable Notions of the Remarkable Notions Man
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Invariance
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Demographic data
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John Graunt’s “observations”
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Compiled insurance data
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Aggregated the first “statistics”
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Edmund Halley’s “Life tables”
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Predicted the occurence of a comet (Halley’s comet)
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Created an age distribution of the population
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Edward Lloyd’s coffee house -> Lloyds of london
1700 – 1900: Measurement Unlimited
Considering the nature of man
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Daniel Bernoulli (Jacob’s nephew)
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Utility theory (thinking of utility as a function of value)
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St Petersberg paradox
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Human Capital
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Loss aversion
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Differing levels of risk aversion
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“Exposition of a new theory of the measurement of risk”
The Search for Moral Certainty
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Jacob Bernoulli
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Abraham de Moivre (first observed and documented the bell curve)
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Thomas Bayes
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Moral certainty = Statistical Significance
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Inference & Bayes’ theorem
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Assumes that events happening in the future will follow the same pattern (distribution) as in the past
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Law of large numbers (Jacob Bernoulli)
The Supreme Law of Unreason
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Carl Freidrich Gauss
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Built on de Moivres observations of the bell curve
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Marquis Laplace
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Bell curve
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Stock market randomness
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Independence <–> Normal distirbution
The Man with the Sprained Brain
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Francis Galton
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Obsessed with measurement
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Lambert Quetelet
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The “average man” (L’homme moyen)
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Regression to the mean
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Average (“standard”) deviations
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Correlation
Peapods and Perils
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Regression to the mean
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Stock market overrreaction
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Dangers of expecting regression to the mean all the time
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What mean should be regressed to?
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At what point has normal shifted to a new location?
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The Fabric of Felicity
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Utility
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Which risks should be taken?
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Preferences and tradeoffs
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Daniel Bernoulli -> Jeremy Bentham -> William Jevons
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Bernoulli built the groundwork
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Bentham invented utility theory
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Jevons built on it
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1900 -> 1960: Clouds of Vagueness and the Demand for Precision
The Measure of our Ignorance
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Louis Bachalier: The theory of speculation
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Acceptance of uncertainty
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Birth of risk management
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Kenneth Arrow
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Practicality is introduced
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Risk management becomes more pragmatic
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There is so much randomness that nothing can be that precise
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The gravitational pull of an electron in the milky way can affect a game of billiards on earth
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The radically distant notion
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Frank Knight
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John Maynard Keynes
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Moving away from probablity theory and toward practical applications and risk
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Historical evidence cannot predict the future
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Keynes: Intervention from government removes uncertainty
The Man who counted everything except calories
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John von Neuman
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Game theory
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Oskar Morgenstern
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Rationality
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Other’s decisions as the cause of uncertainty
The Strange Case of the Anonymous Stockbroker
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Harry Markowitz: Optimal portfolio selection
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William Sharpe: CAPM model
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Max return sub to risk
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Min risk sub to return
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Variance may not be a good proxy for risk
Degrees of Beleif: Exporing Uncertainty
The failure of invariance
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Kahnemen and Tversky
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Prospect theory
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Behavioural biases: Humans dont always act rationally
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Loss aversion
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Ambiguity aversion
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Paradox of choice
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Experimental economics
The Theory Police
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Behavioural biases
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Decision regret
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Loss aversion
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Risk aversion
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Endowment effect
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Market rationality
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Market efficiency
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Risk management in the 1970s
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DeBondt & Thaler
The Fantastic System of Side Bets
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Derivatives (financial options) reallocate risk
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Black Scholes Merton model
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Volatiliy & risk vs direction
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1987 portfolio insurance crash
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Aimed to replicate a put option
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Sold stock on way down
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Bought as it came back up
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Problem was too many people were doing in, so as stock prices began to go down they crashed really fast
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1990s companies speculating in derivatives
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P & G
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Awaiting the wildness
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The future of risk management
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Models of the future
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Chaos theory
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Neural networks
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Genetic algorithms
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