Is it all random?
A few physicists have extended the debate to portfolio suggesting investment management is vain. Money is made because of luck. In The Drunkard's Walk, Leonard Mlodinow says success or outperformance is a myth. Suddenly the physicist's societal framework for randomness resembles Malcolm Gladwell's sequel.
Is success because of chance? Thinkers like Gerolamo Cardano, Abraham de Moivre or Joseph Jagger have deliberated chance. Though Mlodinow details the chronology of randomness driven by the evolution of probability and human understanding of universal patterns, he fails to address randomness in totality and gives in to a subjective conclusion: Persistence as a possible answer to success.
So, a section of the scientific community has unknowingly let the Street in the debate. For the investor, randomness is so interdisciplinary he can't only comprehend the big picture but also cross-question physicists, mathematicians and behavioral gurus.
Chance, cause and control
Mlodinow says society is different, more prone to be ruled by chance as it relies more on causal links. People like to exercise control over environment. Hence the conflict in an uncertain one. That doesn't mean we can't train a section of society in counter-intuitive thinking and patterns of randomness. Saying humans are error-prone, markets inefficient, offering opportunities because of chance, is confusing. In my "End of behavioral finance" I spoke of how it had chosen to glorify psychological errors rather than identifying, and working around universalities.
Outliers, extreme reversion, outperformance
Behavioural finance chose to explain psychological errors based on mean reversion failures; Mlodinow chose to highlight mean reversion as a key idea in randomness without suggesting a method to benefit from it; Mandelbrot and Taleb were more about challenging mean reversion focusing on fat tails and outliers. Mlodinow says, "We can't know if our single observation represents the mean or an outlier." Randomness could be simplified if we could link outliers with reversion and call it extreme reversion. This way we could identify outliers, classify those and even anticipate a reversion. This way Mlodinow won't have to write a book on randomness without talking about reconciling a random event with fat tails, a reality of natural randomness, too.
Dragon kings and beating the market
Didier Sornette at Swiss Finance Institute has a theory of determining outliers where he shows how black swans are eaten by dragon kings. Overplaying underperformance works against randomness theorists. There are enough passive-indexing approaches that can not only showcase superior performance compared to the universe at lower risk but also showcase this outperformance consistently. Better risk management is not all chance.
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