The Better Letter: Randomness Rules - by Bob Seawright - The Better Letter - 0 views
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randomness probabilistic thinking success skill luck contingent history

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We readily – routinely – underestimate the power and impact of randomness in and on our lives
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In his book, The Drunkard’s Walk, Caltech physicist Leonard Mlodinow employs the idea of the “drunkard’s [random] walk” to compare “the paths molecules follow as they fly through space, incessantly bumping, and being bumped by, their sister molecules,” with “our lives, our paths from college to career, from single life to family life, from first hole of golf to eighteenth.”
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Although countless random interactions seem to cancel each another out within large data sets, sometimes, “when pure luck occasionally leads to a lopsided preponderance of hits from some particular direction...a noticeable jiggle occurs.” When that happens, we notice the unlikely directional jiggle and build a carefully concocted story around it while ignoring the many, many random, counteracting collisions.
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As Tversky and Kahneman have explained, “Chance is commonly viewed as a self-correcting process in which a deviation in one direction induces a deviation in the opposite direction to restore the equilibrium. In fact, deviations are not ‘corrected’ as a chance process unfolds, they are merely diluted.”
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Such contingency explains why sports provide the world’s best reality show. The better team does not win every game.
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Its power, its meaning, and its joy are wrapped in its improbability. In retrospect, it seems destined. That the U.S. team was “born for this.” The truth is, despite the power and greatness of Brooks’ speech, it was anything but.
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As Stephen Jay Gould famously argued, were we able to recreate the experiment of life on Earth a million different times, nothing would ever be the same, because evolution relies upon randomness. Indeed, the essence of history is contingency.
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Mauboussin describes the “paradox of skill” as follows: “As skill improves, performance becomes more consistent, and therefore luck becomes more important.” In investing, therefore (and for example), as the population of skilled investors has increased, the variation in skill has narrowed, making luck increasingly important to outcomes.
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All-time great teams still lose about one out of every three games, all to inferior teams, demonstrating that winning baseball games involves a lot of luck.
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Since mean reversion establishes that the expected value of the whole season is roughly 50:50 (or slightly above or below that level), a 60 percent winning percentage being really good means that there is a lot of randomness built into baseball outcomes.
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Luck matters. A lot. Yet, we tend dramatically to underestimate the role of randomness in the world.
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The self-serving bias is our tendency to see the good stuff that happens as our doing (“we worked really hard and executed the game plan well”) while the bad stuff isn’t our fault (“It just wasn’t our night” or “we simply couldn’t catch a break” or “we would have won if the umpiring hadn’t been so awful”). Thus, desirable results are typically due to our skill and hard work — not luck — while lousy results are outside of our control and the offspring of being unlucky.
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Michael Mauboussin’s The Success Equation seeks to untangle elements of luck and skill in sports, investing, and business
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the ever-increasing aggregate skill (supplemented by massive computing power) of the investment world has come largely to cancel itself out.
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Meanwhile, Smith argues that effort and repetition mean a great deal to athletic success, but that innate talent, which cannot be taught, means even more. Thus practice — even perfect practice — does not make perfect.
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randomness explains why the best team or player doesn’t always win, even though the best will tend to win more often. Being very good merely improves the odds of success. It doesn’t guarantee it.
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we should all recognize that the outcomes in many activities in life combine elements of both skill and luck. Like baseball, investing is one of these. Understanding the relative contributions of luck and skill can help us assess past results and, more importantly, anticipate future results, a point to which Mauboussin pays particular attention.
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Lady Luck is crucial to investment outcomes. There is no getting around it. Managing one’s portfolio so as to benefit the most from good luck and (even more importantly) to get hurt the least by bad luck are the keys to investment management. Doing so well is a remarkable skill, but not the sort of skill that’s commonly assumed, even (especially!) by professionals.
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In the markets, the average investor underperforms due to costs alone. Poker is similar on account of the house’s rake. Yet most investors — like most poker players and most people generally, due to optimism bias — think they are better (and often much better) than the norm
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In a “quasi-experimental” study, researchers set out to examine these questions in poker. They got together a group of both expert and novice poker players to play fixed games, meaning that the players received hands that the researchers had set up – without the knowledge of the players – to test how things would go under various scenarios. The results revealed that while the cards dealt (luck) largely predicted the winner, skill was crucial to reducing losses when players were dealt a bad hand. That’s a true if unsurprising result as far as it goes. But the conclusion of the study (“that poker should be regarded as a game of chance”) is clearly overstated.
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It’s surely true that over the short term, luck dominates skill in poker. However, over longer and longer periods of time – a much larger database of hands – a slight skill advantage will result in a positive win rate because no player will have better cards in the aggregate. In other words, given enough time, luck cancels itself out.
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As Silver argues in The Signal and the Noise, especially when the skill differential is not great, the interesting question is how long it will take for skill to win out.
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consistent with the study – the primary reason is that the expert player makes fewer mistakes. Science seeks the truth by uncovering and discarding what is false. What’s left is likely to be true.
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As noted above, we all like to think that our successes are earned and that only our failures are due to luck – bad luck. But the old expression – it’s better to be lucky than good – is at least partly true. That said, it’s best to be lucky *and* good. As a consequence, in all probabilistic fields (which is nearly all of them), the best performers dwell on process and diversify their bets. You should do the same.
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what we should already know – market success (however defined), especially over the relatively short run, is more a matter of luck than of skill.
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nvestment performance data support this idea unequivocally. As Charley Ellis has shown, “research on the performance of institutional portfolios shows that after risk adjustment, 24% of funds fall significantly short of their chosen market benchmark and have negative alpha, 75% of funds roughly match the market and have zero alpha, and well under 1% achieve superior results after costs — a number not statistically significantly different from zero.”
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As Silver emphasizes in The Signal and the Noise, we readily overestimate the degree of predictability in complex systems [and t]he experts we see in the media are much too sure of themselves (I wrote about this problem in our industry from a slightly different angle…). Much of what we attribute to skill is actually luck.