Quote of the week: 

“Goodness is the only investment that never fails.” – Henry David Thoreau  

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The value of doing things differently

“What tends to happen in any complex system is that if you over-optimize the parts, you’re actually damaging the whole.” I loved this line by Rory Sutherland, speaking in conversation with author and producer Rick Rubin. It’s an epic 3-hour podcast about many things, but in particular, it’s about creativity: how it works, why it works, and who is best at it. 

I’m a big fan of Rory’s classic book Alchemy, which explores consumer decision-making through the often irrational lens of behavioral psychology. Though Rory is ostensibly a marketer, his ideas—generally speaking, about breaking convention and thinking outside the box—will resonate among investors, entrepreneurs, and anyone passionate about becoming an outlier in any given field they are pursuing.

“The business problem… is destroying entrenched metrics. People become very, very comfortable about metrics. And in many cases, these metrics are further entrenched because people are incentivized on doing these things. And what tends to happen in any complex system is that if you over-optimize the parts, you’re actually damaging the whole. And that seems to happen here. And the healthy thing to do with metrics is make some of them subjective and change them every now and then. But once they take hold, they’re very, very persistent and very difficult to dislodge.”

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Discernment as edge

In April, the investing columnist Jason Zweig listed out what he characterized as the seven “virtues” among great investors: curiosity, skepticism, independence, humility, discipline, patience, and courage. Todd Wenning, an investor and writer of the Flyover Stocks blog, takes this idea a bit further and adds an 8th characteristic: Discernment. “Discernment,” Todd writes, “is recognizing when it’s time to be impatient and seizing upon a rare opportunity.” He continues: 

“Investing lore is steeped in stories about intrepid investors who bet big in a panic and built fortunes from being correct. Sir John Templeton, for example, famously borrowed money at the onset of World War II in 1939 to buy 100 shares of 104 companies selling at $1 or less per share. While that was a legendary move, we know the story because it was successful. For every legendary investment made near the point of actual ‘maximum pessimism’ that proved lucrative, there are hundreds of stories of investors who were wiped out playing the contrarian card too soon. We don’t hear those stories. Even if you can discern that fear is ruling the day and stocks are attractive long-term investments, it still takes tremendous emotional fortitude to bring out even the thimble when everyone else is taking shelter.”

A few more links I enjoyed:

How To Be Lucky – via Tom Morgan / Sapient Capital
“In stark contrast, ‘luck’ appears to be both quantifiable and trainable. Long-term studies by the psychologist Richard Wiseman have had some wild and amusing results. One of his experiments involved people who defined themselves as lucky and unlucky walking down a street with a $20 bill lying on the pavement. The lucky people noticed it and unlucky people didn’t. Self-defined lucky people weren’t any better at winning random games of chance like the lottery, but they had material advantages when it came to noticing positive opportunities presented by their environment.”
Letter to a Young Investor – via Vitaliy Katsenelson / The Intellectual Investor
“When you solve physics problems you expect the answers to extend several digits beyond the decimal point. Physics is an exact science. In investment classes you were given precise inputs to punch into mathematical models and thus were expected to spit out exact answers. But unlike the inputs you were given in your classroom problems, real-world inputs are imprecise; indeed, they can be downright hairy. Thus heed John Maynard Keynes’ advice: ‘I’d rather be vaguely right than precisely wrong.’ Vague rightness comes from understanding how things work and the relationships among variables.”
Large language models, explained with a minimum of math and jargon – via Understanding AI
“Further, prediction may be foundational to biological intelligence as well as artificial intelligence. In the view of philosophers like Andy Clark, the human brain can be thought of as a ‘prediction machine’, whose primary job is to make predictions about our environment that can then be used to navigate that environment successfully. Intuitively, making good predictions benefits from good representations—you’re more likely to navigate successfully with an accurate map than an inaccurate one. The world is big and complex, and making predictions helps organisms efficiently orient and adapt to that complexity.”

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