VisualCapitalist just shared an infographic showing the Average IQ by state. It caught my eye and my interest. Here it is.

via VisualCapitalist.
When I first examined the chart, I focused on the state-by-state differences. Honestly, I was taken aback that some states scored higher than others. And by that, I mean it wasn't necessarily the states I would've predicted. But then I took a closer look at the scale and realized these differences are probably insignificant. The results essentially show that, on average, states' intelligence levels are... well, average.
I know a lot of smart people.
I also know many people who think they're smarter than they are (even the smart ones ... or, perhaps, especially the smart ones).
It's common. It's so common that there's a name for it—the Dunning-Kruger Effect.
Have you ever met someone who's so confident about what they think that they believe they know more than an expert in a field? That's the Dunning-Kruger effect. It's defined as a cognitive bias where a lack of self-awareness prevents someone from accurately assessing their skills.
Here's a graph that shows the general path a person takes on their journey towards mastery of a subject.

via NC Soy
The funny thing about the above image... it's not actually a part of the paper on the Dunning-Kruger Effect. But it's now so commonplace that people report that chart as fact—a fitting example of the effect.

David Fitzsimmons via Cagle Cartoons
Recognizing the "victims" of this effect in our daily lives can often be funny or frustrating. But we're all prone to this; it's a sign of ignorance, not stupidity.
This is a problem with all groups and all people. You're not immune to it, even if you already know about the cognitive bias resulting from the Dunning-Kruger Effect.
It should be a reminder to reflect inward - not cast aspersions outward.
Two different ways that people get it wrong, first is to think about other people and it’s not about me. The second is thinking that incompetent people are the most confident people in the room, that’s not necessarily true.
Usually, that shows up in our data, but they are usually less confident than the really competent people but not that much... - David Dunning
To close out, even this article on the Dunning-Kruger presents a simplification of its findings. The U-shape in the graph isn't seen in the paper, the connection that lack of ability precludes meta-cognitive ability on a task is intuitive, but not the only potential takeaway from the paper.
Regardless, I think it's clear we are all victims of an amalgam of different cognitive biases.
We judge ourselves situationally and assume "the best". Meanwhile, we often assume "the worst" of others.
We can do better ... it starts with awareness.
Progress starts by telling the truth.
Old School Wisdom Isn't Always So Wise ...
When I first got interested in trading, I relied on traditional sources and old-school market wisdom. For example, I studied the Stock Trader’s Almanac.
While there is some real wisdom in some of those sources, most might as well be horoscopes or Nostradamus-level predictions. Throw enough darts, and one might hit the bullseye.
Traders love patterns ... from head-and-shoulders, to Fibonacci sequences, and even Elliot Wave Theory.
Here’s an example from Samuel Benner, an Ohio farmer. In 1875, he released a book titled “Benner’s Prophecies: Future Ups and Downs in Prices,” where he shared the often-referenced chart called the Benner Cycle. Some claim it’s been accurately predicting market fluctuations for over 100 years. Let’s check it out.
Here’s what it gets right ... markets go up and down ... and that cycle continues. Consequently, if you want to make money, you should buy low and sell high ... It’s hard to call that a competitive advantage.
Mostly, you’re looking at vague predictions with +/- 2-year error bars on a 10-year cycle.
However, it was close to the dotcom bust and the 2008 crash ... so even if you sold a little early, you’d have been reasonably happy with your decision to follow the cycle.
We use a form of cycle analysis in our models … but it’s more rigorous, nuanced, and scientific than the Benner Cycle. The trick is figuring out what to focus on – and what to ignore.
Just as humans are good at seeing patterns, even where there are none ... they tend to see cycles that aren’t anything but coincidences.
In trading, “alpha” measures the excess return created by manager skill rather than luck or movement of the underlying market. As you might guess, both “art” and “science” are involved in that calculation. Profitable traders want to believe it’s a sign of their skill, while losing traders prefer to blame luck.
Nicholas Nassim Taleb pointed out in “Fooled by Randomness” that many successful traders, even those with decades-long careers, were likely more lucky than skillful. They just happened to be at the right firm, on the right trading desk, at the right time.
That said, I believe technology, algorithms, and AI are evolving into Amplified Intelligence - the ability to make better decisions, take smarter actions, and continually improve performance. We’re about to experience a huge asymmetric advantage ... those who understand technology and science (math, statistics, game theory, etc.) will have a real edge over those relying on more primitive techniques or gut instinct.
In a sense, this is another type of cycle.
The best traders I know believe that “smart money” takes “dumb money”. While it may sound harsh, this cycle has played out repeatedly over time. Cutting-edge science can seem like magic to those who don’t understand it. However, these capabilities give a significant advantage to those who possess and use them.
I believe the gap between smart and dumb money is widening. That represents a massive opportunity for those who recognize what’s coming.
This is a reminder that just because an AI chat service recommended something that made money, doesn’t make it a good recommendation. Those models may do some things well ... but they also might just have made a lucky prediction at an opportune time. Making scientific or mathematically rigorous market predictions probably isn’t an area to trust ChatGPT or one of its rivals (at least if you don’t understand how to ask AI to do something that you understand and believe gives you a real edge).
If you don’t know what your edge is, then you don’t really have one. This becomes even more important in the age of AI. It doesn’t matter if AI does what it’s supposed to unless you believe it is doing what you want.
Be careful out there.
Posted at 06:18 PM in Books, Business, Current Affairs, Ideas, Market Commentary, Science, Trading, Trading Tools, Web/Tech | Permalink | Comments (0)
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