There’s an old saying on Wall Street: “Everyone is a genius in a bull market.” If social media had existed back then, the saying probably would have been, “Everyone has a YouTube channel in a bull market.”
Every time the market starts ripping higher, the gurus hatch like cicadas. Suddenly everyone has the ultimate strategy, the holy grail indicator, and a thumbnail with a shocked face pointing at a stock chart. Apparently, they’ve all cracked the code.
Then the market drops 20%.
Funny how quiet YouTube gets.
I’ve been trading for over 30 years, and I’ve watched this cycle repeat more times than I can count. Bull markets create experts overnight. Bear markets collect résumés. Some gurus disappear because the market finally catches up with them. Others discover there’s a steadier paycheck in selling courses, Discord memberships, newsletters, and “exclusive communities” than there is in actually trading. I suppose consistency is consistency.
That’s not to say every trading educator lacks credibility. There are people who genuinely know what they’re doing and want to teach. The problem is that bull markets make it incredibly difficult to tell the difference between real experience and favorable market conditions.
One thing I’ve noticed over the years is how many engineers end up in trading. That’s not a criticism. Engineers are wired to solve problems, and markets certainly look like one giant math problem.
The trouble starts when someone decides they’ve solved it.
I constantly hear traders brag that they trade “purely statistically” because it removes emotion from trading. Fair enough. You absolutely should remove emotion from your decisions.
That doesn’t mean you’ve removed emotion from the market.
Becoming Spock doesn’t automatically make you a great trader.
The market isn’t a physics equation. It’s millions of people making emotional decisions, along with millions of algorithms reacting to those emotional decisions. Those algorithms don’t feel fear, but they’ll happily dump positions the moment their rules tell them to. Then other algorithms react to those algorithms, and before long you’ve got a feedback loop that looks suspiciously like panic.
Markets evolve because people evolve.
Algorithms evolve because people continually refine them, and increasingly AI is being used to help design and optimize trading models. As those models become more sophisticated, they also become more interconnected. One system reacts to another, triggering buying or selling that causes yet another system to react. That’s how feedback loops can develop and amplify market moves.
That doesn’t mean AI has solved the market. Far from it. AI is an incredibly powerful tool, but it’s still built by humans, trained on historical data, and capable of making mistakes. Generative AI models can hallucinate and produce convincing but incorrect answers. Trading models have their own limitations and can fail when market conditions change. Treating AI as an oracle is no different than believing you’ve discovered the one perfect indicator.
The edge that worked five years ago might not work today because everyone else—including the bots—is trading differently now. Markets adapt because the participants adapt. Yet every bull market produces a fresh crop of traders convinced they’ve found the one system that will work forever.
Good luck with that.
The traders I’ve respected most over the last three decades rarely claimed they’d solved the market. They talked about probabilities, risk management, and adapting when conditions changed. Funny enough, they’re usually still around after the next bear market.
Everyone is a guru in a bull market.
The bear market is where the market grades everyone’s homework.