Podbit · Economist Podcasts
When Elm Wealth gave the same test to 5 expert macro traders, all five made money and on average more than doubled their stake. Their edge wasn't better prediction — it was disciplined bet sizing. On uncertain days they didn't trade at all. On high-conviction days they went all in.
Where this was said
At 17:37 · chapter starts 15:35
The Elm Wealth experiment didn't stop at human participants. The researchers also ran AI models through the same crystal-ball test and found the results were both reassuring and sobering. The machines correctly predicted market direction about 60% of the time — better than the 51% human average — but they made the same fundamental error: over-betting when uncertain and under-betting when confident. [1] — Joshua Roberts "AI models: 60% correct market direction: AI models tested in the same Elm Wealth experiment correctly predicted market direction 60% of the…" 17:00 Rosie Blau admits to finding it 'quite comforting' that the machines aren't brilliant at this. The real revelation comes when the five expert macro traders are introduced. Unlike the AI and lay participants, all five finished in profit, and on average they more than doubled their stake. [2] — Joshua Roberts "When Elm Wealth gave the same test to 5 expert macro traders, all five made money and on average more than doubled their stake. Their edge …" 17:37 Their edge wasn't dramatically better prediction — it was dramatically better bet sizing. On low-conviction days they chose not to trade at all. On high-conviction days they ramped up leverage aggressively. Roberts draws a broader lesson: the investing world obsesses over what to buy, but the more important question is how much to bet, calibrated to actual confidence. This, he argues, is possibly the most important question in investment, and the one we give the least thought to.
Markets don't move on events — they move on surprises versus expectations. If a great jobs report was already priced in, knowing it in advance is worthless. Participants in the Elm Wealth study called the market direction correctly only 51% of the time, barely above a coin flip.
AI models tested in the Elm Wealth experiment predicted market direction 60% of the time — better than humans — but made the same catastrophic mistake: they didn't calibrate bet sizes to their confidence. Even our supposed future overlords took too much risk when uncertain.
AI models tested in the same Elm Wealth experiment correctly predicted market direction 60% of the time, slightly better than humans, but still struggled with bet sizing.
All 5 expert macro traders recruited by Elm Wealth for the same experiment finished with profits and on average more than doubled their money.
Investors obsess over which stock or bond to buy. But the Elm Wealth study reveals the more important question is how much: calibrating bet size to confidence level. Getting this wrong is what caused ordinary participants — and AI models — to go bust even with tomorrow's headlines.
Sam built Algrow, a SaaS for finding viral content formats, with zero coding experience using ChatGPT and Cursor. Six months later: 10,000 users, $14K/month in revenue.
Sam's first MVP threw an application error on its very first user — and he shipped it anyway. The core idea worked, and that was enough to validate the product and keep users coming back.
Sam joined Discord voice chats, muted himself, and silently screen-shared his product. Users in the chat started tagging him asking what the tool was. No pitch needed — curiosity did the selling.
Most founders post links in Discord and immediately get banned for self-promotion. Sam's approach was the opposite: build rapport, help people with the tool, let word of mouth do the work.
Find where your ICP lives. Listen before building. Validate with DMs and Loom recordings. Build in public with users inside your own Discord server. Turn early adopters into advocates with free access.
Instead of fearing the self-promo ban in large Discord servers, create your own private server for your product. You funnel in ideal customers and build a relationship that email can't replicate.
Algrow helps creators find and replicate viral video formats, starting at $25/month. It analyzes subscriber counts, average views, and trending formats — and can even generate the videos with AI.
After weeks of Sam silently screen-sharing in a Discord server, the server owner — unprompted — made a full YouTube promotional video about Algrow. Sam paid nothing and asked for nothing.
Producer Gus admits Discord never crossed his mind as a customer acquisition channel. Pat connects the insight to a broader lesson: match your distribution channel to where your actual customers live.
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