A few months ago I came across a Bloomberg article, [AI isn't ready Trading](https://www.bloomberg.com/news/articles/2026-05-06/ai-bots-auditioning-for-wall-street-trading-are-mostly-losing?cmpid=eveus&utm_campaign=eveus&utm_medium=email&utm_source=newsletter&utm_term=260506&utm_content=4208&sref=iFWW0xUZ), highlighting how new frontier models were highly unreliable, trading too often, producing inconsistent results, and losing money more often than not.
Everyone knows the saying, garbage in, garbage out, but I think what gets overlooked is that 99% of data is garbage, even when the numbers are technically correct, because it is unintelligible in its current form, even to a machine. To add insult to injury, there have been so many times where I've experienced Claude or Gemini glomming onto to the wrong thing or taking something out context, given how messy the web is, and produce something that's extremely misleading.
Despite the pitfalls, I ultimately think AI can help more than it can hurt. If it were given "clean" data, then it's off to the races, given how fast it can process it. I spent the past 9 months experimenting with this hypothesis across four strategies: value, momentum, small-mid cap fundamentals (not necessarily value), and a blend of fundamentals and momentum, and here's how each stacks up against the S&P's 9.8% year-to-date performance:
1. Value: +4.18% ytd
2. Momentum: +16.41% ytd
3. Fundamentals: +26.79% ytd
4. Momentum/Fundamental blend: + 2.87%
I'm pretty encouraged by these results overall, and am not too surprised that value has struggled, given that it's been mostly a losing trade for a long time at this point. Fyi, here are the holdings for value:
**Value**:
1. FG
2. SLDE
3. CASH
4. OSCR
5. NRDS
6. APAM
7. KFY
8. ADT
9. PENG (carrying almost all the weight)
10. TRV
11. UPBD
12. GL
13. SBH
14. NJR
15. KHC
16. CMCSA
17. ADUS
18. APOG
19. CAG
20. ASO
I'll share a link to a page that lists the rest of the holdings in the comments, in case anyone is interested. Curious to hear others' thoughts and their experiences with AI and investing.
