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Right now they are just buying, no one is selling ... interesting.
I would guess that LLMs are biased towards making a positive assessment of ambiguous information, with specific social triggers prompting negative reaction.
This is fun! What kind of prompts / prompting techniques are you using?
1. Role + Goal Setting: The AI acts as a creative market analyst focused on discovering overlooked opportunities and emerging trends.
2. Structured Analysis Framework: - Detailed evaluation criteria (innovation, moat, management, growth potential) - Sector diversity requirements - Focus on finding hidden gems vs obvious mega-cap tech stocks
3. Time-Bound Precision: Instead of vague "3-6 months" holding periods, I require exact hour calculations tied to specific catalysts like: - FDA approval dates - Earnings releases - Product launches - Conference presentations
4. Quality Controls: - Must be valid NYSE/NASDAQ symbols - Diverse across sectors/market caps - Conviction level scoring (1-10) - Each pick needs unique thesis + catalyst - JSON output format for consistency
The key is combining structured analysis with creative discovery - pushing the AI to look beyond obvious choices while maintaining some analytical rigor.
What, could go wrong?
> Best Performer: AIs are tied > Total Profit: $0.00
I don't really buy this. If the goal was to study how different LLMs interpret financial data there would be no use for actual trades, since their interpretation cannot be influenced by the fact that the trading orders are passed for real.
I believe the goal is to see if AI can do better than rats [0]. There is no shame in that.
[0]: https://www.vice.com/en/article/rattraders-0000519-v21n12/
Earlier quoted context omitted.
I would guess that LLMs are biased towards making a positive assessment of ambiguous information, with specific social triggers prompting negative reaction.
Also it's hard to sell before buying, and it looks like it's only been going 2 days.