81–90 of 212 posts
- does the AI perform the same trades given the same input?
- does the AI perform the same trades given slightly different inputs? (E.g. same data, but re-ordered)
Earlier quoted context omitted.
> Or a monkey. or just a stocktrader haha
> or just a stocktrader haha Many quant trading firms make 50%-100% annual returns, each year, over the past 15-20 years. The secret is leverage. And they do not accept outside investor money. Many hedge funds outperform the market. However, the returns after fees, to the passive outside investor underperform S&P500. But yes, publicly traded active ETFs generally underperform. But counter example is VGT or QQQ, both…
> The goal is to study how different LLMs interpret financial data and make decisions with real consequences. 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…
Real trades have transaction fees, latency, slippage, etc. - you can simulate all this, but it's hard to know if it's being simulated correctly or not. > their interpretation cannot be influenced by the fact that the trading orders are passed for real It's not going to make much difference with $5 trades, but the impact on the market is non-zero.
> BOUGHT TLRY
Thanks and Happy New Year
Also, the reasoning is partially a hallucination - "The holding period of 9 months aligns with the expected completion of Grayscale's pivotal Phase 3 Bitcoin ETF trial, a major catalyst for unlocking investor demand and driving trust value realization."
There is no such thing as a "holding period", nor are they doing a "Phase 3 Bitcoin ETF trial". It's possible the "Phase 3" thing is picked up from news about a drug company.
So props on doing proper double opt-in for newsletters.
Some things to watch out for:
- LLMs, by default, don't follow the best practices for trading or investing. Without careful constraints, they can ignore fundamental investment best practices. This is something I learned while building https://decodeinvesting.com/chat.
- I see Claude bought a penny stock SMX. This could be volatile, and the price could change significantly in 24 hours before the next execution at 9:30 am.
- The LLMs are day trading on some volatile securities; while LLMs could be good at day trading, unlike humans (we will find out), this setup has the disadvantage of only trading once a day.
Earlier quoted context omitted.
Real trades have transaction fees, latency, slippage, etc. - you can simulate all this, but it's hard to know if it's being simulated correctly or not. > their interpretation cannot be influenced by the fact that the trading orders are passed for real It's not going to make much difference with $5 trades, but the impact on the market is non-zero.
It's zero for all practical purposes and it'd be completely undetectable to every single system on earth. I do agree many times studies about model performance break down as soon as you force the researcher to actually connect it to the market and have to eat fees and so on.