Thread

1. glimshe · 1789660950 · focus · HN ↗

   Product idea: a LLM trained separately from mainline LLMs that anticipate market trends by analyzing how mainline LLMs will invest. As retail investors will probably use mainline AI for decisions going forward , one could get an edge.

   "The AI-driven Market Hypothesis"

   Please let me know where I should pick up my Nobel prize.

   1. codebastard · 1789661145 · focus · HN ↗

      Would you not then also copy the investments? Or are you trying to inverse the trades by an unpredictable time factor reasoning that thanks to AI the underlying stock is over- or underpriced?

      1. in_absentia · 1789663747 · focus · HN ↗

         A lot of algorithmic trading is short-term, essentially trying to guess what other parties may be selling or buying so that you can front-run them and then collect a fee. Kinda like ticket scalping, except we accept it and have a retro-justification for why it's good ("improving liquidity").

         Or, in the best case, you're trying to mine signals few days before earnings or some other big story and bet on the directional outcome of that.

         Fully-algorithmic long-term trading is of dubious benefit simply because that's driven to a much greater extent by geopolitics and macroeconomic trends, unforeseen scandals, successful product launches, and so on. As an example, you can believe that AR / VR is the future; I don't disagree. And in 2013, you might have inferred that Google is working on a revolutionary miniature AR headset. But you would not have made money if you bet on that turning out to be a hit. So even if you had a way to automate this bet, it would not have been a good bet.

         1. cj · 1789664319 · focus · HN ↗

            I was under the impression that front-running was something that happened in the span of seconds (or milliseconds), not a timeframe compatible with LLM inference time.

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