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Comment by _pdp_ | Hacker News Reader

I think this might work.

When I started working no the trading agent I mentioned above I wanted to see if it can be just a better investor over the long run. The intention was not to do high-frequency trading. As you can see most of the days it is not taking any actions. The losses where down to mistakenly setting the stop losses too close to the top. If it wasn't so careful it might have made some money tbf.

My gut feeling is that AI agents will be able to manage a long-term portfolio much better than a human. Though it is just a gut feeling.

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Lmao, you llm people have some crazy delusions. You realize markets are zero sum, and if you're using a public model that everyone else also has access too, you llm psychos will destory eachothers "agentic" edge (not that there ever was one). Not to mention all the other obvious flaws with llms, lime having an effective memory of ~200k words and no ability to judge whats actually going on in the real world.

You really have no idea what you are talking about.

I have been running an intermittent experiment with a multi agent "investment firm" for over a year now across model releases.

They certainly can beat indexes, BUT.. the model families have some biases that you have to design around. The stop loss that bit the parent is certainly one. The models like to create rules. Often rules, one of those is making all kinds of exit conditions.

Another big one from my experience is the bias to inaction in a scenario with risk. This means a model without structure around it will bias to keeping too much cash.

This would be nice if it was supported by some hard data. But even if it was, one year is too short of a timeline to make any kind of reasonable conclusions about its efficacy.

Buying stock based on coin flips can beat indexes short term too, that does not mean it is a better strategy or that it works over the long term.

There must be some room for some anti-llm agent that can profit from specific behaviors of these models when deployed against actual markets.

The idea that somebody here came up with idea that all professional algo traders didn't explore to the last penny a year if not more ahead of others is funny... but its not my money adding liquidity to the markets.

Come to me when you have 500 trades and can beat Vangaurd's-VOO over a multi year time frame. Ill bet my entire networth and all future earnings for the rest of my life that your bot doesnt beat it. Your llm induced Dunning Kruger is going to get you in trouble one of these days I promise.

Look, it isn't fool proof and it is dangerous. With the current models you need to understand both markets and model biases and dynamics.

However with that said they are a huge multiplier and can tirelessly analyze the market for you.

They certainly can be used to beat sp 500 quite easily, but again that requires some understanding of risk on your part because the models will do what you ask them. If you go all in on options or something without clear risk management you will lose your ass.

Is it opensource?

"just trust me bro"

The 'edge' is holding the investments over long periods of times. Agents are merely automating the portfolio managing part for lower costs.

Sure, but why would the organizations managing ETFs employ the same low cost agents + their own insights and provide a better return.

Yeah and you probably have to. An ETF easily has >1000 different stocks and even being weighted. So it has a completely different risk appetite by being so averaged.

But ETFs do have to follow particular rules defined by their product description. So it is still interesting to benchmark against.

Markets are only zero-sum in any given trade. Allocating capital to assets with higher growth rates (on the marginal dollar) creates value in the long run.

So, very simply, if AI can actually do better at picking a better long-term winner then it will increase growth.

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