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We gave 5 LLMs $100K to trade stocks for 8 months

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Re: We gave 5 LLMs $100K to trade stocks for 8 months

#251

Post by tim333 »

derrida wrote: post #173
chroma205 wrote: post #164

Earlier quoted context omitted.

>but for various reasons can end up flopping when actually executed in the real market. 1. Your order can legally be “front run” by the lead or designated market maker who receives priority trade matching, bypassing the normal FIFO queue. Not all exchanges do this. 2. Market impact. Other participants will cancel their order, or increase their order size, based on your new order. And yes, the algos do care about your…

Dear HFT Quant, > And yes, the algos do care about your little 1 lot order. I'm just your usual "corrupted nerd" geek with some mathematics and computer security background interests - 2 questions if I may 1. what's like the most interesting paper you have read recently or unrelated thing you are interested in at the moment? 2. " And yes, the algos do care about your little 1 lot order." How would one see this effect…

Retail speculator here. Re 2 it's often quite easy to demo on thinly traded markets - I'm more familiar with crypto. Say the spread is 81.00 buy, 81.03 sell. Put in a limit buy at 81.00 and watch someone/something immediately outbid you ate 81.01. In the short term that kind of thing is done by algorithms but there are humans behind it and doing it too.

There's quite a lot of other game playing going on also.

Re: We gave 5 LLMs $100K to trade stocks for 8 months

#252

Post by bwfan123 »

portly wrote: post #235

What is the point of this? LLMs are trained to predict the next word in a text. In what way, shape or form does that have anything to do with stock market prediction? Completely ridiculous AI bubble nonsense.

shhh. We need more of these as counter-parties to improve alpha.

Re: We gave 5 LLMs $100K to trade stocks for 8 months

#253

Post by [deleted] »

keepamovin wrote: post #170

I’d say Grok did best because it has the best access to information. Grok deep search and real time knowledge capabilities due to the X integration and just general being plugged into the pulse of the Internet a really best in class. It’s a great OSINT research tool. Interesting how this research seems to tease out a truth traders have known for eons that picking stocks is all about having information maybe a little…

[deleted]

Re: We gave 5 LLMs $100K to trade stocks for 8 months

#254

Post by this_user »

chroma205 wrote: post #242
this_user wrote: post #208

Earlier quoted context omitted.

If you actually were in the industry, you would know that most retail traders don't fail, because they lose a tick here or there on execution, they fail, because their strategies have no edge in the first place.

> If you actually were in the industry, you would know that most retail traders don't fail, because they lose a tick here or there on execution Where did I say “retail trader”? Because “institutional” low-latency market makers trade 1 lot all the time.

The context from parent was obviously that. Instis don't trade on Alpaca.

> Because “institutional” low-latency market makers trade 1 lot all the time.

That sentence alone tells me that you're a LARPer.

Re: We gave 5 LLMs $100K to trade stocks for 8 months

#255

Post by tim333 »

bmitc wrote: post #142
naet wrote: post #62

I used to work for a brokerage API geared at algorithmic traders and in my experience anecdotal experience many strategies seem to work well when back-tested on paper but for various reasons can end up flopping when actually executed in the real market. Even testing a strategy in real time paper trading can end up differently than testing on the actual market where other parties are also viewing your trades and makin…

I've honestly never understood what backtesting even does because of the things you mention like time it takes to request and close trades (if they even do!), responses to your trades, the continuous and dynamic input of the market into your model, etc. Is there any reference that explains the deep technicalities of backtesting and how it is supposed to actually influence your model development? It seems to me that o…

I'm not sure about deep technicalities but backtesting is a useful thing to see how some strategy would have performed at some times in the past but there are quite a lot of limitations to it. Two of the big ones are the market reacting to you and maybe more so a kind of hindsight bias where you devise some strategy that would have worked great on past markets but the real time ones do something different.

https://en.wikipedia.org/wiki/Long-Term_Capital_Management was kind of an example of both of those. They based their predictions on past behaviour which proved incorrect. Also if other market participants figure a large player is in trouble and going to have to sell a load of bonds they all drop their bids to take advantage of that.

A lot of deviations from efficient market theory are like that - not deeply technical but about human foolishness.

Re: We gave 5 LLMs $100K to trade stocks for 8 months

#256

Post by bwfan123 »

Genego wrote: post #107

When I see stuff like this, I feel like rereading the Incerto by Taleb just to refresh and sharpen my bullshit senses.

LLM is the fad of the day, and these sort of articles provoke the natural get-rich-quick-greed inherent in all of us, especially the young tech-types. As such they are clickbait, and also a barometer of the silliness that is widespread.

I am curious why re-reading incerto sharpens your bullshit sense. I have read a few in that series, but didnt see it as sharpening my bullshit sensor.

Re: We gave 5 LLMs $100K to trade stocks for 8 months

#257

Post by Maxatar »

chroma205 wrote: post #164
naet wrote: post #62

I used to work for a brokerage API geared at algorithmic traders and in my experience anecdotal experience many strategies seem to work well when back-tested on paper but for various reasons can end up flopping when actually executed in the real market. Even testing a strategy in real time paper trading can end up differently than testing on the actual market where other parties are also viewing your trades and makin…

>but for various reasons can end up flopping when actually executed in the real market. 1. Your order can legally be “front run” by the lead or designated market maker who receives priority trade matching, bypassing the normal FIFO queue. Not all exchanges do this. 2. Market impact. Other participants will cancel their order, or increase their order size, based on your new order. And yes, the algos do care about your…

>Your order can legally be “front run” by the lead or designated market maker who receives priority trade matching, bypassing the normal FIFO queue. Not all exchanges do this.

Unless you're thinking of some obscure exchange in a tiny market, this is just untrue in the U.S., Europe, Canada, and APAC. There are no exchanges where market makers get any kind of priority to bypass the FIFO queue.

Re: We gave 5 LLMs $100K to trade stocks for 8 months

#258

Post by Maxatar »

bmitc wrote: post #142
naet wrote: post #62

I used to work for a brokerage API geared at algorithmic traders and in my experience anecdotal experience many strategies seem to work well when back-tested on paper but for various reasons can end up flopping when actually executed in the real market. Even testing a strategy in real time paper trading can end up differently than testing on the actual market where other parties are also viewing your trades and makin…

I've honestly never understood what backtesting even does because of the things you mention like time it takes to request and close trades (if they even do!), responses to your trades, the continuous and dynamic input of the market into your model, etc. Is there any reference that explains the deep technicalities of backtesting and how it is supposed to actually influence your model development? It seems to me that o…

We use back testing at my firm for two primary reasons, one as a way to verify correctness and two as a way to assess risk.

We do not use it as a way to determine profitability.

Re: We gave 5 LLMs $100K to trade stocks for 8 months

#259

Post by arisAlexis »

knollimar wrote: post #239
arisAlexis wrote: post #202

Earlier quoted context omitted.

You believe in the tech sector because technology always goes well and it's what humans strive to achieve, not because it has done well recently. It has always.

When does the tech sector become the computer sector? Agriculture would have been considered tech 200 years ago.

full throttle until AGI is achieved, then we will see

Re: We gave 5 LLMs $100K to trade stocks for 8 months

#260

Post by giantg2 »

hxtk wrote: post #175
tshaddox wrote: post #67

Earlier quoted context omitted.

> It would almost be more interesting to specifically train the model on half the available market data, then test it on another half. Yes, ideally you’d have a model trained only on data up to some date, say January 1, 2010, and then start running the agents in a simulation where you give them each day’s new data (news, stock prices, etc.) one day at a time.

I suspect trading firms have already done this to the maximum extent that it's profitable to do so. I think if you were to integrate LLMs into a trading algorithm, you would need to incorporate more than just signals from the market itself. For example, I hazard a guess you could outperform a model that operates purely on market data with a model that also includes a vector embedding of a selection of key social and…

"includes a vector embedding of a selection of key social and news media accounts or other information sources that have historically been difficult to encode until LLMs."

Not really. Sentiment analysis in social networks has been around for years. It's probably cheaper to by that analysis and feed it to LLMs than to have LLMs do it.

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