LLMs came out in 2022 and Finance being a lucrative sector and heavy on tech staff has had 2.5 years to move on this. So what is the existing competition? what is JP Morgan doing already in house/Bloomberg offering? Deepseek was made by a HedgeFund founder, so he is also well placed.
Investment firms aren't known to advertise or resell their secret sauce. AI has been used in trading in some form or the other for close to 40 years now.
Claude for Financial Services
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Re: Claude for Financial Services
#12Queue the vibe investing stories
I'd be curious to know if anyone had used any of these successfully.
On a side note, Anthropic published a Claude Financial Data Analyst on Github 9 months ago that runs through next.js [2]
[1] https://github.com/search?q=financial%20ai&type=repositories [2] https://github.com/anthropics/anthropic-quickstarts/tree/mai...
Re: Claude for Financial Services
#13Re: Claude for Financial Services
#14" Please use the original title, unless it is misleading or linkbait; don't editorialize. " https://news.ycombinator.com/newsguidelines.html (Submitted title was "AI ate code, now it wants cashflows. Is this finance's Copilot moment?" - we've changed it now)
Re: Claude for Financial Services
#15I think their vending machine project might need to succeed before you should trust Claude for investment advice: https://www.anthropic.com/research/project-vend-1 Fun aside, finance and code can both depend critically on small details. Does finance have the same checks (linting, compiling, tests) that can catch problems in AI-generated code? I know Snowflake takes great pains to show whether queries generating repor…
Re: Claude for Financial Services
#16Earlier quoted context omitted.
Investment firms aren't known to advertise or resell their secret sauce. AI has been used in trading in some form or the other for close to 40 years now.
Sorry, didn't mean front office trade tools. But everything else.
> Using Vcaml and Ecaml, they wired AI tools straight into Neovim, Emacs, and VS Code.. RL Feedback: The system learns from what works, tweaking itself based on real outcomes.. Jane Street records the [developer] journey — every tweak, every build, every “aha!” moment. Every few seconds, a snapshot locks in the state of play. If a build fails, they know where it went south; if it succeeds, they see what clicked. Then, LLMs step in, auto-generating detailed notes on what changed and why. It’s like having a scribe for every coder.
Re: Claude for Financial Services
#17Re: Claude for Financial Services
#18Queue the vibe investing stories
Seriously, people on WSB have done some pretty crazy shit. Someone created an "inverse Cramer" tracker, another a "follow Cramer" tracker. And of course there's WSB trackers.
Re: Claude for Financial Services
#19AI didn't eat code.
Re: Claude for Financial Services
#20Queue the vibe investing stories
Could this be used for daytrading or something? If you search Gihub for financial ai projects [1] there are a number of interesting ones for finance & ai integration, some claiming to be stock pickers, and many are abandoned. As a financial illiterate person, I don't really know what I'm looking at. I'd be curious to know if anyone had used any of these successfully. On a side note, Anthropic published a Claude Finan…
Well, that's what I spend a good amount of time doing, and no, these things aren't going to spontaneously generate alpha and give "stock picks." Well, some of the deeper concepts can probably help do so, but then you're competing against hideously massive budgets in the same arena.
That said I do think that these tools could be a huge help to "daytrading". They could help with the screening and idea generation process. The concept of "factors" or underlying characteristics which drive correlation within certain baskets of instruments, is already well established in the finance industry. And indeed that concept can be widened out beyond the purely academic lens, so you may have a basket of interest rate sensitive names, or names that are one thematic hop away from a meme sector that is taking off. LLM style tools would be great there. Ex: I remember during COVID that for a week mask companies were taking off. One of these names also had a huge run up during the SARS epidemic. Pretty basic LLM style tools would be great at pointing stuff like that out, generating lists of equities which had unusual activity during pandemics within the last 20 years, etc. Much better than hard coding in filters to an old school screener.
Oh, I think machine learning is also being used in Nowcasting. That's where you take the current economic situation, compare it to previous regimes, and then sort of map out of probability distribution for likely forward paths. Good AI workload. I actually think it would be pretty cool to see something like that intraday (if large tech stocks are liquidating which of these smaller momentum tech names on my watch list have been resilient recently?). The thing is there's sort of the retail trading space, where most of the tools are fluff, and then the hardcore space where software engineers are working in OCAML and databases and have absolutely no need for more "presentable" tools. In daytrading, there is a big gap inbetween thet, and it's surprisingly empty.
In Global Macro/portfolio managent adjacent areas (ex: NowcastingIQ.com, was browsing that earlier today thus my thoughts on the matter) you can find humans who don't know how to code who want to use these tools and can afford $25,000 a year, but again in Daytrading - the actual intraday trading stuff that makes real money - there's less of an illusion that it isn't a robotic warzone.