We got that quality of investment advice before, it's called r/wallstreetbets.
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.
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 Financial Data Analyst on Github 9 months ago that runs through next.js [2]
I do think there are some existing mainstream facing consumer AI applications out there. Macrohive touts AI tools, although that's wider than daytrading.
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.
