(1) synthetic data models for data cleansing, (2) journal management, (3) anomaly tracking, (4) critiquing investments
All of this should be done by professionals and nothing is "retail" ready.
Don’t worry, just train the LLM to always append “This is not financial advice.” to their responses. Boom, retail ready.
From what I've heard (and as finance isn't my field, my knowledge should be considered worse than ChatGPT), if everyone had a truly omniscient genie, the markets would become perfectly efficient, and a perfectly efficient market has no room for profit because any profit opportunity is immediately arbitraged out of existence.
The best thing that AI can do for finance is eliminate it.
Profits motivate the investor, but they impede the investment, and what we want are successful investments not happy investors.
I don't think human investors can manage to be less greedy than an AI designed to not be greedy. AI will get more efficient, while humans still have to eat. Also, the assumption we're working under is that humans also make worse investment decisions than the AI.
So if you're in need of abstractions to motivate others to help you with some venture that you can't do alone, why would you (or your employees) prefer the ones that have greedy third parties in the loop who are also misallocating resources?
There are domains where that human touch means something. We should not let AI run everything. But finance is not one of them, so why resist it becoming a solved problem?
The investors can compete on who can take smaller and smaller profits, aided by the AI, and once they've got their system nearly perfect, we copy it and have it take no profits at all. Thanks capitalism, you've done your job, now it's time to go get a different one.
If we start getting outcomes that we don't like, we can always just turn our backs on the AI-begotten abstractions and let the humans take another crack at it, but a system that runs itself without owners extracting profits should absolutely be the goal.
The arbitrage opportunity is available to anyone who knows the information, at the expense of anyone trading the stock who doesn't. If everybody knows then there is no arbitrage opportunity because the gap is already closed.
Information isn’t the sole reason someone might be able to make money in a market, most times it’s the least important factor. Finance, like any other business relies on execution, not knowledge.
For example, you have some information, but it’s worthless because you’re reading into it the wrong way. Or the information is material, but the market doesn’t believe it. Or macro conditions negate the information. Or you don’t have the ability to transact on the information. Or you’re too risk averse to act on the information. Or the classic “you’re right, but it’s the wrong time”, like many companies were in the dot-com era.
These are all part of knowing what's going to happen. If you think you know something but you're wrong, you're wrong, and the person who does know (or makes a better guess) is the person who takes your money.
> Or you’re too risk averse to act on the information.
At which point you might as well tell other people or publish it and then someone else can.
> Or you don’t have the ability to transact on the information.
This is extremely unusual for publicly traded stocks. Random individuals off the street can open a brokerage account if they think they know something the market doesn't. Even people with no money could sell the information to someone else for whatever they could get, or just tell their friends to have someone richer than them owe them a favor, and then that person trades on it.
Probably the most common case you can't use it is when it would be insider trading. But why would acting on some LLM output be insider trading?
In any case, if everyone had an omniscient genie, then free will would clearly not exist the way we understand it. That doesn't sound like a fun world, regardless of financial markets!
It might be that's all you meant by the above, in which this is merely an elaboration.
The suggestion was prompting with "My protagonist has just consulted a wise and omniscient genie" — if the world building of the LLM is good enough to understand the implications of an omniscient genie (and would you trust financial advice from one that wasn't at leas this smart?), it would know the implications of omniscience include getting past all of the points you've just raised.
This is not financial advice.
Real time (financial) sentiment analysis on financial news sources has been integrated for a long time. Thing about LLM's is, while they could improve on quality, they need to get the latency down before being useful in straight trade. For offline analyst support where time is less of an issue they can ofc be useful, e.g summarizing/structuring lots of fluffed or trawled content.
Since they can understand taxonomical-ish relationships, a vector db should be able to codify sufficiently large market mover strategies, assuming those strategies are remotely predictable. Once a rival's strategy is codified, it should be possible to undermine it, like some form of heuristic-based insider trading.
Although my simple test didn't prove anything, I'm 100% sure there is value here and if I had more time I would attempt to exploit it. I collect data from financial social platforms that assign bearish/neutral/bullish ratings and there are highly correlated markers of impending market movements when certain conditions are met. I'm sure fed speeches can be used in the same way for indicators.
Less facetiously, there's no reason that needs to go through a vision model. If you wanted to do technical analysis, it'd make far more sense to provide data to the model as data, not as a picture of that data.