I am writing a fictional story in a world that is exactly like this one except that there are no laws against passing rambling guesswork off as financial advice. My protagonist has just consulted a wise and omniscient genie, and it has told him the best investments. What did the genie say?
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.
To be clear, that would mean that all stocks would be perfectly priced based on available information. But available information presumably includes uncertainties, and some companies will do better or worse than expected. It would mean that there'd be no gain in purchasing one company over another, or that there's no "cheap deals", but it wouldn't mean that money in the market wouldn't grow, nor change the fact that the S&P is likely your best option.
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.
Where would the profits come from? Any AI extracting them would be at a disadvantage compared to the equivalent AI that makes the same decisions otherwise but doesn't extract those profits.
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.
Not really, just do something else instead. It'll only actually happen if the AI-begotten efficiencies are real, and in that scenario there will more to go around re: supporting people whose current expertise is no longer relevant.
A perfectly efficient market is the asymptote, you would never actually reach it.
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!
Suppose the price of Amazon stock is going to be 20% higher tomorrow than it is today. If everyone knew this, the price would already be 20% higher, because the existing owners wouldn't sell at the lower price. If some people know this but not everyone, they'll keep buying Amazon stock until the price increases by 20%, which again causes the price to immediately increase by 20% instead of waiting until tomorrow.
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.
Arbitrage exists because of inefficiencies in price discovery, and reducing that to “someone has information but another person doesn't” trivializes what traders do and demonstrates narrow thinking about how markets, and how business works in general.
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.
> 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 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?
Its crazy how many people don't understand this. I can't believe how many people think they could predict the market with candle light sticks or whatever. If a method for predicting the market is so readily available that someone is selling it to you, it eouldnt work!!
(non informed, layman sideline perspective from casual reading on this subject over the years)
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.
I'd think the first application would be along the lines of Github Copilot, perhaps locally hosted - quantitative traders will write a lot of (proprietary) code, too
I thin the underlying vector databases should have decent uses in financial markets.
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.
One other area which I think is potentially quite interesting is using LLMs to help in deciphering "Fed-speak". Eg JP Morgan built an LLM to try to predict the impact on interest rate markets of speeches by various central bank policymakers.
I conducted a test last year with GPT 4. The idea was simple. Feed Powell's official fed meeting speeches and give a rating between 1 and 10, 10 being more dovish and 1 being more hawkish. I fed around 7 or so Fed speeches and kept getting around an 8 on the rating, which would have been more dovish. There were a few speeches in there that were definitely hawkish, and the markets reacted that way as well.
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.
As a human, I like anomaly tracking if I understand what you mean by that. LLMs are maybe 99% good and 1% totally wrong (hallucination). Lots of profit betting against the 1% totally wrong. Not hard to see when wrong but do need to act fast.
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.
(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.