11 ms·

TradeExpert, a trading framework that employs Mixture of Expert LLMs

114 points by wertyk 1y ago

ArtTimeInvestor 1y ago
How do people on HN think about the market? Do you think the market is so efficient that anyone who outperforms it is merely lucky? Or do you think the market is inefficient enough for a person smart enough to be able to outperform it by thinking? In other words: Do you think a single person can rationally decide to invest their time into thinking about the stock market? Or would that always be a fallacy, and whatever the outcome is - we can't decide if it was just good or bad luck?
- moritonal 1y ago
  I know that due to being interested in a specific industry, lets say Video Games, I can combine a general understanding of the environment, to a specific understanding of certain companies and the games they're making. If I see in a low-key mailing list that a company is making a new game that I know will line up well with the direction the industry is going, then I can invest in that company and likely be ahead of the market. My hunch is that if you spend more than 6 hours a week studying the mood of a industry, you would likely be "luckier" than the market (although all risks still apply). I also believe a LLM could do exactly what I do with enough investment.
  - miningape 1y ago
    This is exactly how I make money shorting (or buying puts on) companies like Ubisoft and EA. They're pretty much hated by the entire gaming community and their games do not perform well - investors actually believe the stuff they say in press conferences so often the stock prices are over inflated and get corrected about 1 week post launch.
    - iTokio 1y ago
      Be careful, shorts are generally not for retail investors. Shorting is about predicting when a stock will go down. Not that it will go down. Because - there is no limit to how high a stock price can go - the market can stay irrational longer than you can remain solvent
      - gnarlynarwhal42 1y ago
        there are ways to cover yourself, either buy a put (like he mentioned) or if you are short shares then buy a call. both of these have defined risk. also more advanced options strategies would let you adjust where you'd profit and where your risk is in the trade
- Cantinflas 1y ago
  Imo long term efficient, short term could be inefficient enough
  - DougN7 1y ago
    That’s a good way to put it. Short term is dominated by mood/PR/talking heads, etc, but long term seems more about fundamentals. A company not making money can survive and pull a lot of stunts but sooner or later investors want to see profits or they bail. But that “sooner or later” might be 10 years.
  - energy123 1y ago
    A lot of people say crypto bubbles are evidence of inefficiency but just because the moves are craze driven doesn't mean there's a profit opportunity, and it doesn't mean that historical price data can be used to predict future price data. It's common to conflate "market doesn't follow economic fundamentals" with "market inefficiency" but afaik those are two different concepts.
- davedx 1y ago
  “In the short run, the market is a voting machine but in the long run, it is a weighing machine.” Short term movements are very much sentiment driven, both humans and algorithms. Long term movements generally trend towards the consensus of fair value of any given security, which is usually modelled somehow. You can see stocks where the models struggle to reach consensus by their long term volatility.
- flowerthoughts 1y ago
  I believe the markets are assymptotically efficient, but because of constant changes/surprises and the mechanisms being chaotic, it never reaches steady state, and thus is never actually efficient. There might be individual stocks or sectors that do reach steady state between annual reports, but as a whole: no. It's possible there's statistical signal in the inefficiency, comparing predictions to outcomes. At least HFT seems consistently profitable, and whatever Medallion is doing. That said, judging if one specific trader is lucky or good is practically impossible.
- littlestymaar 1y ago
  > Do you think the market is so efficient that anyone who outperforms it is merely lucky? > Or do you think the market is inefficient enough for a person smart enough to be able to outperform it by thinking? The market cannot be “efficient” (though this isn't what “efficient” means in economics besides in EMH), because if it was efficient, then there would be no incentives for market makers, and as such there wouldn't be anyone working to make it efficient. As such, the market is always in an in-between state, inefficient enough so that people spend energy to try beat the average, but still hard to beat because there are already many players out there.
  - ArtTimeInvestor 1y ago
    if it was efficient, then there would be no incentives for market makers, and as such there wouldn't be anyone working to make it efficient. Many market makers work with others people money. So they don't need an inefficient market as an incentive. Market makers also could have a distorted view of the market. Thinking it is inefficient while it is not. So they have an inefficient market as incentive even though it does not exist.
    - littlestymaar 1y ago
      > Many market makers work with others people money. So they don't need an inefficient market as an incentive. Financial institutions pay a lot of people for these tasks, and they are very well paid (and HFT infrastructures cost hundreds of millions), all of that is being paid by their own money, there must be an incentive for them to spend so much money on this. > Market makers also could have a distorted view of the market. Thinking it is inefficient while it is not. So they have an inefficient market as incentive even though it does not exist. This assumes that one of the wealthiest industry on the planet is entirely made out of clueless fools, which is a interesting perspective.
      - ArtTimeInvestor 1y ago
        If you read my post again, you'll see that it was not about the question if institutions can create a positive ROI by doing HFT. It was about the question whether the market is inefficient enough for a person to create a positive ROI by thinking.
- valenterry 1y ago
  "Markets can remain irrational longer than you can remain solvent"
  - solumunus 1y ago
    I would argue irrational markets are easier to make money in.
    - valenterry 1y ago
      Exactly. This is basically confirming that markets are, at least temporarily and sometimes for a very long time, irrational and hence not perfectly efficient.
    - pixl97 1y ago
      It's easy when the market is in the 'the numbers must always go up' phase The hard part is predicting the 'just kidding, they go down' phase.
- grumpymuppet 1y ago
  Sort of both. I believe there are massive polarized forces that invest heavily in understanding and gaming the system. Sort of like a big multi-player game of tug of war . The system must be understandable or people wouldn't incorporate and collaborate on extracting an edge. Slack in the system represents a lower price point, which will be corrected by a corresponding purchase order. An individual has an effect, but it's miniscule compared to the massive forces in play. Unless you have a TRULY novel analysis of a situation, you are going to have a very low probability, success rate and out competing the market.
- benlivengood 1y ago
  There is insufficient information in the market by design as evidenced by the existence of material nonpublic information. Anyone who knows MNPI can make quite a lot of money which is why the SEC exists to regulate how that information can be used in the broader market. To the extent that sufficient intelligence can reverse engineer or infer the private books and planning of public companies and the likely outcomes it can outperform other investors and make the market even more efficient. Modeling global economies is hard; even regional models are hard and a large part why 20th century communism performed poorly compared to open markets (the others being internal corruption and external interference). Therefore I think individual humans have neither the capital reserves (bigger risks can be taken ~safely with more capital) nor the intelligence to beat the current markets. But it's not a zero-sum game and the global economy is still growing so if one's net outcome over several years is negative then it's probably due to bad strategy (e.g. picking stocks by hand, not diversifying) as opposed to bad luck.
- _heimdall 1y ago
  Its hard to find efficiency in markets when company values seem completely unhinged from reality. Historically, companies were valued with a heavy weight put on their financials. That doesn't seem to be the case anymore, and without any clear approximation of how we are valuing companies it feels to me more like pure gambling.
  - rafaelero 1y ago
    Maybe it's your understanding of reality that it's flawed.
    - _heimdall 1y ago
      It certainly is, everyone's understanding of reality is flawed. Show your work here though. I'd point to P/E ratios over time [1]. That's a very common signal used when valuing a company and today those ratios are much higher than historic averages, nearing the ratios we saw before the dotcom bubble burst. [1] https://www.currentmarketvaluation.com/models/price-earnings.php https://www.currentmarketvaluation.com/models/price-earnings...
      - yupitsme123 1y ago
        P/E ratios are probably more useful for comparing companies in the same industry at the same moment in time, rather than as a global rule of thumb. Valuing a company needs to take risk free interest rates and future growth into account, so it's difficult to compare across vastly different companies and time periods.
        fc417fc802 1y ago
        Your response seems to imply that there are broad differences in potential for future growth (among other things) today relative to the dotcom era. Could you elaborate? Alternatively, we could cherry pick a single company. How do you justify tesla's p/e relative to the other car companies? From where I'm standing it doesn't appear to make any sense.
- asah 1y ago
  the markets are provably inefficient: companies shouldn't have their total marketcaps jostle by whole percentage points in a single trading day, when the underlying economics aren't that volatile. but "markets" are (and have always been) "animal spirits" with all but participants leveraging their bets and other players pushing them off the table when they're slightly wrong.
- deleted 1y ago
  [deleted]
- OtherShrezzing 1y ago
  Markets aren't perfectly information-efficient. They're just _very_ information-efficient. So there's at least some room for non-luck-based strategies to outperform the market. More important than information efficiency, is the subjective nature of investments, and the inter-sectoral complexity of the modern economy. There's lots of meaningful calculations you can do to predict the longterm value of a company, but massive and mostly unseen shifts in expectations happen regularly. A fairly small number of people in Feb 2020 saw that 1/3 of students globally were suddenly home-schooled, and connected the dots to turn that into an ultra-strong signal to invest in Moderna. Similarly, lots of people saw that Nvidia's CUDA granted it a near absolute-monopoly over anything that requires matrix multiplication. They were able to connect the dots to turn that into an ultra-strong signal that NVDA would turn from a relatively obscure company into a significant company. Domain specialists have an edge over the aggregate-market within their narrow field of interest.
- mettamage 1y ago
  When Meta did a name change, another stock - Meta Platforms - saw a spike
- jjmarr 1y ago
  The efficient market hypothesis also implies that it's impossible to consistently lose money for a given level of risk. Yet this happens all the time.
- brookst 1y ago
  If there’s volatility it’s not perfectly efficient, because corporate and economic fundamentals don’t change that quickly. But playing volatility is a meta game. It’s about predicting what other players will do.
- Tycho 1y ago
  It’s pretty efficient at assimilating obvious revelations. You have to be quick to trade on the news, and you’re not going to find many arbitrage opportunities. There’s no reason why it would be particularly efficient at pricing long term outcomes. It reflects some sort of consensus or balance of opinions, but those things could simply be wrong. That said, even if you’re right about something, there’s so many factors to account for, it’s not going to be easy to profit. Personally I have most of my savings in retirement tracker funds (global equities), but I’m also building a portfolio of handpicked stocks/bets, aiming for 20, each with the same starting investment. Maybe it won’t be successful but at least it will be fun and minimise the regret of not acting on my insights/convictions. The diversification should stop it from being a disaster.
- nurettin 1y ago
  I hear these all the time: 1. Non-zero sum 2. Market efficiency 3. Everything is priced in 1 only makes sense if you are the market as a whole (you are not), not the one who is making the more informed decisions. 2 is true and actually a good thing for trading. It means there will be less noise vs signals. 3 doesn't matter if you are the market maker or you know the patterns caused by the "pricing in" and react to them.
- _Algernon_ 1y ago
  IMO efficient market hypothesis is not true (assuming you have all available information you could beat it), but for an ordinary person there are so many ways the market is stacked against them that they should still just assume that it is true. The question isn't "is it possible to outperform the market by thinking?", it is "will whatever advantage I can get by thinking weigh up for all the disadvantages I have from not being able to insider trade, being further from the exchange than other market participants, having lower ability to sustain losses than big market players, trading fees, taxes, opportunity cost, etc.?" For any single individual, the answer to the second question is almost certainly no (unless you happen to sit in congress).
- high_na_euv 1y ago
  If you have industry knowledge then you can outperform market short term
  - infecto 1y ago
    Disagree unless we are talking about insider information. There are lots of experts with industry knowledge and most are not able to monetize that.
    - luma 1y ago
      Insider information is the only durable advantage in the market. Any time you see a long running and consistently successful fund report, keep this fact in mind.
    - high_na_euv 1y ago
      I said you can, not you will Understanding industry allows you to not get baited by rumors, articles, dramas, bullshit comments on reddit hn etc
      - infecto 1y ago
        And I said I disagree. Having knowledge of an industry is not that valuable. It’s the bare minimum before making an investment and therefore is a very known datapoint.
        high_na_euv 1y ago
        >It’s the bare minimum before making an investment Such a naivety. Try visiting r/Wallstreetbets and you'll see that people often don't have any meaningful industry understanding
        infecto 1y ago
        Are you referring to yourself? Keyword I said was investment. Most of the folks on those types of forums are simply gamblers or wishful thinkers. Again my only point before you took it to this level was that industry knowledge is not an edge it’s table stakes when making an investment in the public markets. Having that experience or knowledge is not niche or unique and something that can be purchased with a handful of expert interviews.
- TeMPOraL 1y ago
  N=1, I think that: - You'd have to be either extremely lucky, or spend a lot of money and effort (e.g. to get to the bleeding edge of quant or HFI game), to be in a position where you could use your knowledge and brainpower directly to give yourself an edge over the market, and: - Any such edge is extremely short-lived - the moment you take advantage of it, the market itself will start adjusting to correct, and on top of that, other smart players will notice the irregularity, work to exploit it or reverse engineer your approach; in the end, the "pattern" quickly disappears. Whether one can become able to continuously find such short-lived edges and profit off them, by means other than pure random chance, I don't know, but I highly doubt it. The space is way too competitive; a sustained miracle advantage would eventually attract regulatory attention, and/or unscrupulous parties willing to lie and cheat to bury you legally, or literally. But that's just me speculating.
  - jamespattn 1y ago
    If the "edge" is ephemeral (I agree that it is), I always wonder how quant/HFT firms like Jane Street, RenTech continuously make insane profits out of such strategies. I suppose it could be a combination of things that isn't necessarily just related to finding edge over markets. Having an entrenched market position or access to data faster perhaps?
    - mtillman 1y ago
      Rentech is an old customer of mine, do you know if they’ve still not had a down year on the employee fund?
    - cmcaleer 1y ago
      Not all edge is necessarily ephemeral, if you're thoroughly entrenched and have a deep understanding of a market you will usually just outperform your competitors. Take Jane Street's infamously long-lasting (and profitable!) Indian options trade for example. They had clearly put in the work and effort into understanding a market that other firms didn't do to the same extent, and resources and minds who are good at figuring this stuff out are finite. You're totally right that edge isn't just knowing if number is more likely to go up, as an example since you mentioned faster access to data: some of the best of the best companies will hire meteorologists so that they know how reliable their microwave towers for transmitting data between e.g. Chicago and NY are (and they can lean in or widen their spreads according to how current and up-to-date their information is). It sounds like crazy stuff to do, but when your data could be up to 10ms slower than you expect due to weather and you're so sensitive to latency you hire FPGA engineers because normal high performance CPUs aren't enough for you, it's not that crazy. I sometimes feel like HFT is a waste of good talent and wonder what some of the people I've met who work at JS or CitSec could have done in other industries, but at the same time HFT is often the only industry that correctly prices these peoples' minds. Ultimately having a smoother financial system where risk is more correctly priced is a good thing, even if it's not the best thing they could be doing.
- mtillman 1y ago
  I spent 6 years in algo trading. I think that the market is a thing people call the US stock market and it’s 98% machine traded volume. Whenever I hear people talking about their alpha on an equity I assume it’s either insider trading or ignorance of the billions in PhDs, super computing, and dark fiber they’re up against.
  - Fade_Dance 1y ago
    There is alpha in markets. I did a lot of relatively unsophisticated SPAC relative value warrant trading during the 2020 period, and I think a big part of it is the question of scale and slippage. If you're a prop firm that makes "real money" your universe is limited by these constraints. IE "not worth the time" would be a common response to trading opportunities. For example, there were high sophistication players in the merger/stat arb phase of the game, and they would layer out their warrants like an onion of dark liquidity (the orders were hidden/not directly listed on ARCA/etc). They were involved in just about every SPAC name out there. But when an SEC filing came out, or you learned some specifics about a certain sponsor team (maybe they have very high quality lockup partners who don't dump shares on lockup date, as shown by their last 3 SPACs), then maybe that implies a higher warrant valuation, or maybe that should be priced into the option chain. And they will happily sell to those pricing in that "hair" and sell their inventory because they don't want to deal with some 5 dollar warrant that trades 50,000 volume per day. The profitable futures traders I know are also more or less just riding off the back of the machine volume and participating when machine trading from option flow is moving/pinning markets. They are of course just exacerbating the situation, which is partly why we see this increasingly bifurcated market where robots/options are entirely into control, interspersed with violent price discovery/mini vol events.
- hattmall 1y ago
  With time and focus any person can beat the market. The market is wildly irrational, so rational actions are not the deciding factor. It is being able to spend all your time and focus watching the data. The question is whether this can be reliably outsourced to machines and what level of effort will it take. A very simple exercise is to go and watch the live data for a single stock for 1 hour. You will see that it moves up and down and has trends. After 1 hour you can have an idea of an entry point, pretend to pick one, continue to watch, the odds are much greater than 50% that at some point the stock will go above your entry point in the next hour. It only doesn't if you bought into the top of a solid downward trend. And that is the very basic example, but pair that with an understanding of options and a hedge strategy for the unlikely chance that you bought in at the top of a solid downward trend. The last piece is to watch and understand Level II data and I reliably believe anyone can "beat" the market. The issue is that you literally have to monitor it consistently with a clear focus, can you do that with more than one security? What portion can we reliably have machines do without some risk that the machine makes a tremendous error and blows up the account?
- PaulRobinson 1y ago
  I spend far too much time thinking about and building code for trading on betting exchanges, which isn't quite the same, but there are parallels. Most experts agree that the hard definition of efficient markets (that all information is baked into a price immediately), doesn't hold, but the soft definition (that the price will veer towards true value), does hold. The big question is how quickly does it get there? That means there is potential to make money (if it takes n minutes, and you are able to trade at n/2, and exit at n, you're going to make money). Insider traders can make the most money, but there is also money to be made on much longer trends too, I think. Most of the super smart people throwing money at algos and hardware are specialising in HFT to try and trade at very high speed. They are typically not looking at much longer trends. That means there is perhaps more exploitable value for the individual in longer trend spotting compared to shorter term trends. (Note, I don't mean technical analysis when I talk about trends.) Would I recommend you get into market making and HFT? Not without an eight figure sum to get started. Would I recommend you get into value investing and looking at the long-term? Sure, just remember that diversification is good for a reason, and you might struggle to beat an index - most professionals do. If you enjoy it though, you might find it a good way to make your retirement savings grow, perhaps even a living. Would I recommend you get into day trading? Probably not, but that doesn't mean there aren't successful day traders sat at home making a living trading on margin. It's hard work, and if you're smart enough to make it pay, you're probably smart enough to make more money doing something more productive for society instead. I also don't think most people are smart enough to make money (important note [1]), if they try and work out by "thinking". Don't try and move from first principles. Learn from successful people, who aren't full of BS. The vast majority of people on YouTube and selling books are not successful. There are real success stories out there, you need to filter a lot to find them, but they exist. Use them. [1] Your question was if people can "outperform" the market. You don't need to outperform the market, you don't need to be optimal, you "just" need to make enough money to meet your goals, and preferably more than you would get just from leaving your money in an index tracker. That's not the same thing. If you're trying to perfectly enter/exit trades and "beat the market", you're dead before you get started.
- mring33621 1y ago
  I have done, using my own real money, algorithmic swing and day trading for many years. There are patterns that can be found and exploited, in the short term. However, I was unable to predict changes in the trading environment. My software did not even try to watch the news. So when big macro events happen, like a civil war in Syria, for example, the patterns can change overnight, so I sometimes was left holding a heavy bag.
- immibis 1y ago
  80% of it is the world's largest and longest-running Ponzi scheme. Because it's a Ponzi scheme, it brings negative expected value (maybe the other 20% cancels it out, maybe not). But because it's the world's largest and longest-running, you'd better participate because the chance it collapses at the exact moment you didn't invest but everyone else did is pretty low, and you can't let them outcompete you in the short term. You have a significant chance of not being the bottom tier of the Ponzi, unfortunately. If you do invest and it does crash, you're no worse off than everyone else. That's for general market trends. Individual stocks also make no sense. You could buy and hold some very stable company's stock but you're making a relative pittance compared to just, like, changing jobs or something. Expected compound interest is not high enough to justify the risk of a catastrophic crash; also if you think a crash will happen any time in the next forever, you're better off holding cash or low-risk bonds until after the crash and jumping in then, as that will more than make up for the compound interest you make up on. In the past, compound interest has been significantly higher than expected, and very much worth it, but only due to survivorship bias. There are many reasons to think the next 60 years won't be anything like the last 60.
  - Fade_Dance 1y ago
    >Expected compound interest is not high enough to justify the risk of a catastrophic crash That's just not the case. It may be a lower yield world, but you can still find companies with relatively stable and growing 10-15% cashflow to EV ratio even in the US. Outside of the US old-school "easy" Value is still very much alive as well. What you were advocating for is market timing, and market timing demonstrably does not add alpha unless it's done very mindfully, mostly because the opportunity cost of sitting out is great. If you look at core alpha sources through a factor lens like trend following, most of the profit comes from participating in the big trends (read, most of the easy returns come from "expensive" getting "more expensive/"overbought"). From another lens that takes into account fragility/crashes - vol trading - selling vol is paradoxically highest sharpe when vol is low and most vulnerable to severe disruption. Part of what you're disregarding is how market participants are far more sophisticated today than they were even 20 years ago. If you're building a 60/40, it doesn't look attractive, but even accounting for survivorship bias, the baseline has risen. The "crash case" remains relatively similar when it comes to portfolio planning - you need to prepare for 60% crashes, and 10-year "lost decades." The tools to manage that equity risk and still access smooth returns are far more powerful and accessible than they were in the past though.
- NotAnOtter 1y ago
  I stick with the dog walker analogy. A man walks down the street at a steady pace, and the dog on the leash runs back and forth and side ways and sits and jumps. The man is the economy, the dog is the market. Unless you have access to HFT systems & models, there is no point in trying to guess where the dog will go. You have to look at the man, which is the aggregate health of the economy. If I start to see the man walk backwards, I sell, and vis versa. But *mostly*, I just stick things in ETF's and don't worry about it unless I need the money in the near future.
AIorNot 1y ago
So did it make any money?
- kinnth 1y ago
  It doesn't look like it. There isn't a clear comparison to a "human trader".
- jsheard 1y ago
  If it did, I think it's safe to assume they would have sold it to a quant firm and we never would have heard about it.
  - TechDebtDevin 1y ago
    This. It is a gimmick.
- IronyMan100 1y ago
  one drawback here is the backtesting. They backtesting only 1 year in 2023.
flowerthoughts 1y ago
> Alpha Factors incorporates 108 technical indicators and factors with their expressions, which are believed to possess predictive power regarding stock price movements. Examples of the indicators are in Figure 15. The ablation studies in Table 4 suggest that market and news information made a much bigger impact than the magic indicators. Makes sense if the indicators are simple enough that the LLM can reproduce them without losing processing power. I somewhat like that they used DJI and not SPX, but 2023 was a sideways bull year with DJI +12% and SPX +23%. One year is way too short of a study. > Hardware: NVIDIA A5000 GPU x 4, AMD Ryzen Threadripper PRO 3975WX CPU, 256 GB RAM Seems approachable. > The proposed TradExpert framework utilizes a Mixture of Experts (MoE) approach, where four LLMs are specialized in processing distinct sources of financial data. All these LLMs are based on the LLaMA-2-7B Touvron et al. (2023b) model and fine-tuned using the LoRA mechanism Hu et al. (2022) Relatively small LLM. Overall, this does seem like an interesting study, even for just comparing data sources.
- blitzar 1y ago
  > 7B, Relatively small LLM. Possibly too large a model. (Daily) finance data is finite - 7B parameters is potentially order(s) of magnitude more than the training data.
  - flowerthoughts 1y ago
    Yes, but these are LLMs where the point is they understand English prompts and information. They aren't just fed market data.
niemandhier 1y ago
If I understand this correctly we have come full circle on what MoE means. MoE started out as some form of multi model approach. Afaik in current architectures it’s basically a load balancing method that while it increases latency makes the model better suitable for distributed operations. To me this reads as if the author uses the term closer to Urs original meaning than its current.
mzhaase 1y ago
I want to coin a new law: if a news title has "revolutionizing" in the title, its bullshit.
- thomassmith65 1y ago
  The phrase "changing the [something] game" is the most obnoxious.
amelius 1y ago
I'm curious at what point stock and derivatives trading becomes something entirely for AI, and thus restricted to companies rich enough to buy tons of GPUs. Are we near that point yet?
- TechDebtDevin 1y ago
  We've been past that point for more than a decade. This is a gimmick.
  - amelius 1y ago
    Then why are there still brokerage firms targeting small people?
mkoryak 1y ago
Do is it "tradExpert" or "tradeExpert" ? Shortening variable names from words by a vowel or two is a hge pt peev.
infecto 1y ago
Not a very good study. I did not look at any of the researchers background but it’s like they did not consult their respective finance school departments.
csantini 1y ago
The market is like an ecosystem. There are huge mammals (investment banks, hedge funds) that look at certain type of preys, and there are smaller rodents that only eat very tiny worms. In high volatility regimes, ie. stocks with low market cap, the market is far from efficient. Hedge funds are not even looking at stocks with 100M market cap. There are traders that act in these regimes that beat the market, exactly because they play small. Anyhow most people would be better of by assuming the market is completely efficient.
thunder-blue-3 1y ago
fwiw, I tried something similar about 5–10 years ago. I wasn’t using LLMs like the abstract here suggests, and honestly, I’m not sure how you'd act on a signal fast enough with them. When I gave it a shot, there was some slight predictive value, but in the end it felt like noise and gambling, so I moved on.
bguberfain 1y ago
So they used a LLM with knowledge cut in mid 2023 to evaluate 2023? Seems like a classic leakage problem. From paper: "testing set: January 1, 2023, to December 31, 2023" From the Llama 2 doc: "(...) some tuning data is more recent, up to July 2023."
- mhmmmmmm 1y ago
  Removing the "Market expert" which uses OHLCV (Open, High, Low, Close, Volume) also drops the sharpee from 5.01 to 1.88 while also increasing the max draw down to 13.29% (v.s. 9.70% for the index). I'd be very surprised if the pre training of the base model was the only source of leakage...
languagehacker 1y ago
How did it perform against a boglehead portfolio? Were fees and commissions included? Seems weird to evaluate performance over a single year for trades. Much more interested in long-term growth over one or more market cycles.
- Fade_Dance 1y ago
  I think if you're talking on portfolio level a lot of these things are used as signals and parts of a greater whole. In that sense, they can indeed add value. My current project is a modern version of a classic Harry Browne portfolio with even asset allocations to gold/bonds/equity/commodities, with optional layers of sophistication according to spec needs. Something like systematic macro could be analyzed as a standalone return stream, but it's more useful when considered as an input into allocation/leverage adjustments (ex: if geopolitical uncertainty readings are high, cut down the trend following exposure). Even the more robot/quant stuff like vol trading feeds back into the wider portfolio management and portfolio construction level to some degree.
ta12653421 1y ago
Good one, happy to add my perspective here: DISCLAIMER: I've spent the last 8 month heavily on building a quant-based asset management app (though, still not live, currently in final steps to sync processes with broker) a) I tried to leverage some of this AI-voodoo stuff, though not on the level as in the paper; my findings are clear (at least for me): AI-driven trading does not give you a bigger/better edge than any of the other well-known approaches b) In fact, AI-based approaches are at best on par with traditional approaches, in lot of scenarios not even this; I havent seen any setup from anyone which actually outperformed one of the classic approaches. BUT: The AI-guys have much higher cost, be it Infra, processing time / waiting time in front of screen etc. So you have you to pick carefully, which one you choose. c) I'm doing today only "standard approaches" with volume/statistics/vola/price action, as this approach is super-cost-efficient (i need only one cheap datastream) and a lightweight machine for 10 / 20 USD a month d) It is clearly possible to outperform the market, though these approaches are not scalable unlimited - Ex: depending on the used instruments, there may not be enough liquidity to buy continuously for 100k, but maybe for 10k only. Apply leverage of 5-10 on an asset that moved 5% in last 10 days on a 10k position - is this outperforming? A clear >yes< in my perception? e) People who have built & found a stable approach do not share it or talk about it, there is no real community; you will get details of working approaches only from people whom you are really "friend with"; there is a lot of unshared but working business tactics in the field.
- r0b05 1y ago
  Are you referring to LLM's when you mention AI here?
  - ta12653421 1y ago
    Thanks for the question: Not really in the field of trading, rather prediction-based approaches etc.; Im not sure if LLM could be of any use here? The approaches based on statistical arbitrage are purely math/number models. from my own experience, LLM are absolutely useless when it comes to "trading ideas" (I use them for code generation, instead), this is because they are dicing together values in their output which are not really related, because of their hallucis. Also, for fundamental analysis they are too often incorrect - so running an auto-approach based on LLM-fundamental output would be an "interesting" idea :))
reedf1 1y ago
Did they release the code or the model itself?
16th_hop 1y ago
Does anyone understand how the Market Expert works? It takes in numerical OHLC data and converts it to embeddings for use by the LLM… but embedding are also numbers so I don’t see how that’s any easier for the LLM to process since it’s a language model. > The Market Analyst LLM focuses on analyzing historical OHLCV (Open, High, Low, Close, Vol- ume) data to predict stock movements. However, time series data is inherently continuous and lacks the discrete token structure that LLMs are designed to process. This misalignment poses a signifi- cant challenge in effectively utilizing LLMs on time series. To this end, we utilize a reprogramming mechanism Jin et al. (2024) to reprogram the input financial time series into text prototype repre- sentations.
immibis 1y ago
[flagged]
thedudeabides5 1y ago
lol 5 sharpe classic 'tell me you overfit without telling me' tell
mhh__ 1y ago
A sharpe of 5 is ludicrously good for a long only equities strategy
bGl2YW5j 1y ago
I feel like applying MoE to LLMs is a just a brute-force prediction approach that's neither efficient or very accurate.

114 points by wertyk 1y ago

How do people on HN think about the market? Do you think the market is so efficient that anyone who outperforms it is merely lucky? Or do you think the market is inefficient enough for a person smart enough to be able to outperform it by thinking? In other words: Do you think a single person can rationally decide to invest their time into thinking about the stock market? Or would that always be a fallacy, and whatever the outcome is - we can't decide if it was just good or bad luck?

moritonal 1y ago
I know that due to being interested in a specific industry, lets say Video Games, I can combine a general understanding of the environment, to a specific understanding of certain companies and the games they're making. If I see in a low-key mailing list that a company is making a new game that I know will line up well with the direction the industry is going, then I can invest in that company and likely be ahead of the market. My hunch is that if you spend more than 6 hours a week studying the mood of a industry, you would likely be "luckier" than the market (although all risks still apply). I also believe a LLM could do exactly what I do with enough investment.
- miningape 1y ago
  This is exactly how I make money shorting (or buying puts on) companies like Ubisoft and EA. They're pretty much hated by the entire gaming community and their games do not perform well - investors actually believe the stuff they say in press conferences so often the stock prices are over inflated and get corrected about 1 week post launch.
  - iTokio 1y ago
    Be careful, shorts are generally not for retail investors. Shorting is about predicting when a stock will go down. Not that it will go down. Because - there is no limit to how high a stock price can go - the market can stay irrational longer than you can remain solvent
    - gnarlynarwhal42 1y ago
      there are ways to cover yourself, either buy a put (like he mentioned) or if you are short shares then buy a call. both of these have defined risk. also more advanced options strategies would let you adjust where you'd profit and where your risk is in the trade
Cantinflas 1y ago
Imo long term efficient, short term could be inefficient enough
- DougN7 1y ago
  That’s a good way to put it. Short term is dominated by mood/PR/talking heads, etc, but long term seems more about fundamentals. A company not making money can survive and pull a lot of stunts but sooner or later investors want to see profits or they bail. But that “sooner or later” might be 10 years.
- energy123 1y ago
  A lot of people say crypto bubbles are evidence of inefficiency but just because the moves are craze driven doesn't mean there's a profit opportunity, and it doesn't mean that historical price data can be used to predict future price data. It's common to conflate "market doesn't follow economic fundamentals" with "market inefficiency" but afaik those are two different concepts.
davedx 1y ago
“In the short run, the market is a voting machine but in the long run, it is a weighing machine.” Short term movements are very much sentiment driven, both humans and algorithms. Long term movements generally trend towards the consensus of fair value of any given security, which is usually modelled somehow. You can see stocks where the models struggle to reach consensus by their long term volatility.
flowerthoughts 1y ago
I believe the markets are assymptotically efficient, but because of constant changes/surprises and the mechanisms being chaotic, it never reaches steady state, and thus is never actually efficient. There might be individual stocks or sectors that do reach steady state between annual reports, but as a whole: no. It's possible there's statistical signal in the inefficiency, comparing predictions to outcomes. At least HFT seems consistently profitable, and whatever Medallion is doing. That said, judging if one specific trader is lucky or good is practically impossible.
littlestymaar 1y ago
> Do you think the market is so efficient that anyone who outperforms it is merely lucky? > Or do you think the market is inefficient enough for a person smart enough to be able to outperform it by thinking? The market cannot be “efficient” (though this isn't what “efficient” means in economics besides in EMH), because if it was efficient, then there would be no incentives for market makers, and as such there wouldn't be anyone working to make it efficient. As such, the market is always in an in-between state, inefficient enough so that people spend energy to try beat the average, but still hard to beat because there are already many players out there.
- ArtTimeInvestor 1y ago
  if it was efficient, then there would be no incentives for market makers, and as such there wouldn't be anyone working to make it efficient. Many market makers work with others people money. So they don't need an inefficient market as an incentive. Market makers also could have a distorted view of the market. Thinking it is inefficient while it is not. So they have an inefficient market as incentive even though it does not exist.
  - littlestymaar 1y ago
    > Many market makers work with others people money. So they don't need an inefficient market as an incentive. Financial institutions pay a lot of people for these tasks, and they are very well paid (and HFT infrastructures cost hundreds of millions), all of that is being paid by their own money, there must be an incentive for them to spend so much money on this. > Market makers also could have a distorted view of the market. Thinking it is inefficient while it is not. So they have an inefficient market as incentive even though it does not exist. This assumes that one of the wealthiest industry on the planet is entirely made out of clueless fools, which is a interesting perspective.
    - ArtTimeInvestor 1y ago
      If you read my post again, you'll see that it was not about the question if institutions can create a positive ROI by doing HFT. It was about the question whether the market is inefficient enough for a person to create a positive ROI by thinking.
valenterry 1y ago
"Markets can remain irrational longer than you can remain solvent"
- solumunus 1y ago
  I would argue irrational markets are easier to make money in.
  - valenterry 1y ago
    Exactly. This is basically confirming that markets are, at least temporarily and sometimes for a very long time, irrational and hence not perfectly efficient.
  - pixl97 1y ago
    It's easy when the market is in the 'the numbers must always go up' phase The hard part is predicting the 'just kidding, they go down' phase.
grumpymuppet 1y ago
Sort of both. I believe there are massive polarized forces that invest heavily in understanding and gaming the system. Sort of like a big multi-player game of tug of war . The system must be understandable or people wouldn't incorporate and collaborate on extracting an edge. Slack in the system represents a lower price point, which will be corrected by a corresponding purchase order. An individual has an effect, but it's miniscule compared to the massive forces in play. Unless you have a TRULY novel analysis of a situation, you are going to have a very low probability, success rate and out competing the market.
benlivengood 1y ago
There is insufficient information in the market by design as evidenced by the existence of material nonpublic information. Anyone who knows MNPI can make quite a lot of money which is why the SEC exists to regulate how that information can be used in the broader market. To the extent that sufficient intelligence can reverse engineer or infer the private books and planning of public companies and the likely outcomes it can outperform other investors and make the market even more efficient. Modeling global economies is hard; even regional models are hard and a large part why 20th century communism performed poorly compared to open markets (the others being internal corruption and external interference). Therefore I think individual humans have neither the capital reserves (bigger risks can be taken ~safely with more capital) nor the intelligence to beat the current markets. But it's not a zero-sum game and the global economy is still growing so if one's net outcome over several years is negative then it's probably due to bad strategy (e.g. picking stocks by hand, not diversifying) as opposed to bad luck.
_heimdall 1y ago
Its hard to find efficiency in markets when company values seem completely unhinged from reality. Historically, companies were valued with a heavy weight put on their financials. That doesn't seem to be the case anymore, and without any clear approximation of how we are valuing companies it feels to me more like pure gambling.
- rafaelero 1y ago
  Maybe it's your understanding of reality that it's flawed.
  - _heimdall 1y ago
    It certainly is, everyone's understanding of reality is flawed. Show your work here though. I'd point to P/E ratios over time [1]. That's a very common signal used when valuing a company and today those ratios are much higher than historic averages, nearing the ratios we saw before the dotcom bubble burst. [1] https://www.currentmarketvaluation.com/models/price-earnings.php https://www.currentmarketvaluation.com/models/price-earnings...
    - yupitsme123 1y ago
      P/E ratios are probably more useful for comparing companies in the same industry at the same moment in time, rather than as a global rule of thumb. Valuing a company needs to take risk free interest rates and future growth into account, so it's difficult to compare across vastly different companies and time periods.
      - fc417fc802 1y ago
        Your response seems to imply that there are broad differences in potential for future growth (among other things) today relative to the dotcom era. Could you elaborate? Alternatively, we could cherry pick a single company. How do you justify tesla's p/e relative to the other car companies? From where I'm standing it doesn't appear to make any sense.
asah 1y ago
the markets are provably inefficient: companies shouldn't have their total marketcaps jostle by whole percentage points in a single trading day, when the underlying economics aren't that volatile. but "markets" are (and have always been) "animal spirits" with all but participants leveraging their bets and other players pushing them off the table when they're slightly wrong.
deleted 1y ago
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OtherShrezzing 1y ago
Markets aren't perfectly information-efficient. They're just _very_ information-efficient. So there's at least some room for non-luck-based strategies to outperform the market. More important than information efficiency, is the subjective nature of investments, and the inter-sectoral complexity of the modern economy. There's lots of meaningful calculations you can do to predict the longterm value of a company, but massive and mostly unseen shifts in expectations happen regularly. A fairly small number of people in Feb 2020 saw that 1/3 of students globally were suddenly home-schooled, and connected the dots to turn that into an ultra-strong signal to invest in Moderna. Similarly, lots of people saw that Nvidia's CUDA granted it a near absolute-monopoly over anything that requires matrix multiplication. They were able to connect the dots to turn that into an ultra-strong signal that NVDA would turn from a relatively obscure company into a significant company. Domain specialists have an edge over the aggregate-market within their narrow field of interest.
mettamage 1y ago
When Meta did a name change, another stock - Meta Platforms - saw a spike
jjmarr 1y ago
The efficient market hypothesis also implies that it's impossible to consistently lose money for a given level of risk. Yet this happens all the time.
brookst 1y ago
If there’s volatility it’s not perfectly efficient, because corporate and economic fundamentals don’t change that quickly. But playing volatility is a meta game. It’s about predicting what other players will do.
Tycho 1y ago
It’s pretty efficient at assimilating obvious revelations. You have to be quick to trade on the news, and you’re not going to find many arbitrage opportunities. There’s no reason why it would be particularly efficient at pricing long term outcomes. It reflects some sort of consensus or balance of opinions, but those things could simply be wrong. That said, even if you’re right about something, there’s so many factors to account for, it’s not going to be easy to profit. Personally I have most of my savings in retirement tracker funds (global equities), but I’m also building a portfolio of handpicked stocks/bets, aiming for 20, each with the same starting investment. Maybe it won’t be successful but at least it will be fun and minimise the regret of not acting on my insights/convictions. The diversification should stop it from being a disaster.
nurettin 1y ago
I hear these all the time: 1. Non-zero sum 2. Market efficiency 3. Everything is priced in 1 only makes sense if you are the market as a whole (you are not), not the one who is making the more informed decisions. 2 is true and actually a good thing for trading. It means there will be less noise vs signals. 3 doesn't matter if you are the market maker or you know the patterns caused by the "pricing in" and react to them.
_Algernon_ 1y ago
IMO efficient market hypothesis is not true (assuming you have all available information you could beat it), but for an ordinary person there are so many ways the market is stacked against them that they should still just assume that it is true. The question isn't "is it possible to outperform the market by thinking?", it is "will whatever advantage I can get by thinking weigh up for all the disadvantages I have from not being able to insider trade, being further from the exchange than other market participants, having lower ability to sustain losses than big market players, trading fees, taxes, opportunity cost, etc.?" For any single individual, the answer to the second question is almost certainly no (unless you happen to sit in congress).
high_na_euv 1y ago
If you have industry knowledge then you can outperform market short term
- infecto 1y ago
  Disagree unless we are talking about insider information. There are lots of experts with industry knowledge and most are not able to monetize that.
  - luma 1y ago
    Insider information is the only durable advantage in the market. Any time you see a long running and consistently successful fund report, keep this fact in mind.
  - high_na_euv 1y ago
    I said you can, not you will Understanding industry allows you to not get baited by rumors, articles, dramas, bullshit comments on reddit hn etc
    - infecto 1y ago
      And I said I disagree. Having knowledge of an industry is not that valuable. It’s the bare minimum before making an investment and therefore is a very known datapoint.
      - high_na_euv 1y ago
        >It’s the bare minimum before making an investment Such a naivety. Try visiting r/Wallstreetbets and you'll see that people often don't have any meaningful industry understanding
        infecto 1y ago
        Are you referring to yourself? Keyword I said was investment. Most of the folks on those types of forums are simply gamblers or wishful thinkers. Again my only point before you took it to this level was that industry knowledge is not an edge it’s table stakes when making an investment in the public markets. Having that experience or knowledge is not niche or unique and something that can be purchased with a handful of expert interviews.
TeMPOraL 1y ago
N=1, I think that: - You'd have to be either extremely lucky, or spend a lot of money and effort (e.g. to get to the bleeding edge of quant or HFI game), to be in a position where you could use your knowledge and brainpower directly to give yourself an edge over the market, and: - Any such edge is extremely short-lived - the moment you take advantage of it, the market itself will start adjusting to correct, and on top of that, other smart players will notice the irregularity, work to exploit it or reverse engineer your approach; in the end, the "pattern" quickly disappears. Whether one can become able to continuously find such short-lived edges and profit off them, by means other than pure random chance, I don't know, but I highly doubt it. The space is way too competitive; a sustained miracle advantage would eventually attract regulatory attention, and/or unscrupulous parties willing to lie and cheat to bury you legally, or literally. But that's just me speculating.
- jamespattn 1y ago
  If the "edge" is ephemeral (I agree that it is), I always wonder how quant/HFT firms like Jane Street, RenTech continuously make insane profits out of such strategies. I suppose it could be a combination of things that isn't necessarily just related to finding edge over markets. Having an entrenched market position or access to data faster perhaps?
  - mtillman 1y ago
    Rentech is an old customer of mine, do you know if they’ve still not had a down year on the employee fund?
  - cmcaleer 1y ago
    Not all edge is necessarily ephemeral, if you're thoroughly entrenched and have a deep understanding of a market you will usually just outperform your competitors. Take Jane Street's infamously long-lasting (and profitable!) Indian options trade for example. They had clearly put in the work and effort into understanding a market that other firms didn't do to the same extent, and resources and minds who are good at figuring this stuff out are finite. You're totally right that edge isn't just knowing if number is more likely to go up, as an example since you mentioned faster access to data: some of the best of the best companies will hire meteorologists so that they know how reliable their microwave towers for transmitting data between e.g. Chicago and NY are (and they can lean in or widen their spreads according to how current and up-to-date their information is). It sounds like crazy stuff to do, but when your data could be up to 10ms slower than you expect due to weather and you're so sensitive to latency you hire FPGA engineers because normal high performance CPUs aren't enough for you, it's not that crazy. I sometimes feel like HFT is a waste of good talent and wonder what some of the people I've met who work at JS or CitSec could have done in other industries, but at the same time HFT is often the only industry that correctly prices these peoples' minds. Ultimately having a smoother financial system where risk is more correctly priced is a good thing, even if it's not the best thing they could be doing.
mtillman 1y ago
I spent 6 years in algo trading. I think that the market is a thing people call the US stock market and it’s 98% machine traded volume. Whenever I hear people talking about their alpha on an equity I assume it’s either insider trading or ignorance of the billions in PhDs, super computing, and dark fiber they’re up against.
- Fade_Dance 1y ago
  There is alpha in markets. I did a lot of relatively unsophisticated SPAC relative value warrant trading during the 2020 period, and I think a big part of it is the question of scale and slippage. If you're a prop firm that makes "real money" your universe is limited by these constraints. IE "not worth the time" would be a common response to trading opportunities. For example, there were high sophistication players in the merger/stat arb phase of the game, and they would layer out their warrants like an onion of dark liquidity (the orders were hidden/not directly listed on ARCA/etc). They were involved in just about every SPAC name out there. But when an SEC filing came out, or you learned some specifics about a certain sponsor team (maybe they have very high quality lockup partners who don't dump shares on lockup date, as shown by their last 3 SPACs), then maybe that implies a higher warrant valuation, or maybe that should be priced into the option chain. And they will happily sell to those pricing in that "hair" and sell their inventory because they don't want to deal with some 5 dollar warrant that trades 50,000 volume per day. The profitable futures traders I know are also more or less just riding off the back of the machine volume and participating when machine trading from option flow is moving/pinning markets. They are of course just exacerbating the situation, which is partly why we see this increasingly bifurcated market where robots/options are entirely into control, interspersed with violent price discovery/mini vol events.
hattmall 1y ago
With time and focus any person can beat the market. The market is wildly irrational, so rational actions are not the deciding factor. It is being able to spend all your time and focus watching the data. The question is whether this can be reliably outsourced to machines and what level of effort will it take. A very simple exercise is to go and watch the live data for a single stock for 1 hour. You will see that it moves up and down and has trends. After 1 hour you can have an idea of an entry point, pretend to pick one, continue to watch, the odds are much greater than 50% that at some point the stock will go above your entry point in the next hour. It only doesn't if you bought into the top of a solid downward trend. And that is the very basic example, but pair that with an understanding of options and a hedge strategy for the unlikely chance that you bought in at the top of a solid downward trend. The last piece is to watch and understand Level II data and I reliably believe anyone can "beat" the market. The issue is that you literally have to monitor it consistently with a clear focus, can you do that with more than one security? What portion can we reliably have machines do without some risk that the machine makes a tremendous error and blows up the account?
PaulRobinson 1y ago
I spend far too much time thinking about and building code for trading on betting exchanges, which isn't quite the same, but there are parallels. Most experts agree that the hard definition of efficient markets (that all information is baked into a price immediately), doesn't hold, but the soft definition (that the price will veer towards true value), does hold. The big question is how quickly does it get there? That means there is potential to make money (if it takes n minutes, and you are able to trade at n/2, and exit at n, you're going to make money). Insider traders can make the most money, but there is also money to be made on much longer trends too, I think. Most of the super smart people throwing money at algos and hardware are specialising in HFT to try and trade at very high speed. They are typically not looking at much longer trends. That means there is perhaps more exploitable value for the individual in longer trend spotting compared to shorter term trends. (Note, I don't mean technical analysis when I talk about trends.) Would I recommend you get into market making and HFT? Not without an eight figure sum to get started. Would I recommend you get into value investing and looking at the long-term? Sure, just remember that diversification is good for a reason, and you might struggle to beat an index - most professionals do. If you enjoy it though, you might find it a good way to make your retirement savings grow, perhaps even a living. Would I recommend you get into day trading? Probably not, but that doesn't mean there aren't successful day traders sat at home making a living trading on margin. It's hard work, and if you're smart enough to make it pay, you're probably smart enough to make more money doing something more productive for society instead. I also don't think most people are smart enough to make money (important note [1]), if they try and work out by "thinking". Don't try and move from first principles. Learn from successful people, who aren't full of BS. The vast majority of people on YouTube and selling books are not successful. There are real success stories out there, you need to filter a lot to find them, but they exist. Use them. [1] Your question was if people can "outperform" the market. You don't need to outperform the market, you don't need to be optimal, you "just" need to make enough money to meet your goals, and preferably more than you would get just from leaving your money in an index tracker. That's not the same thing. If you're trying to perfectly enter/exit trades and "beat the market", you're dead before you get started.
mring33621 1y ago
I have done, using my own real money, algorithmic swing and day trading for many years. There are patterns that can be found and exploited, in the short term. However, I was unable to predict changes in the trading environment. My software did not even try to watch the news. So when big macro events happen, like a civil war in Syria, for example, the patterns can change overnight, so I sometimes was left holding a heavy bag.
immibis 1y ago
80% of it is the world's largest and longest-running Ponzi scheme. Because it's a Ponzi scheme, it brings negative expected value (maybe the other 20% cancels it out, maybe not). But because it's the world's largest and longest-running, you'd better participate because the chance it collapses at the exact moment you didn't invest but everyone else did is pretty low, and you can't let them outcompete you in the short term. You have a significant chance of not being the bottom tier of the Ponzi, unfortunately. If you do invest and it does crash, you're no worse off than everyone else. That's for general market trends. Individual stocks also make no sense. You could buy and hold some very stable company's stock but you're making a relative pittance compared to just, like, changing jobs or something. Expected compound interest is not high enough to justify the risk of a catastrophic crash; also if you think a crash will happen any time in the next forever, you're better off holding cash or low-risk bonds until after the crash and jumping in then, as that will more than make up for the compound interest you make up on. In the past, compound interest has been significantly higher than expected, and very much worth it, but only due to survivorship bias. There are many reasons to think the next 60 years won't be anything like the last 60.
- Fade_Dance 1y ago
  >Expected compound interest is not high enough to justify the risk of a catastrophic crash That's just not the case. It may be a lower yield world, but you can still find companies with relatively stable and growing 10-15% cashflow to EV ratio even in the US. Outside of the US old-school "easy" Value is still very much alive as well. What you were advocating for is market timing, and market timing demonstrably does not add alpha unless it's done very mindfully, mostly because the opportunity cost of sitting out is great. If you look at core alpha sources through a factor lens like trend following, most of the profit comes from participating in the big trends (read, most of the easy returns come from "expensive" getting "more expensive/"overbought"). From another lens that takes into account fragility/crashes - vol trading - selling vol is paradoxically highest sharpe when vol is low and most vulnerable to severe disruption. Part of what you're disregarding is how market participants are far more sophisticated today than they were even 20 years ago. If you're building a 60/40, it doesn't look attractive, but even accounting for survivorship bias, the baseline has risen. The "crash case" remains relatively similar when it comes to portfolio planning - you need to prepare for 60% crashes, and 10-year "lost decades." The tools to manage that equity risk and still access smooth returns are far more powerful and accessible than they were in the past though.
NotAnOtter 1y ago
I stick with the dog walker analogy. A man walks down the street at a steady pace, and the dog on the leash runs back and forth and side ways and sits and jumps. The man is the economy, the dog is the market. Unless you have access to HFT systems & models, there is no point in trying to guess where the dog will go. You have to look at the man, which is the aggregate health of the economy. If I start to see the man walk backwards, I sell, and vis versa. But *mostly*, I just stick things in ETF's and don't worry about it unless I need the money in the near future.

AIorNot 1y ago

So did it make any money?

kinnth 1y ago
It doesn't look like it. There isn't a clear comparison to a "human trader".
jsheard 1y ago
If it did, I think it's safe to assume they would have sold it to a quant firm and we never would have heard about it.
- TechDebtDevin 1y ago
  This. It is a gimmick.
IronyMan100 1y ago
one drawback here is the backtesting. They backtesting only 1 year in 2023.

flowerthoughts 1y ago

> Alpha Factors incorporates 108 technical indicators and factors with their expressions, which are believed to possess predictive power regarding stock price movements. Examples of the indicators are in Figure 15. The ablation studies in Table 4 suggest that market and news information made a much bigger impact than the magic indicators. Makes sense if the indicators are simple enough that the LLM can reproduce them without losing processing power. I somewhat like that they used DJI and not SPX, but 2023 was a sideways bull year with DJI +12% and SPX +23%. One year is way too short of a study. > Hardware: NVIDIA A5000 GPU x 4, AMD Ryzen Threadripper PRO 3975WX CPU, 256 GB RAM Seems approachable. > The proposed TradExpert framework utilizes a Mixture of Experts (MoE) approach, where four LLMs are specialized in processing distinct sources of financial data. All these LLMs are based on the LLaMA-2-7B Touvron et al. (2023b) model and fine-tuned using the LoRA mechanism Hu et al. (2022) Relatively small LLM. Overall, this does seem like an interesting study, even for just comparing data sources.

blitzar 1y ago
> 7B, Relatively small LLM. Possibly too large a model. (Daily) finance data is finite - 7B parameters is potentially order(s) of magnitude more than the training data.
- flowerthoughts 1y ago
  Yes, but these are LLMs where the point is they understand English prompts and information. They aren't just fed market data.

niemandhier 1y ago

If I understand this correctly we have come full circle on what MoE means. MoE started out as some form of multi model approach. Afaik in current architectures it’s basically a load balancing method that while it increases latency makes the model better suitable for distributed operations. To me this reads as if the author uses the term closer to Urs original meaning than its current.

mzhaase 1y ago

I want to coin a new law: if a news title has "revolutionizing" in the title, its bullshit.

thomassmith65 1y ago
The phrase "changing the [something] game" is the most obnoxious.

amelius 1y ago

I'm curious at what point stock and derivatives trading becomes something entirely for AI, and thus restricted to companies rich enough to buy tons of GPUs. Are we near that point yet?

TechDebtDevin 1y ago
We've been past that point for more than a decade. This is a gimmick.
- amelius 1y ago
  Then why are there still brokerage firms targeting small people?

mkoryak 1y ago

Do is it "tradExpert" or "tradeExpert" ? Shortening variable names from words by a vowel or two is a hge pt peev.

infecto 1y ago

Not a very good study. I did not look at any of the researchers background but it’s like they did not consult their respective finance school departments.

csantini 1y ago

The market is like an ecosystem. There are huge mammals (investment banks, hedge funds) that look at certain type of preys, and there are smaller rodents that only eat very tiny worms. In high volatility regimes, ie. stocks with low market cap, the market is far from efficient. Hedge funds are not even looking at stocks with 100M market cap. There are traders that act in these regimes that beat the market, exactly because they play small. Anyhow most people would be better of by assuming the market is completely efficient.

thunder-blue-3 1y ago

fwiw, I tried something similar about 5–10 years ago. I wasn’t using LLMs like the abstract here suggests, and honestly, I’m not sure how you'd act on a signal fast enough with them. When I gave it a shot, there was some slight predictive value, but in the end it felt like noise and gambling, so I moved on.

bguberfain 1y ago

So they used a LLM with knowledge cut in mid 2023 to evaluate 2023? Seems like a classic leakage problem. From paper: "testing set: January 1, 2023, to December 31, 2023" From the Llama 2 doc: "(...) some tuning data is more recent, up to July 2023."

mhmmmmmm 1y ago
Removing the "Market expert" which uses OHLCV (Open, High, Low, Close, Volume) also drops the sharpee from 5.01 to 1.88 while also increasing the max draw down to 13.29% (v.s. 9.70% for the index). I'd be very surprised if the pre training of the base model was the only source of leakage...

languagehacker 1y ago

How did it perform against a boglehead portfolio? Were fees and commissions included? Seems weird to evaluate performance over a single year for trades. Much more interested in long-term growth over one or more market cycles.

Fade_Dance 1y ago
I think if you're talking on portfolio level a lot of these things are used as signals and parts of a greater whole. In that sense, they can indeed add value. My current project is a modern version of a classic Harry Browne portfolio with even asset allocations to gold/bonds/equity/commodities, with optional layers of sophistication according to spec needs. Something like systematic macro could be analyzed as a standalone return stream, but it's more useful when considered as an input into allocation/leverage adjustments (ex: if geopolitical uncertainty readings are high, cut down the trend following exposure). Even the more robot/quant stuff like vol trading feeds back into the wider portfolio management and portfolio construction level to some degree.

ta12653421 1y ago

Good one, happy to add my perspective here: DISCLAIMER: I've spent the last 8 month heavily on building a quant-based asset management app (though, still not live, currently in final steps to sync processes with broker) a) I tried to leverage some of this AI-voodoo stuff, though not on the level as in the paper; my findings are clear (at least for me): AI-driven trading does not give you a bigger/better edge than any of the other well-known approaches b) In fact, AI-based approaches are at best on par with traditional approaches, in lot of scenarios not even this; I havent seen any setup from anyone which actually outperformed one of the classic approaches. BUT: The AI-guys have much higher cost, be it Infra, processing time / waiting time in front of screen etc. So you have you to pick carefully, which one you choose. c) I'm doing today only "standard approaches" with volume/statistics/vola/price action, as this approach is super-cost-efficient (i need only one cheap datastream) and a lightweight machine for 10 / 20 USD a month d) It is clearly possible to outperform the market, though these approaches are not scalable unlimited - Ex: depending on the used instruments, there may not be enough liquidity to buy continuously for 100k, but maybe for 10k only. Apply leverage of 5-10 on an asset that moved 5% in last 10 days on a 10k position - is this outperforming? A clear >yes< in my perception? e) People who have built & found a stable approach do not share it or talk about it, there is no real community; you will get details of working approaches only from people whom you are really "friend with"; there is a lot of unshared but working business tactics in the field.

r0b05 1y ago
Are you referring to LLM's when you mention AI here?
- ta12653421 1y ago
  Thanks for the question: Not really in the field of trading, rather prediction-based approaches etc.; Im not sure if LLM could be of any use here? The approaches based on statistical arbitrage are purely math/number models. from my own experience, LLM are absolutely useless when it comes to "trading ideas" (I use them for code generation, instead), this is because they are dicing together values in their output which are not really related, because of their hallucis. Also, for fundamental analysis they are too often incorrect - so running an auto-approach based on LLM-fundamental output would be an "interesting" idea :))

reedf1 1y ago

Did they release the code or the model itself?

16th_hop 1y ago

Does anyone understand how the Market Expert works? It takes in numerical OHLC data and converts it to embeddings for use by the LLM… but embedding are also numbers so I don’t see how that’s any easier for the LLM to process since it’s a language model. > The Market Analyst LLM focuses on analyzing historical OHLCV (Open, High, Low, Close, Vol- ume) data to predict stock movements. However, time series data is inherently continuous and lacks the discrete token structure that LLMs are designed to process. This misalignment poses a signifi- cant challenge in effectively utilizing LLMs on time series. To this end, we utilize a reprogramming mechanism Jin et al. (2024) to reprogram the input financial time series into text prototype repre- sentations.

immibis 1y ago

[flagged]

thedudeabides5 1y ago

lol 5 sharpe classic 'tell me you overfit without telling me' tell

mhh__ 1y ago

A sharpe of 5 is ludicrously good for a long only equities strategy

bGl2YW5j 1y ago

I feel like applying MoE to LLMs is a just a brute-force prediction approach that's neither efficient or very accurate.