Perplexity AI's new tool for researching the stock market
zdnet.com
zdnet.com
This reads to me like garbage in, garbage out... just like 99.9999% of current resources on financial data.
There's definitely an opportunity to disrupt this backwards "financial data" industry, but it's not going to be done by slapping LLMs and RAGs onto stale data in 10-Qs and 10-Ks.
Building a useful forward looking financial model mostly involves qualitative analysis. This means thoroughly examining the company's and competitors' 10-Ks and 10-Qs, digesting industry reports, understanding the company’s business model, breaking down the underlying mechanics of the income statement, balance sheet, and cash flow statement, identifying the core processes driving value creation, forming solid hypotheses on how the business will evolve, etc.
I believe Perplexity, as an advanced answering engine, provides a strong foundation for supporting this kind of in-depth research and hope to see the platform evolve into this direction.
I've been researching a bit and everything I could find was basically APIs that charged you by the number of API request calls to extract the dataset bit by bit. First the tickers, then the aggregates... and so on.
- $$$ FactSet
- $$ Capital IQ
Depends on how much money you have and what your needs are but that's basically it
To put it differently, historical financials, K/Qs are all data points that have been commoditized and you can pull it instantly.
The former is what equity research analysts do at major investment banks (like Morgan Stanley, BAML, JP Morgan, etc.) and boutique / middle-market research firms (Stifel, Cantor Fitzgerald, Raymond James, Guggenheim, etc.). Google has led me to this LinkedIn post with a long list of equity research firms which seems accurate and credible after skimming it briefly: https://www.linkedin.com/pulse/most-comprehensive-list-sell-...
The latter is what I used to do as an M&A advisor. Basically the "I want to buy company X, how much should I pay?" or "I may be interested in selling / people are reaching out expressing interest in my company, how much am I worth?" type of scenarios, plus some other more complex but not necessarily more fun things like merger of equals and what have you. In these situations, the analysis tends to be more of a "let's look at it from all angles" which usually gets distilled into a one-page summary nicknamed "football field" showing ranges of values according to various methodologies. Things like DCF, discounted equity value, relative trading multiples (also called "comps"), LBO (also called the "floor valuation") all get featured and are the standard metrics on which an advisor's view is supported.
As an advisor, I never came up with my own projections for valuation, because that would open the door for litigation so it's just not done. Instead, we point to what "the street" is saying, by taking the consensus view (often some filtered average/mean of equity research projections usually provided by Bloomberg, FactSet or Capital IQ for liability reasons, but which may be "handspread" in some situations by actually pulling the specific numbers from the latest available research reports from several analysts and calculating the mean).
I hope that helps answer your question but happy to answer any follow-ups too since I'm always glad to share what I know about the topic
Which makes sense - seems like Perplexity will always cater towards your average retail investor, there’s just too much complexity and cost to acquiring the type of data a professional cares about. Seems like that will need a to be its own platform.
That's one of the rows of the football field. Actually one I forgot to mention, often called "precedent transactions". You can see some examples of these slides if you scroll down to "Why these slides are made" here https://www.alexanderjarvis.com/investment-banking-slide-exa...
But when I mentioned relative valuation or trading comparables, I meant looking at similar public companies today and what their implied valuation is based on their current share price (more about that here https://news.ycombinator.com/item?id=41862295)
Those relative valuation methodologies are different so-called "intrinsic" valuation methodologies like DCF or discounted equity value, which just look at the company you're valuing and do some math "in a vacuum" to get some implied value per share.
> Which makes sense - seems like Perplexity will always cater towards your average retail investor, there’s just too much complexity and cost to acquiring the type of data a professional cares about. Seems like that will need a to be its own platform.
I agree, but there's definitely a lot of room for automation in the professional space. Unfortunately I can only tackle one startup at a time so that's like ~third on my list of revolutionary ideas that I'll get to one day ;-)
He also reads mainstream press - wsj, ft etc.
I always hear these finance people dick waving about how crap everyone else's methodologies are without examples of their own. This leads me to conclude it's all snake oil anyway.
So I'm asking, speaking as a former M&A financial advisor... What _does_ work?
- It can be a bit of a zero sum game and the Buffett's and Soros make outsized returns because joe public makes lower ones.
- Investing like that is hard - Buffett would basically spend all waking hours studying the stuff when younger. Just reading a How to Invest Like Buffett article doesn't cut it.
- Most "investment professionals" make money on fees from clients and so will recommend what sells to clients - typically the hot thing of the day - rather than what's the best investment which is often cheap because most people think it's dull / doomed / unrespectable.
I recently answered a similar question so if you don't mind I'll just link you to it: https://news.ycombinator.com/item?id=41862295
Genuinely wondering. Is this because they have so much money to play with that they can move markets in their favour?
At least what my firm does, is we look at the current state of the market at any given time point, and test whether the current state of the market satisfies our model of an efficient market. If it does, then there's no action to take, if it doesn't then we determine what kind of violation is present and jump in to close the gap.
So a very trivial example would be to take two ETFs, like QQQ and TQQQ. As a simplification a model of an efficient market would have at any moment in the day the change in price of TQQQ = 3x the change in price of QQQ.
We then observe the actual state of the market and if the actual change in price of TQQQ matches our model, then there's nothing to do. If it doesn't, then either TQQQ is under priced or it's overpriced or QQQ is underpriced or it's overpriced (or our model is just wrong or some outlier). Depending out what the condition is we buy x dollars worth of TQQQ and sell 3x worth of QQQ or do the opposite.
There's no real prediction here, we simply have a model of what an efficient market looks like, we scan the market for violations of that model, and then we perform an action to bring the market back to an efficient state.
The model I presented above is incredibly simple and just for illustrative purposes, but in a nutshell, that's our job. We have literally hundreds of models for an efficient market and for every model we have algos that test whether the market satisfies our model, and when the market deviates from our model the algo produces a signal which other algos act.
And yes, high throughput and low latency are critical aspects of our trading and they are factored into the model as well, in that for every deviation we observe from our model need to measure how long such a deviation is likely to last and we only trade on those which are likely to last long enough for the trading algo to complete.
But I also assume that's not the type of thing parent comment is asking about - Any rational actor with an opportunity to do this would already be doing this after all.
I'll probably use this in some of my investigations, but definitely need to look at the citations.
>At this stage of the game, though, Perplexity Finance needs much more refining before I can call it a real competitor to the existing stock analysis programs, such as Stock Rover, WallStreetZen, and TradingView.