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Perplexity AI's new tool for researching the stock market

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21–30 of 45 posts

Re: Perplexity AI's new tool for researching the stock market

#21
post #16

Earlier quoted context omitted.

What makes you confident a methodology that consistently beats the market exists?

There are a number of wealthy investors who don't tell other people about their methodology. They're either very lucky, criminals, or have beaten the market.

There's wealthy, and there's Wealthy. As the market itself tends to trend upwards, you can absolutely ride that into wealthy, no crime or extreme luck required.

Re: Perplexity AI's new tool for researching the stock market

#22
post #14

Earlier quoted context omitted.

That's a lot of "this won't work" without very much "here's what does work" leading me to conclude this is bluster and ego. 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?

nothing. There is no way to predict the stock market. Even the way you're probably thinking of. Even the ones in the replies to this comment. Even the really basic ones and the really advanced ones.

The existence and success of the Millenium fund is a (probabilistic, to be fair) disproof of your assertion.

Re: Perplexity AI's new tool for researching the stock market

#23

Speaking as a former M&A financial advisor and valuation nerd, historical financial data is very close to worthless for any valuation work, except perhaps for vaguely connecting the dots to your proprietary, forward looking financial model which is based on a deep understanding of a particular company and industry. This reads to me like garbage in, garbage out... just like 99.9999% of current resources on financial d…

While I agree with your statement and recognize that, for now, Perplexity has only introduced a financial information platform comparable to Google Finance or Yahoo Finance, the true value of any forward-looking financial model is rooted in the depth of the qualitative research supporting it.

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.

Re: Perplexity AI's new tool for researching the stock market

#24
post #19
post #16

Earlier quoted context omitted.

What makes you confident a methodology that consistently beats the market exists?

If such methodology doesn't exist then how are quantitative trading firms in business? Genuinely wondering. Is this because they have so much money to play with that they can move markets in their favour?

The one consistent method I know of would be high-frequency trading to front-run orders, which involves maintaining a moving target of state of the art infrastructure (both hardware and software), including a relationship at the markets so you can get an ultra high-speed connection (I'm certain there are rules with this to make it fairer, but I would assume not everyone will be provided a connection simply due to physical limits).

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.

Re: Perplexity AI's new tool for researching the stock market

#25
post #8

Am I missing something, or is this just a normal stock browser like Yahoo Finance? I don't see anything remotely new in the article or the site ( https://www.perplexity.ai/finance/NVDA ) and it doesn't seem to have anything to do with AI. It's a nice-looking feature but I don't think it's newsworthy.

The benefit is that it gives you some suggested topics of investigation, including references to where it found that information. For example, I looked at one stock I'm interested in and it suggested there was a potential short squeeze in the making, and the references pointed out that that was 7 months ago. So it was summarizing it thinking that was a current state. It also suggested summaries about how changes in classification of the business might impact the stock price.

I'll probably use this in some of my investigations, but definitely need to look at the citations.

Re: Perplexity AI's new tool for researching the stock market

#26

Speaking as a former M&A financial advisor and valuation nerd, historical financial data is very close to worthless for any valuation work, except perhaps for vaguely connecting the dots to your proprietary, forward looking financial model which is based on a deep understanding of a particular company and industry. This reads to me like garbage in, garbage out... just like 99.9999% of current resources on financial d…

Is there a "backwards" financial data service you'd recommend instead? 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.

- $$$$ Bloomberg

- $$$ FactSet

- $$ Capital IQ

Depends on how much money you have and what your needs are but that's basically it

Re: Perplexity AI's new tool for researching the stock market

#27
Somewhat related: Last night I fed 3 companies proxy statements to Notebook LM and had it generate a "podcast" on them. One of which was a 100 page document, which I read the bulk of, and the podcast was pretty good, though it did misrepresent one 2023 statement as being a current statement. Definitely a tool I'm going to be using more.

Re: Perplexity AI's new tool for researching the stock market

#28
post #19
post #16

Earlier quoted context omitted.

What makes you confident a methodology that consistently beats the market exists?

If such methodology doesn't exist then how are quantitative trading firms in business? Genuinely wondering. Is this because they have so much money to play with that they can move markets in their favour?

How many quantitative trading firms have gone out of business?

Re: Perplexity AI's new tool for researching the stock market

#30
post #19
post #16

Earlier quoted context omitted.

What makes you confident a methodology that consistently beats the market exists?

If such methodology doesn't exist then how are quantitative trading firms in business? Genuinely wondering. Is this because they have so much money to play with that they can move markets in their favour?

As a quant myself, we don't try to predict the market, at least not the way that people normally talk about predicting, and we certainly don't move the market in our favor.

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.

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