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.
Perplexity AI's new tool for researching the stock market
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Re: Perplexity AI's new tool for researching the stock market
#22Earlier 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.
Re: Perplexity AI's new tool for researching the stock market
#23Speaking 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…
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
#24Earlier 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?
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
#25Am 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.
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
#26Speaking 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.
- $$$ FactSet
- $$ 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
#27Re: Perplexity AI's new tool for researching the stock market
#28Earlier 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?
Re: Perplexity AI's new tool for researching the stock market
#29Re: Perplexity AI's new tool for researching the stock market
#30Earlier 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?
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.