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Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

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Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#91

Post by throaway101o »

scottydelta wrote: post #32
nodesocket wrote: post #17

Earlier quoted context omitted.

How are you different than the native macOS WeBull application? WeBull comes the closest I have seen to a Bloomberg terminal.

WeBull only provides financial and newsmedia data about the stocks but Quantale is the first of it's kind to provide not only Financial and newsmedia data but also real-time data from SEC, Reddit, and Twitter. Along with that, additional features include: - Top trending stocks from the internet in real-time - Sentiment of the discussions using a pytorch model. - Ability to save posts(reddit, twitter, news headline, s…

This isn’t really true… there are a myriad of web tools that provide similar functionality and most are free such as:

- https://gamestonkterminal.netlify.app/ - https://gbear.trade - https://app.hypeequity.com/monitor

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#92

Post by danielmarkbruce »

jdavis703 wrote: post #90
soheil wrote: post #80

Earlier quoted context omitted.

I think big part of a strategy like this is long term. If you want to short a stock you need to make sure the fraud is discovered by other investors. So you probably need to have a strong marketing department that basically thrashes other companies, this may not be a goal a lot of people aspire to. With a short you're also exposed to lose an infinite amount. And finally "markets can stay irrational longer than you ca…

My guess is they also have plans to move in on other sorts of fraud detection, for example bond issues or privately held firms. That’s my good faith interpretation. My bad faith interpretation is they don’t trust their algos enough to trade on it themselves.

I guess I'm not even saying it's bad/good faith. I just literally wonder - why not do the obvious thing? A number of years ago I ran into several people trying to sell services predicting stock movements via twitter sentiment. Same thing - if it works just make billions fast using it to take positions. It's not trivially easy to start a hedge fund, but it's not rocket science either. The key ingredient is finding a way to make good returns. These twitter people seemed to have good intent.. it was just strange.

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#93

Post by frijole »

kbennatti wrote: post #6
c3pa wrote: post #3

> Our algorithms picked up these red flags and more, and assessed Sino-Forest as high risk when we ran our models on the company’s historical filings. When you're backtesting your models, how do you distinguish between novel fraud that the industry is _now_ aware of vs. fraud that was visible but ignored -- if your model has learned _from_ Sino-forest, how do you know it would have caught Sino-Forest at the time? > F…

Great q. Sino-Forest is an out-of-sample test so our models didn't technically "learn" from it. That said, very valid comment. Historical testing only goes so far. Assessing whether our algorithms work in deployment has been cool. Check out some of our live, in deployment examples here - https://bedrock.substack.com/p/bedrock-ai-vs-activist-shorts

Just about every company mentioned in the article increased in value near and/or after the time of those reports. Pretty interesting.

Great work!

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#95

Post by RandomLensman »

Great stuff.

Do you have any data/indication of the outstanding short positions vs. when you detect something, i.e. are these generally stocks shorted quite a bit at that time? Could they even be borrowed/how expensive were they to borrow?

These kind of analyzes are definitely interesting (and are happening elsewhere I think, too). So really cool area!

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#97

Post by davedx »

Hi, great idea! I tried to do something similar for earnings call transcripts and got very stuck very fast, so I appreciate that this is quite a tough problem. My suggestion would be to indeed see if your algos can extract useful structured data from earnings calls too, as often c levels give information here that’s not necessarily included in the regulatory filings. Good luck!

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#98

Post by bambax »

HeatherJudd wrote: post #51
bambax wrote: post #46

> Most public company data is unstructured and textual. This is surprising to me. Wouldn't it be possible to make a very short list of, say, 12 blunt questions that would help flag fraud? Of course the company could be lying in the answers. (If it was found to be lying in any one answer then it would automatically be flagged as "high risk".) But this may not even be needed, since what you seem to be saying is that th…

An interesting idea. I'm not sure if say 12 or so questions could cover the risks, or it if would just add one more data point for people to (not) read? There are certainly some sorts of transactions that are much more risky than others - so having an easy source for these transactions would be useful (and we'd built it into our models). But often the signals are more subtle. Companies with overly aggressive accounti…

> or it if would just add one more data point for people to (not) read?

Intuitively fraud should be correlated to specific accounting practices, or maybe simply to the number of hours billed by the auditors, who are likely to charge more if the work is more "complicated"... Disclosing the amount paid to auditors could be one of those questions.

An analogy would be the "Joel Test" (2000) [1]; checklists in general, and direct questions, are much more revealing than blurb written by the target or a communications agency.

My two cents.

[1] https://www.joelonsoftware.com/2000/08/09/the-joel-test-12-s...

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#100

Post by kbennatti »

doctoboggan wrote: post #99

Just curious, are you doing anything to prevent companies from running drafts of their disclosures through your algorithm? That would allow them to tweak the disclosure until your AI gives it a positive score.

We don't sell to filers. Ever. Got to protect against conflicts of interest. That's one of the reasons we don't have a true free version of the product.

That said, we're using language models so replacing words with synonyms won't evade the model as long as its expressing the same thing.

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