You are charging way too much and offering too little. $29/month to track 15 companies, $89 to track 50, and "Contact sales" for unlimited. The "AI Analysis" you have is too brief and doesn't tell me anything useful as an investor.
As someone who was a paid customer of Quartr: they do not offer the ability to look or search actual filings at the $20/month plan. Full text search starts from $500/month, and is an annual contract (so $6,000/month.)
Pricing for these services is not cheap, given it can be very helpful for professional traders.
(I’m no professional trader, and not even a trader. I just sometimes want to search for interesting things in transcripts, when I research a topic. I would pay for a decent service offering full text search for transcript search, to use it a few times per month (or perhaps even less frequently). Still not found a product that does it at a sensible price point for my use case - likely because my use case is not worth building a business on.)
Not at all, I’m inclined to agree with the commenter. If you work in the industry you can immediately pick up a few problems.
1) SEC filings are largely useless. For earnings, funds typically look at the press release that companies put out. 10-Qs and Ks are sometimes released days or weeks after earnings are already out. You could potentially trade on filings that disclose insider share transactions but these are largely noise.
2) Setting all that aside, who exactly is buying this? Citadel/P72/all the other institutional investors have entire teams of data scientists. I’d be surprised if they didn’t have similar tools already with better functionality. Maybe this picks up steam with the retail crowd, but I doubt any average investor is going to have a trading system that can take advantage of this.
There’s just limited practicality and an even more limited customer base. Even if this were free, Im not sure I would have much use for it
Unfortunately much of earnings responses is written after the fact. If the stock price goes up you can point to some positive parts. If it goes down, you can point to some negative parts. I see that all the time. "Earnings beat estimates but analysts were worried about declining growth in app related earnings and looming regulatory threats". Sometimes they even switch! The stock goes up, reporters write their pieces, then it goes back down and switch over to another explanation.
I'm reminded of the headline "More than 16M Americans have lost jobs in 3 week, dow's best week since 1938"
> I'm reminded of the headline "More than 16M Americans have lost jobs in 3 week, dow's best week since 1938"
That's likely a significant contributor behind the November election results in the US and across Western countries in general. People aren't dumb, they spot through politicians and media claiming "good economy numbers" while their own paychecks don't come close to keeping up with inflation.
The economy numbers may be at record highs, but way too much of the wealth ends up in the pockets of a very select few.
> The economy numbers may be at record highs, but way too much of the wealth ends up in the pockets of a very select few.
It's not that at all. Things like Russia spending all its money on the war effort boosts GDP, but doesn't help prices in the long term. The measures often don't measure costs, other than inflation.
It might kick out 2 or 3 "good idea" trades a year that you could milk, but the real value in this data is getting it quickly into the hands of people who manage sector portfolios.
Say for example a filing happens that a company will be impacted by trade sanctions. You could short the stock as a naive investor and maybe make a few bucks. Someone with sector knowledge will rebalance their portfolio knowing that customer demand for widgets will shift to sprockets which in turn require doodads. AI isn't there yet because it requires a lot of non-public knowledge to really make money off of.
The value is in scaling this beyond what any individual could do. Yes, the data is public, but building reliable tooling around it, continuously validating the analysis, and expanding coverage across all filings creates far more interesting opportunities than solo trading.
We've already seen how just having basic sentiment and risk analysis has helped our users catch significant changes they would have missed - like subtle shifts in supply chain disclosures that preceded market moves. As we add features like more filing types, earnings call transcripts, and cross-company competitive insights, the system becomes more valuable for everyone.
Plenty of after hours trading happens around these releases so there’s certainly the potential for them to be useful to people engaging in that trading.
It's this. Just doing basic analytics on SEC data for free provides a lot of value to the niche looking for it. A few players have realized that ingesting and normalizing the data is half the battle and charge for very small subsets of data, for example cybersecurity breaches.
Most of the data is unstructured, or worse Edgar xml, adding yet another barrier.
I suspect this case is mostly about sentiment analysis and summary using LLM. The claims about reacting before the market seem egregious.
I think this tool surfaces information not previously immediately digestible by retail investors.
Institutional investors have had systems like this in place for decades. LLMs might improve parsing the data in some ways, but this is (and was) completely doable before the LLM era, meaning there’s probably not a huge amount of secret sauce here worth protecting.
If anything, a project like this simply improves the information asymmetry between retail and institutional investors.
Not true. I can’t speak to the situation in the US but, in the UK, there are certainly platforms that enable after hours trading on US markets even for retail traders.
It's priced in. I guarantee every major hedge fund had a prototype running within hours of GPT API being made public, and they're probably running it on real money right now.
Everyone who is anyone in the finance space has been doing stuff like this since way before LLMs were a thing, and they've put a lot of time and effort into their tools. This suggestion is kind of like saying you should try to sell your lemonade stand to Coca-Cola.
That's exactly what I'm saying. If you've got something novel/hard to replicate, it's a no-brainer for them to pick up at any price. If not, that's good to know too.
Btw, Coca-Cola bought Minute Maid Lemonaide in 1960. :)
This is a good example of Dunning-Kruger, no offense. Sentiment analysis has been used as a tool to guide investments since the late 90s and there are companies out there who have been doing it for decades. LLMs didn't really break any new ground here, they just made this more accessible for the masses.
> Sentiment analysis has been used as a tool ... since the late 90s
Yes!
> LLMs didn't really break any new ground here
I don't think this is true. LLMs are a gigantic leap forward from any traditional sentiment analysis I've seen. Pre-2013, bag-of-words and TF-IDF were still state of the art. Call me out if you think I'm wrong, but hand-waving away the transformative power of LLMs here because we had some sentiment analysis approaches before seems unfair.
Sounds like you are the one suffering from Dunning-Kruger. Just check out one of the reports and you will see that it's lots more than just "sentiment analysis", and much more dynamic.
I'm in the business of selling AI tools to high-frequency traders / hedge funds and the bad news is that, most of them are so risk averse and/or technically illiterate that sometimes we joke that there's big alpha to be had in starting a hedge fund that simply embraces AI.
I think you might be slightly misunderstanding why you're struggling to sell. In finance, correctness matters. A tool that's mostly right most of the time, but radically incorrect sometimes is a very hard sell when there's battle tested and well understood boring tools out there that do the same thing.
Ive heard many variations of this along the lines of pennies and steam rollers. Yes, you have to have positive EV across the strategy. And just about everyone makes money when times are good, or theres volatility that matches your strategy, or your pods null out a bunch of factors.
But to survive long term you have to _not fail_ in a very repeatable and consistent manner. Long term success is risk and downside management.
> there's big alpha to be had in starting a hedge fund that simply embraces AI.
Maybe hedge funds are completely out of step with the rest of the finance world, but much of finance has been using AI for a long time. AI is old news at this point.
I’d guess they’re already using this signal and if not they’d be more likely to do it at competitively high speed and internally, where they can control and iterate? Maybe crypto HFT since that’s a big more sluggish.
Congrats on the release! I really like what you've done here. Making existing professional trading tools more accessible is a great path.
I'm especially intrigued by the use of AI to analyze the Risk Factors section. I've been working on a tool to SaaS increase sales by combing through 10-K Risk Factors and seeing which companies, industries, markets make the best sales targets. It becomes a matching algorithm between the value levers of the SaaS solution and the needs expressed in the Risk Factors section.
Do you have any plans to incorporate economic data from the monthly releases by BLS, BEA, Census, Federal Reserve, etc.?
A bit late, but thank you for this comment. Appreciate the feedback. The features are actively expanding. Currently we have added 8K's and Form-4s, for handling SEC filings coverage. As our userbase grows alongside their feature requests and analysis presents new data points worth investing into we will increase the scope on a bang for buck basis.
Having tested this extensively against historical market movements, I'm quite confident in its analysis accuracy. After running it against countless filings and tracking post-filing price movements, the system's risk assessments and change detection have proven remarkably reliable - especially for catching subtle shifts in risk factors and management tone that often precede larger market moves.
I personally rely on it for my own decisions, but like any tool, it's most effective when used as part of a broader analysis process. The system is great at rapidly surfacing the most significant changes in these massive documents and contextualizing them against historical patterns. That's incredibly valuable for making timely decisions, especially since the market often takes days or weeks to fully price in the implications of complex filing changes.
That said, the analysis code has built in multiple validation layers and error handling because filings are just one piece of the market puzzle. The code is designed to be conservative - it'll fail closed rather than make questionable assertions. But for what it's designed to do - deep analysis of filing changes and their implications - it's proven to be a reliable tool for actual decision-making.
> The system is great at rapidly surfacing the most significant changes in these massive documents and contextualizing them against historical patterns.
probably worth capturing a few successful situations and documenting that in some marketing way.. also probably worth capturing a few Very Big Fails and making a ticket out of that internally, to improve the system. Seize the day!
If you mean that retail trading volume and opportunities to make money from it have a healthy future then I agree. But if you mean that retail traders themselves have a good outlook, in the sense that they will end up with more money overall than if tools and access were more limited, I couldn't disagree more. Retail stock traders have a terrible track record overall, and bits of additional market information here or there will do nothing to change that. Increased access to trading results in amateurs having less money.
You are charging way too much and offering too little. $29/month to track 15 companies, $89 to track 50, and "Contact sales" for unlimited. The "AI Analysis" you have is too brief and doesn't tell me anything useful as an investor.
Compare this to what https://quartr.com/products/quartr-core is offering for $20/month.
I know how difficult it is to build a tool like this and you've done a decent job. Just doesn't make sense to me to price it like this.
As someone who was a paid customer of Quartr: they do not offer the ability to look or search actual filings at the $20/month plan. Full text search starts from $500/month, and is an annual contract (so $6,000/month.)
Pricing for these services is not cheap, given it can be very helpful for professional traders.
(I’m no professional trader, and not even a trader. I just sometimes want to search for interesting things in transcripts, when I research a topic. I would pay for a decent service offering full text search for transcript search, to use it a few times per month (or perhaps even less frequently). Still not found a product that does it at a sensible price point for my use case - likely because my use case is not worth building a business on.)
Wow $6000/month for a $500/month subscription is a bad deal!
5*12=60, so assume $6k/yr.
This has similar vibes to The Infamous Dropbox Comment:
https://news.ycombinator.com/item?id=9224
Not at all, I’m inclined to agree with the commenter. If you work in the industry you can immediately pick up a few problems.
1) SEC filings are largely useless. For earnings, funds typically look at the press release that companies put out. 10-Qs and Ks are sometimes released days or weeks after earnings are already out. You could potentially trade on filings that disclose insider share transactions but these are largely noise.
2) Setting all that aside, who exactly is buying this? Citadel/P72/all the other institutional investors have entire teams of data scientists. I’d be surprised if they didn’t have similar tools already with better functionality. Maybe this picks up steam with the retail crowd, but I doubt any average investor is going to have a trading system that can take advantage of this.
There’s just limited practicality and an even more limited customer base. Even if this were free, Im not sure I would have much use for it
Naive question here: wouldn't the upside of keeping this secret and trading on it's output yourself far exceed what you can make in subscriptions?
Unfortunately much of earnings responses is written after the fact. If the stock price goes up you can point to some positive parts. If it goes down, you can point to some negative parts. I see that all the time. "Earnings beat estimates but analysts were worried about declining growth in app related earnings and looming regulatory threats". Sometimes they even switch! The stock goes up, reporters write their pieces, then it goes back down and switch over to another explanation.
I'm reminded of the headline "More than 16M Americans have lost jobs in 3 week, dow's best week since 1938"
https://www.reddit.com/media?url=https%3A%2F%2Fi.redd.it%2Fr...
> I'm reminded of the headline "More than 16M Americans have lost jobs in 3 week, dow's best week since 1938"
That's likely a significant contributor behind the November election results in the US and across Western countries in general. People aren't dumb, they spot through politicians and media claiming "good economy numbers" while their own paychecks don't come close to keeping up with inflation.
The economy numbers may be at record highs, but way too much of the wealth ends up in the pockets of a very select few.
> The economy numbers may be at record highs, but way too much of the wealth ends up in the pockets of a very select few.
It's not that at all. Things like Russia spending all its money on the war effort boosts GDP, but doesn't help prices in the long term. The measures often don't measure costs, other than inflation.
If it works, yes. If it doesn't work, no it's better to let others convince themselves.
It's the same way creating your own get rich quick scheme is the actual way to get rich quick, not following someone else's scheme.
It might kick out 2 or 3 "good idea" trades a year that you could milk, but the real value in this data is getting it quickly into the hands of people who manage sector portfolios.
Say for example a filing happens that a company will be impacted by trade sanctions. You could short the stock as a naive investor and maybe make a few bucks. Someone with sector knowledge will rebalance their portfolio knowing that customer demand for widgets will shift to sprockets which in turn require doodads. AI isn't there yet because it requires a lot of non-public knowledge to really make money off of.
The value is in scaling this beyond what any individual could do. Yes, the data is public, but building reliable tooling around it, continuously validating the analysis, and expanding coverage across all filings creates far more interesting opportunities than solo trading.
We've already seen how just having basic sentiment and risk analysis has helped our users catch significant changes they would have missed - like subtle shifts in supply chain disclosures that preceded market moves. As we add features like more filing types, earnings call transcripts, and cross-company competitive insights, the system becomes more valuable for everyone.
The best trade isn't always the obvious one.
These releases usually happen after trading hours, so instant analysis isn't super helpful for making trades.
Plenty of after hours trading happens around these releases so there’s certainly the potential for them to be useful to people engaging in that trading.
The information is freely available, this just makes it more readable
https://www.sec.gov/cgi-bin/browse-edgar?action=getcurrent
It's this. Just doing basic analytics on SEC data for free provides a lot of value to the niche looking for it. A few players have realized that ingesting and normalizing the data is half the battle and charge for very small subsets of data, for example cybersecurity breaches.
Most of the data is unstructured, or worse Edgar xml, adding yet another barrier.
I suspect this case is mostly about sentiment analysis and summary using LLM. The claims about reacting before the market seem egregious.
Sell pick axes to gold miners. More predictable!
My first question when I saw the page.
I think this tool surfaces information not previously immediately digestible by retail investors.
Institutional investors have had systems like this in place for decades. LLMs might improve parsing the data in some ways, but this is (and was) completely doable before the LLM era, meaning there’s probably not a huge amount of secret sauce here worth protecting.
If anything, a project like this simply improves the information asymmetry between retail and institutional investors.
Sell shovels during a gold rush.
Typically, you won't be able to make any trades for hours after the info is released anyway.
Not true. I can’t speak to the situation in the US but, in the UK, there are certainly platforms that enable after hours trading on US markets even for retail traders.
Everyone has access to this data.
It's priced in. I guarantee every major hedge fund had a prototype running within hours of GPT API being made public, and they're probably running it on real money right now.
Have you tried selling to high-frequency traders / hedge funds? If they bite, it's probably not even worth having a low-cost/self-serve tier.
Everyone who is anyone in the finance space has been doing stuff like this since way before LLMs were a thing, and they've put a lot of time and effort into their tools. This suggestion is kind of like saying you should try to sell your lemonade stand to Coca-Cola.
That's exactly what I'm saying. If you've got something novel/hard to replicate, it's a no-brainer for them to pick up at any price. If not, that's good to know too.
Btw, Coca-Cola bought Minute Maid Lemonaide in 1960. :)
This is not possible without LLMs. The interesting stuff is not the numbers but the soft values and insights. Go check out the example reports.
With that said, I agree that hedge funds probably already have their own internal versions of this.
This is a good example of Dunning-Kruger, no offense. Sentiment analysis has been used as a tool to guide investments since the late 90s and there are companies out there who have been doing it for decades. LLMs didn't really break any new ground here, they just made this more accessible for the masses.
> Sentiment analysis has been used as a tool ... since the late 90s
Yes!
> LLMs didn't really break any new ground here
I don't think this is true. LLMs are a gigantic leap forward from any traditional sentiment analysis I've seen. Pre-2013, bag-of-words and TF-IDF were still state of the art. Call me out if you think I'm wrong, but hand-waving away the transformative power of LLMs here because we had some sentiment analysis approaches before seems unfair.
Sounds like you are the one suffering from Dunning-Kruger. Just check out one of the reports and you will see that it's lots more than just "sentiment analysis", and much more dynamic.
I'm in the business of selling AI tools to high-frequency traders / hedge funds and the bad news is that, most of them are so risk averse and/or technically illiterate that sometimes we joke that there's big alpha to be had in starting a hedge fund that simply embraces AI.
I think you might be slightly misunderstanding why you're struggling to sell. In finance, correctness matters. A tool that's mostly right most of the time, but radically incorrect sometimes is a very hard sell when there's battle tested and well understood boring tools out there that do the same thing.
Ive heard many variations of this along the lines of pennies and steam rollers. Yes, you have to have positive EV across the strategy. And just about everyone makes money when times are good, or theres volatility that matches your strategy, or your pods null out a bunch of factors.
But to survive long term you have to _not fail_ in a very repeatable and consistent manner. Long term success is risk and downside management.
> there's big alpha to be had in starting a hedge fund that simply embraces AI.
Maybe hedge funds are completely out of step with the rest of the finance world, but much of finance has been using AI for a long time. AI is old news at this point.
Let's do it :)
I’d guess they’re already using this signal and if not they’d be more likely to do it at competitively high speed and internally, where they can control and iterate? Maybe crypto HFT since that’s a big more sluggish.
I think the world would be a better place if there were less efficiency in the market, not more.
Congrats on the release! I really like what you've done here. Making existing professional trading tools more accessible is a great path.
I'm especially intrigued by the use of AI to analyze the Risk Factors section. I've been working on a tool to SaaS increase sales by combing through 10-K Risk Factors and seeing which companies, industries, markets make the best sales targets. It becomes a matching algorithm between the value levers of the SaaS solution and the needs expressed in the Risk Factors section.
Do you have any plans to incorporate economic data from the monthly releases by BLS, BEA, Census, Federal Reserve, etc.?
A bit late, but thank you for this comment. Appreciate the feedback. The features are actively expanding. Currently we have added 8K's and Form-4s, for handling SEC filings coverage. As our userbase grows alongside their feature requests and analysis presents new data points worth investing into we will increase the scope on a bang for buck basis.
How confident are you in wiring this up to trade immediately off of the output?
Having tested this extensively against historical market movements, I'm quite confident in its analysis accuracy. After running it against countless filings and tracking post-filing price movements, the system's risk assessments and change detection have proven remarkably reliable - especially for catching subtle shifts in risk factors and management tone that often precede larger market moves.
I personally rely on it for my own decisions, but like any tool, it's most effective when used as part of a broader analysis process. The system is great at rapidly surfacing the most significant changes in these massive documents and contextualizing them against historical patterns. That's incredibly valuable for making timely decisions, especially since the market often takes days or weeks to fully price in the implications of complex filing changes.
That said, the analysis code has built in multiple validation layers and error handling because filings are just one piece of the market puzzle. The code is designed to be conservative - it'll fail closed rather than make questionable assertions. But for what it's designed to do - deep analysis of filing changes and their implications - it's proven to be a reliable tool for actual decision-making.
> The system is great at rapidly surfacing the most significant changes in these massive documents and contextualizing them against historical patterns.
probably worth capturing a few successful situations and documenting that in some marketing way.. also probably worth capturing a few Very Big Fails and making a ticket out of that internally, to improve the system. Seize the day!
> Having tested this extensively against historical market movements, I'm quite confident in its analysis accuracy.
This doesn't say anything. Exactly how much have you tested and what were the results?
Most releases happen after trading hours
Agreed, my focus is on data released during trading hours, intentionally or inadvertently.
https://www.youtube.com/watch?v=ag14Ao_xO4c
EDIT: To those suggesting extended hours trading, check out what the order book looks like and who the market maker is.
https://www.finra.org/investors/insights/extended-hours-trad...
Yes, but you can still trade pre-market and after-hours.
you can trade post hours
I like seeing trading tools released. Kudos.
Barriers are falling, fees and such. APIs popping up and interest in markets growing. I'd be bullish on retail trading and its healthy future.
If you mean that retail trading volume and opportunities to make money from it have a healthy future then I agree. But if you mean that retail traders themselves have a good outlook, in the sense that they will end up with more money overall than if tools and access were more limited, I couldn't disagree more. Retail stock traders have a terrible track record overall, and bits of additional market information here or there will do nothing to change that. Increased access to trading results in amateurs having less money.
Here is a free alternative that seems to provide much more https://app.acclara.ai/sec
I fail to see how Acclara is relevant by looking at their homepage. The link you sent is behind a sign up page.
You would probably increase your subscription rate by not putting a signup page before the demo.
Is there documentation for how you calculate the Risk Score?
Who is Doc Delta?
Your trading way after the fact in some cases.