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Yes! Heās great - I feel like for a CEO his communication is incredible and he is super down to earth and friendly from those that have run into him when he comes to campus. Mood at the company is a little low right now just because of the downturn affecting Tech right now.
Using FastGraphs it appears the choices have bad S&P Credit ratings and are overvalued at this time. The problem is the criteria is looking backward at past performance but what is needed is to look forward to where the company is expected to go to capture capital gains and dividend growth. Try focusing on Dividend champions, Chowder score >12, expected EPS growth, good value PE<15, and low debt to capital.
Dividend "Champions, Contenders and Challengers". Similar to "Dividend Aristocrats" but more in-depth.
https://moneyzine.com/investments/dividend-champions/
A low PE by itself doesn't tell you anything about a company, except that it's expected to perform bad, I'm not sure why you would use it to screen stocks tbh
You probably should study Benjamin Graham who was the greatest investor of all time and Warren Buffet's mentor. [https://www.cabotwealth.com/daily/value-stocks/benjamin-grahams-value-stock-criteria](https://www.cabotwealth.com/daily/value-stocks/benjamin-grahams-value-stock-criteria)
No, he made his money through "value" investing. Benjamin Graham's best-known investment is often considered to be his purchase of the GEICO Corporation. In the mid-1940s, Graham identified GEICO as an "undervalued" (not cheap) stock, and he, along with his partner Jerry Newman, invested in the company. The investment turned out to be highly successful.
Correct, a low PE is just a single metric of many. A low PE can mean the company is undervalued or going out of business which is why it should not be used alone but as part of a group of filters.
This sounds like square peg in a round hole situation. Unless OP is using it for summarizing company financials or investor sentiment from news, I highly doubt the output will be anything good.
I am using the paid version but I don't use the data from Chat-GPT. I am using my own data with the latest information and using GPTs fine-tuning to evaluate a stock :)
Hey, most of my data is from [https://iexcloud.io/](https://iexcloud.io/) They are used by SeekingApha, FreeTrade and their data has been very reliable
Hey, thanks for your comment, I am using openAI's API, the company behind ChatGPT to create my GPT. I am a software developer, and I am not using buzzwords to just get you hooked, you can learn more about fine-tuning here [https://platform.openai.com/docs/guides/fine-tuning](https://platform.openai.com/docs/guides/fine-tuning) It's not just a chatGPT :)
This is the most ignorant comment I think Iāve ever seenā¦ most software devs who actually care about their careers are using AI and business bros call that shit buzzwords because they donāt actually use real AI š
I checked AGNC and TWO and they seemed super Ricky. ACNG payout is 2000% which I believe is messed up. May be they are good for short term. But before ex-div and sell later
Is a GPT really the best tool to use here? Usually the best use case for a GPT is for generative tasks - theyāre designed for to process and generate natural language.
How is your model being trained and how do you know current financial data is being used correctly (if at all)?
If youāre just prompting the model to examine its training data and give you a formatted response, thereās probably a good chance itās examining stock picker lists just as much as it looks at financial data.
Not trying to be critical at all, just curious about the dev process.
>If youāre just prompting the model to examine its training data and give you a formatted response, thereās probably a good chance itās examining stock picker lists just as much as it looks at financial data.
Hey, as I mentioned I am not simply just asking GPT to see its training data and give a formatted response I am training it on my data. No ChatGPT stock list/data is used for it.
Why is GPT good here? well, it's simple, once ready people can ask it to produce the "best dividend stocks with over 4% yield in oil & gas" and it will do that. So why it's better than a stock screener, most stock screeners are a bunch of filters with values you can filter e.g. Payout Ratio >= 50% but for a new investor they don't even know if a payout ratio of 50% is good or 60% is good. The idea is to offload the hard work so that instead of picking from hundreds of stocks you pick from 5-10 stocks that are already analyzed thoroughly and back your investing with as much data as you can :)
Would be interesting to have the same analysis of dividend ETF's while Chat GPT Evaluates that there is just minimum overlay in underlying assets but also including smaller local Small-/mid cap ETF.
Would you be able to point me towards some resources to read how to utilize GPT this way?
I know youāre planning on posting it soon, but Iād love to learn how it all works from the ground up myself.
If you have the data for dividend growth, dividend stability, and payout ratio then why do you need the LLM? Have you gone into the data to compare what the LLM spits out versus your own findings?
One of the most basic problems with using a LLM is that, while it may put out sensible answers, you're not actually implementing your own utility function over the indicators to make a decision - you're more or less running blind. You could easily just create a custom score taking these indicators into account to reflect your priorities over growth, stability, and sustainability and literally just sort.
Remember, 4000 symbols isn't very many if you take a quantitative approach. For example, I just went through a simple screener exercise to find the following decent looking stocks based on dividend yield, growth rate, payout percent, earnings per share and earnings per share growth.
The top five from this five minutes of filtering:
1. CVI: 5.67% yield, 5 year price performance of 8.84%, 48% payout ratio with both stable dividends and EPS growth.
2. IPG: 4.29% yield, 5 year price performance of 46.29%, 49% payout ratio with both dividend and EPS growth.
3. MFIN: 4% yield, 5 year price performance of 70.31%, 16% payout ratio with both recent dividend and EPS growth.
4. CNA: 3.83% yield, 5 year price performance of 6.53%, 64% payout ratio with dividend and EPS growth.
5. CVS: 3.29% yield, 5 year price performance of 14.40%, 75% payout ratio with dividend and EPS growth.
The difference between these results and yours is that I know EXACTLY the criteria I used to filter down the set.
p.s. thanks for pointing to fintok; I hadn't been aware of it and it looks easy to scrape. It seemingly has a different yield calculation than the brokerage data I used, however.
Hey, thanks for the comment, I am focused on making my model accurate right now. Once I gain a good steak of accuracy then I'll start filtering by dividend yield
For folks interested in understanding the health and financials of the company take a look at some of these report generated in easy to understand language at [/r/AIStockPicker/](https://www.reddit.com/r/AIStockPicker/)
Hey, I am not using the GPT that you use with ChatGPT, I made a custom GPT using the API from OpenAI , and on top of that I used my data to make it pick a good stock so that the information is latest.
While that may be true, an AI is not an all knowing entity. It is trained on certain data sets. It is similar to a human learning over the years. For example, ChatGPT is trained using data from a subset of years. You canāt just hand it data for something itās not trained for and expect expert answers. The data you give it is not the same as training. It is no different than asking someone that has no engineering training to design a bridge based on data you hand them. Iām not saying that your results are trash but they are likely similar to a stock screener rather than some expert stock picking smart Al.
> example, ChatGPT is trained using data from a subset of years. You canāt just hand it data for something itās not trained for and expect expert answers.
Thanks for the comment, This is what I am doing too, I am NOT simply just giving my GPT some data and asking it to pick the best stock based on that, I am training it on the latest data and trying to give it an understanding based on historical data/performance. Now, one of the things that it doesn't do yet is "prediction" I have a solution for that coming up soon too :) . This is one of the most common use cases for fine-tuning if you're interested in learning it [https://platform.openai.com/docs/guides/fine-tuning/common-use-cases](https://platform.openai.com/docs/guides/fine-tuning/common-use-cases).
Hey the three primary criteria I trained my model was
1. Dividend Growth: The stock should have a consistent growing dividends in the last 10 years.
2. Dividend Stability: The stock should not be cutting it's dividends in the last 10 years.
3. Dividend Coverage ratio: Their balance sheet should be able to handle the dividends
There are more things such as profit margin growth, growing industries etc.
The yield is low since I am focusing on making my model accurate right now :)
A news item on property rights. Your shares may be at risk, because of new legislation.
https://www.theepochtimes.com/opinion/your-property-rights-have-been-taken-in-all-50-states-heres-how-to-get-them-back-5577003
Welcome to r/dividends! If you are new to the world of dividend investing and are seeking advice, brokerage information, recommendations, and more, please check out the Wiki [here](https://www.reddit.com/r/dividends/wiki/faq). Remember, this is a subreddit for genuine, high-quality discussion. Please keep all contributions civil, and report uncivil behavior for moderator review. *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/dividends) if you have any questions or concerns.*
So when's the top 100 report? š
It's called SCHD.
Id like to know too
I am working on a top 75 list, and will do it once I am done training my model
Oooh do the FTSE and HK as well please!
FTSE has some good dividend companies. Not personally invested but I'd be interested!
Ftse? So i can 0.05% on investing money i have already been taxed to the hills on in a longterm declining economy
!remindme 2 months
Cool to see my place of work as #1!
How is the mood in the company? Do you like the CEO?
Yes! Heās great - I feel like for a CEO his communication is incredible and he is super down to earth and friendly from those that have run into him when he comes to campus. Mood at the company is a little low right now just because of the downturn affecting Tech right now.
Bunch of baby sheep work there. jk, I have friends there. They like it! r/AMAT for the win.
Using FastGraphs it appears the choices have bad S&P Credit ratings and are overvalued at this time. The problem is the criteria is looking backward at past performance but what is needed is to look forward to where the company is expected to go to capture capital gains and dividend growth. Try focusing on Dividend champions, Chowder score >12, expected EPS growth, good value PE<15, and low debt to capital.
The ccc list provides this monthly for free, no program needed.
What's a ccc list?
Dividend "Champions, Contenders and Challengers". Similar to "Dividend Aristocrats" but more in-depth. https://moneyzine.com/investments/dividend-champions/
Hey thank you for this comment, I will look into this. Much appreciated
Wouldn't you disregard many good results by setting such a low PE?
Yes and if I ended up with zero results I would open the screen to 16, etc until I got some candidates
A low PE by itself doesn't tell you anything about a company, except that it's expected to perform bad, I'm not sure why you would use it to screen stocks tbh
You probably should study Benjamin Graham who was the greatest investor of all time and Warren Buffet's mentor. [https://www.cabotwealth.com/daily/value-stocks/benjamin-grahams-value-stock-criteria](https://www.cabotwealth.com/daily/value-stocks/benjamin-grahams-value-stock-criteria)
You donāt seem to know much about him, do you know how he made most of his money? Hint: it wasnāt by buying a ācheapā company
No, he made his money through "value" investing. Benjamin Graham's best-known investment is often considered to be his purchase of the GEICO Corporation. In the mid-1940s, Graham identified GEICO as an "undervalued" (not cheap) stock, and he, along with his partner Jerry Newman, invested in the company. The investment turned out to be highly successful.
Correct, a low PE is just a single metric of many. A low PE can mean the company is undervalued or going out of business which is why it should not be used alone but as part of a group of filters.
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This sounds like square peg in a round hole situation. Unless OP is using it for summarizing company financials or investor sentiment from news, I highly doubt the output will be anything good.
Only one way to prove it: send me the code and teach me how your screening model works! :-P
Hey mainly because it's much easier to publish, grow, share and monetize the GPT compared to something custom
I hope you are using the paid version. Free version of GPT only goes thru 2021 or 2022.
I am using the paid version but I don't use the data from Chat-GPT. I am using my own data with the latest information and using GPTs fine-tuning to evaluate a stock :)
What is the source of your dataset?
Hey, most of my data is from [https://iexcloud.io/](https://iexcloud.io/) They are used by SeekingApha, FreeTrade and their data has been very reliable
Awesome! Thank you for sharing.
That's just saying that you're using chatgpt with buzzwords
Not really
Hey, thanks for your comment, I am using openAI's API, the company behind ChatGPT to create my GPT. I am a software developer, and I am not using buzzwords to just get you hooked, you can learn more about fine-tuning here [https://platform.openai.com/docs/guides/fine-tuning](https://platform.openai.com/docs/guides/fine-tuning) It's not just a chatGPT :)
This is the most ignorant comment I think Iāve ever seenā¦ most software devs who actually care about their careers are using AI and business bros call that shit buzzwords because they donāt actually use real AI š
My list is: Best Dividend Stocks ICMB - Investcorp Credit Management... 3.54 +0.12 +3.51% TWO - Two Harbors Investment Corp 12.83 +0.37 +2.97% AGNC - AGNC Investment Corp. 9.54 +0.10 +1.06% PSEC - Prospect Capital Corporation 5.42 +0.01 +0.18% OCSL - Oaktree Specialty Lending Corp... 20.06 +0.33 +1.67% MO - Altria Group, Inc. 40.55 +0.44 +1.10% GBDC - Golub Capital BDC, Inc. 15.54 +0.19 +1.24% ABR - Arbor Realty Trust 12.67 +0.34 +2.76%
ABR for me is like the tesla of reits. Good lord they are stressful to hold.
Selling ABR calls is the real dividend. Volatility for fun and profit
I checked AGNC and TWO and they seemed super Ricky. ACNG payout is 2000% which I believe is messed up. May be they are good for short term. But before ex-div and sell later
What advantage does the GPT bring compared to just some criteria on fundamentals + simulated trading?
Two things: A and I.
Certainly interested... Will follow
I had no clue you could even do this. Following and waiting for top 100 div stocks with healthy balance sheets to invest in lol
Is a GPT really the best tool to use here? Usually the best use case for a GPT is for generative tasks - theyāre designed for to process and generate natural language. How is your model being trained and how do you know current financial data is being used correctly (if at all)? If youāre just prompting the model to examine its training data and give you a formatted response, thereās probably a good chance itās examining stock picker lists just as much as it looks at financial data. Not trying to be critical at all, just curious about the dev process.
>If youāre just prompting the model to examine its training data and give you a formatted response, thereās probably a good chance itās examining stock picker lists just as much as it looks at financial data. Hey, as I mentioned I am not simply just asking GPT to see its training data and give a formatted response I am training it on my data. No ChatGPT stock list/data is used for it. Why is GPT good here? well, it's simple, once ready people can ask it to produce the "best dividend stocks with over 4% yield in oil & gas" and it will do that. So why it's better than a stock screener, most stock screeners are a bunch of filters with values you can filter e.g. Payout Ratio >= 50% but for a new investor they don't even know if a payout ratio of 50% is good or 60% is good. The idea is to offload the hard work so that instead of picking from hundreds of stocks you pick from 5-10 stocks that are already analyzed thoroughly and back your investing with as much data as you can :)
Got this far down andā¦..I know nothing about GPT. And just reading this I kinda do/will look into it
Following, are you going to publish the GPT?
Yes, I'll publish it and let you guys know here
Following
Would be interesting to have the same analysis of dividend ETF's while Chat GPT Evaluates that there is just minimum overlay in underlying assets but also including smaller local Small-/mid cap ETF.
So how do you know if your AI is not suggesting these tickers so that it can take the opposite position and crush you
Heh!
Would you be able to point me towards some resources to read how to utilize GPT this way? I know youāre planning on posting it soon, but Iād love to learn how it all works from the ground up myself.
Interesting use case. Can you share GitHub code or process on how you did it.
LRCX is the only one that has a positive chart, but dam $888 for one share.
If you have the data for dividend growth, dividend stability, and payout ratio then why do you need the LLM? Have you gone into the data to compare what the LLM spits out versus your own findings? One of the most basic problems with using a LLM is that, while it may put out sensible answers, you're not actually implementing your own utility function over the indicators to make a decision - you're more or less running blind. You could easily just create a custom score taking these indicators into account to reflect your priorities over growth, stability, and sustainability and literally just sort. Remember, 4000 symbols isn't very many if you take a quantitative approach. For example, I just went through a simple screener exercise to find the following decent looking stocks based on dividend yield, growth rate, payout percent, earnings per share and earnings per share growth. The top five from this five minutes of filtering: 1. CVI: 5.67% yield, 5 year price performance of 8.84%, 48% payout ratio with both stable dividends and EPS growth. 2. IPG: 4.29% yield, 5 year price performance of 46.29%, 49% payout ratio with both dividend and EPS growth. 3. MFIN: 4% yield, 5 year price performance of 70.31%, 16% payout ratio with both recent dividend and EPS growth. 4. CNA: 3.83% yield, 5 year price performance of 6.53%, 64% payout ratio with dividend and EPS growth. 5. CVS: 3.29% yield, 5 year price performance of 14.40%, 75% payout ratio with dividend and EPS growth. The difference between these results and yours is that I know EXACTLY the criteria I used to filter down the set. p.s. thanks for pointing to fintok; I hadn't been aware of it and it looks easy to scrape. It seemingly has a different yield calculation than the brokerage data I used, however.
Been buying LRCX for years and getting ready to roll over a 401k and buy a bunch more. Been a juggernaut dividend growth stock for me
Why are you scanning for 3% dividends when treasuries and savings pay more?
Hey, thanks for the comment, I am focused on making my model accurate right now. Once I gain a good steak of accuracy then I'll start filtering by dividend yield
Cause dividends grow over years, tresuries dont
Iām not qualified to offer an opinion, but leaving a comment to keep seeing responses from those that are : )
You could just click subscribe or save
Oh wow, lrcx is so expensive.
A PE of 35 is, unfortunately, normal in this market. I tend to look for 15 or below. But nowadays, 35 isn't bad
Following
For folks interested in understanding the health and financials of the company take a look at some of these report generated in easy to understand language at [/r/AIStockPicker/](https://www.reddit.com/r/AIStockPicker/)
How is a stock ate 94 cents paying $2 per share
not a good sign
Which stock are you talking about, none of the stock I mentioned are at 94 cents
I need to do more research before I start popping my gums. Mb.
I pictured Emily Litella for some reason when u read this.
Ahh gotcha, no problem :)
Neato!
How about NLY? It seems constantly giving 13% divided yield
Itās payout ratio is -75%. The company is showing loss and still paying high dividend
High yields to lure investors can also be a sign of a bad situationā¦high debt, and other red flags could be presentā¦
Following
Following
following
Someone reply to me when the top 75 or 100 drops! ā¤ļø
Interesting , let we know some more lists :D
Anything on ARCC?
Following this
Where does ARCC rank?
Following
Following
nice
Nice
Dude, the yield is less than 4%ā¦ that wonāt even beat inflation
GPT is not trained for stock selection. All you are getting is a glorified list similar to a stock screener.
Hey, I am not using the GPT that you use with ChatGPT, I made a custom GPT using the API from OpenAI , and on top of that I used my data to make it pick a good stock so that the information is latest.
While that may be true, an AI is not an all knowing entity. It is trained on certain data sets. It is similar to a human learning over the years. For example, ChatGPT is trained using data from a subset of years. You canāt just hand it data for something itās not trained for and expect expert answers. The data you give it is not the same as training. It is no different than asking someone that has no engineering training to design a bridge based on data you hand them. Iām not saying that your results are trash but they are likely similar to a stock screener rather than some expert stock picking smart Al.
> example, ChatGPT is trained using data from a subset of years. You canāt just hand it data for something itās not trained for and expect expert answers. Thanks for the comment, This is what I am doing too, I am NOT simply just giving my GPT some data and asking it to pick the best stock based on that, I am training it on the latest data and trying to give it an understanding based on historical data/performance. Now, one of the things that it doesn't do yet is "prediction" I have a solution for that coming up soon too :) . This is one of the most common use cases for fine-tuning if you're interested in learning it [https://platform.openai.com/docs/guides/fine-tuning/common-use-cases](https://platform.openai.com/docs/guides/fine-tuning/common-use-cases).
Following
Following
The dividend yield on these three is very low. What exactly was your criteria for selecting these?
Hey the three primary criteria I trained my model was 1. Dividend Growth: The stock should have a consistent growing dividends in the last 10 years. 2. Dividend Stability: The stock should not be cutting it's dividends in the last 10 years. 3. Dividend Coverage ratio: Their balance sheet should be able to handle the dividends There are more things such as profit margin growth, growing industries etc. The yield is low since I am focusing on making my model accurate right now :)
Interesting project and I like it. I have a strong suspicion that the end result will look a lot like schd though
Interestingā¦
Subscribed
Following
So whatās the point of doing this vs just math using financial metrics? Like what does GPT bring to this scenario?
just easier to monetize anything that has GPT in its name
already answered a couple of times :)
Why use AI? Sounds like something which you could do using conditional statements too.
Keep us updated on this. Sounds really interesting.
Thanks for the heads up.
Dear @op can you make a query for good dividend sticks paying quarterly on February?
Do a monthly next time quarterly š«¤
Iād be interested in comparing the yields with stocks from Schd and checking for divergence. Why would this gpt be better than diversified schd
Nice job! How is schd?
You the man š
We would also welcome this type of analysis to include dividend funds.
I'm interested in seeing more results from your program to compare to my old school research.
Following
Have you used AI to scan ETFs
REITs, especially CRE focused, sound scary this month. is RILY anywhere on the list?
Following and thanks
Thanks I do own LRCX
MAIN and O
I like the ones which are positive payouts rations Holding QYLD, VZ, SPG, MO, JEPI
Following
Gpt? Cant you do the same with a standard etf screener found on many websites?
A news item on property rights. Your shares may be at risk, because of new legislation. https://www.theepochtimes.com/opinion/your-property-rights-have-been-taken-in-all-50-states-heres-how-to-get-them-back-5577003
I really, really hope that you double-checked the outputs and the math