yeah most stock ranking strategies, evaluation tools, etc lose to the index. why wouldn't yours? you should have had some reason to believe otherwise to work on this
You're right: I blindly thought I could find a correlation between good fundamentals and historical returns. Since 2024 I've been working in that as a side project. Like, I pivoted the "features" of the web app a LOT of times.. Adjustable weights, added and removed Net Deb/ Ebtida from the score, etc.
The core feeling and reason for me is that I never found a good screener for common people to understand what is a good company to invest. People usually follow hype news and just bet in the stock market. I wanted to create a tool to fight against that.
And only recently, when I was about to launch my website I got AI to review it and noticed the point-in-time bias. :grimmacing:
What do you mean write your own HN posts? (This is my second post)
Your top level comment is also AI which is against the HN guidelines. Also it is allowed to post your own works, but they should only be a small fraction of your submissions. Please do not use HackerNews primarily for self promotion.
> Don't post generated text or AI-edited text. HN is for conversation between humans.
from the guidelines. Your blog and other comment here look very AI edited at least, although if I'm wrong I apologize.
as for the idea in general - past performance and therefore fundamentals are pretty well known to not be predictive for stocks, and public fundamentals usually aren't good enough information to trade on. You want some specific industry knowledge, right? if you could expose that maybe you could give some advice about trends. But I think you should probably just encourage people not to hold or trade non index funds.
Thanks for been strong about your opinion and also for asking apologies in advance in case you are wrong. (which you guys are) :D
I'm not writing using AI. I'm just focusing in this side project for the last 2 years. It's right now my main side-project to transform a hobby in, maybe, a revenue source... So, I've been polishing and reviewing that article a dozen times since the beginning of this month. It has a LOT of iterations with friends on missing Data Analysis arguments and bad english.
Thank you also for your topic comment: That's kind of my direction now. I want to improve the tool to focus in helping people see that a business is not a ticker and a chart. They're about knowing the forces of revenue, net income, controlling cash and debt.
I just wanted to start with a feature that could easily compare my screener to others, so I build the rankings on Fundamental Data (and also Historical return).
My idea is to bring more features in the quality side of analysis: Michael Porter's 5 forces, SWAT table, release earnings comments, etc.
I am no finance expert but everything I have seen in the last 5-8 years is that "a correlation between good fundamentals and historical returns." have noting to do with stock valuations any more.
I agree with you. That article is like a memo to a tactic that I was following and drove me in the wrong direction of force-trying that correlation (as a predictive tool).
I'm not a finance expert also, but I could learn over the years the (not quantitative truth) that fundamental analysis at least is more reliable than buy moment or day-trading. Right?
So, my conclusion is in line to what you mentioned: The ranking tool I build (and tried to sell as a predictive tool) also fails in that plan. It's actually just too enought to separete the gems from the rubble to help a little bit the investor who wants to consider fundamental analysis...
Yes, it's the reading equivalent of walking over gravel barefoot. The model didn't even help OP understand this thing which most investors learn pretty darn early.
I'm curious what happens if instead of picking the winners, you try to exclude the losers. Cut anything whose fundamentals put them below your coin flip line, keep the rest. If your result that good fundamentals are necessary but not sufficient is correct, then excluding bad fundamentals should beat the index.
Yeah.. After I run the correlation over the full stocks of a window I noticed that maybe that could be a good path. I just didn't wanted to keep digging things and put in this article. It would be a never endless battle to "justify" my stock rankings. Right?
But Consider It done. I'll definitely check my data and see how horrible fundamentals, high debt and other bad things could help us.
One drawback I'm still trying to thing about is the problem with the Cyclical companies. If I take the data as I did before, cyclical usually would rank bad (and they do in my current ranking). So, I'm still thinking how that will distort the data.
also can you write up your own hn posts please
You're right: I blindly thought I could find a correlation between good fundamentals and historical returns. Since 2024 I've been working in that as a side project. Like, I pivoted the "features" of the web app a LOT of times.. Adjustable weights, added and removed Net Deb/ Ebtida from the score, etc.
The core feeling and reason for me is that I never found a good screener for common people to understand what is a good company to invest. People usually follow hype news and just bet in the stock market. I wanted to create a tool to fight against that.
And only recently, when I was about to launch my website I got AI to review it and noticed the point-in-time bias. :grimmacing:
What do you mean write your own HN posts? (This is my second post)
Your top level comment is also AI which is against the HN guidelines. Also it is allowed to post your own works, but they should only be a small fraction of your submissions. Please do not use HackerNews primarily for self promotion.
I suggest you read the guidelines: https://news.ycombinator.com/newsguidelines.html
from the guidelines. Your blog and other comment here look very AI edited at least, although if I'm wrong I apologize.
as for the idea in general - past performance and therefore fundamentals are pretty well known to not be predictive for stocks, and public fundamentals usually aren't good enough information to trade on. You want some specific industry knowledge, right? if you could expose that maybe you could give some advice about trends. But I think you should probably just encourage people not to hold or trade non index funds.
I'm not writing using AI. I'm just focusing in this side project for the last 2 years. It's right now my main side-project to transform a hobby in, maybe, a revenue source... So, I've been polishing and reviewing that article a dozen times since the beginning of this month. It has a LOT of iterations with friends on missing Data Analysis arguments and bad english.
Thank you also for your topic comment: That's kind of my direction now. I want to improve the tool to focus in helping people see that a business is not a ticker and a chart. They're about knowing the forces of revenue, net income, controlling cash and debt.
I just wanted to start with a feature that could easily compare my screener to others, so I build the rankings on Fundamental Data (and also Historical return).
My idea is to bring more features in the quality side of analysis: Michael Porter's 5 forces, SWAT table, release earnings comments, etc.
I'm not a finance expert also, but I could learn over the years the (not quantitative truth) that fundamental analysis at least is more reliable than buy moment or day-trading. Right?
So, my conclusion is in line to what you mentioned: The ranking tool I build (and tried to sell as a predictive tool) also fails in that plan. It's actually just too enought to separete the gems from the rubble to help a little bit the investor who wants to consider fundamental analysis...
Yeah.. After I run the correlation over the full stocks of a window I noticed that maybe that could be a good path. I just didn't wanted to keep digging things and put in this article. It would be a never endless battle to "justify" my stock rankings. Right?
But Consider It done. I'll definitely check my data and see how horrible fundamentals, high debt and other bad things could help us.
One drawback I'm still trying to thing about is the problem with the Cyclical companies. If I take the data as I did before, cyclical usually would rank bad (and they do in my current ranking). So, I'm still thinking how that will distort the data.