Hi, Shrewd!        Login  
Shrewd'm.com 
A merry & shrewd investing community
Best Of MIBest OfAll BoardsThe Shrewd’m WeeklyLearn to InvestHow to Become Shrewd
Search
Shrewd'm.com Merry shrewd investors
Search
Best Of MIBest OfAll BoardsThe Shrewd’m WeeklyLearn to InvestHow to Become Shrewd


The week's question
In December 2024, in the thread "Re: BRK: Why Not XOM?", BreckHutHigh asked the members: "What about the long road trips with kids?" This week it is put to everyone again. The button below opens the small thread re-asking it - read what others have said so far, then give your own answer as an ordinary reply.
Answer this questionContinue to Shrewd'mThis note won't appear again
Investment Strategies / Mechanical Investing
Unthreaded | Threaded | Whole Thread (5) |
Author: tedthedog   😊 😞
Number: of 6131 
Subject: Re: ML for MI question
Date: 07/31/24 9:45 AM
Post New | Post Reply | Report Post | Recommend It!
No. of Recommendations: 1
Thank you for that list!
I'm glad someone did it, i.e. throwing all the random forests, neural net, new stuff against trying to predict stock returns from fundamentals, "Empirical Asset Pricing via Machine Learning" paper:
SSRN: Research paper
But IMHO, the goal seems a little mis-guided.

The LLM stock screen is amusing.
But I wasn't thinking of asking an existing LLM to provide a stock screen, but to train an "AI" to identify "dog" stocks from e.g. "cheetah" stocks.

This is just blue-skying:

I spent a couple of minute online, so no doubt there's something better I missed, but this one at least exemplifies a ML framework that one can fairly easily train on one's own data
developer.apple.com - Create ml

An amusing story of a guy using the above Apple thingy to identify his cat, using his rather small "database" of pics of his own cat, from a bunch of online cat pics
linkedin.com - Finding my feline friend machine learning tale cats codes plachta

An initial thought is to translate all finanical data such as P/B ratios etc into categories e.g. "very low, low, medium, medium high, high" because LLMs aren't great with numbers/arithmetic. This
should be carefully done because e.g. certain sectors tend to have low P/B while others high, etc, so a little thought put into the categorization could be useful.
After translating numbers into categories, then can use text AI's.

With the Apple one, or something similar, could use its "text classification" mode, "word tagging" mode, or "tabular" mode. In classification mode: instead of "great movie" or "bad movie" from reading reviews it'd output "great investment" or "bad investment" from reading (categorized) fundamentals etc. In "word tagging" mode: instead of "iphone" it'd tag "good investment", etc.

Cats from dogs?
zdnet.com - What does AI know of cats and dogs maybe very little
I'm not sure you'd want to fake an existing purpose-built image classifier into doing the finance problem, but maybe one could try. Instead, you might have much better success if build your own AI using some tool like the Apple one to identify, from financial features, the dog stocks from cheetah stocks.

Post New | Post Reply | Report Post | Recommend It!
Print the post
Members reply directly to tedthedog here — and replies get answered. Reading is free; so is joining the conversation. Join Shrewd'm »
This community has written 6,115 posts about Mechanical Investing. The article-length ones it recommended most:
Dividend investing · 52 recs · 2025
Non-Mag7 screen · 34 recs · 2025
OT - Div yields and returns · 32 recs · 2024
Using AI to generate backtesting programs · 30 recs · 2025
Rankings for 19Dec2022 · 29 recs · 2022
Unthreaded | Threaded | Whole Thread (5) |


Announcements
Mechanical Investing FAQ
Contact Shrewd'm
Contact the developer of these message boards.

Best Of MI | Best Of | Favourites & Replies | All Boards | Followed Shrewds | Open Questions | Moving a community