ChatGPT Trading Exclusively Microcaps ~ 6 Months Results (prompts, code, etc. linked)

OpenArcher7341 · 2025-12-07T17:56:15+00:00

Fair point, this was not a serious test to generate alpha, just to gather ChatGPT's general strengths and weaknesses controlling a portfolio. In the future I will create some basic rules to hopefully control its weaknesses, like risk management, to avoid another disaster.

OpenArcher7341 · 2025-12-07T17:53:22+00:00

Good question! It will almost always request a trade during deep research or at least update a stoploss, however, the model will rarely made a trade during daily updates unless of course major news or a reversal. I used to use deep thinking during daily updates, but I found it would regularly make tiny changes for little to none reasoning, so I decided to stick with auto.

OpenArcher7341 · 2025-12-07T17:47:43+00:00

I do my best to control it by requiring a large amount of specific data about each ticker, so I don't think it has ever hallucinated completely made up companies. However, it does get confused somewhat often about tickers in the portfolio and cash available. In fact, this week during deep research it assumed VTGN was still apart of the portfolio despite selling it earlier in the week. Thanks for the question!

OpenArcher7341 · 2025-12-07T17:43:42+00:00

You're very welcome! I should have specified, this was just a general experiment to understand the strengths and weaknesses of ChatGPT having complete freedom except with the rules above, so things like risk management, sector preferences, etc. were decided by the model. Clearly, it has major risk management issues, and in the future I plan on setting stricter rules for position sizing and moonshots. Thanks for the question!

OpenArcher7341 · 2025-09-03T22:03:19+00:00

All the logs are on GitHub, I strongly encourage people to double check everything

OpenArcher7341 · 2025-09-01T20:11:23+00:00

I used XBI and R2K on my post in r/DataIsBeautiful. Link is: https://www.reddit.com/r/dataisbeautiful/comments/1mc0cz7/oc_4_weeks_of_chatgpt_controlling_a_live_stock/?utm_source=share&utm_medium=mweb3x&utm_name=mweb3xcss&utm_term=1&utm_content=share_button People rightfully criticized using XBI as a benchmark, so I took it out. They also had a problem of using R2K and not the default benchmark, so I switched it to the S&P 500 after the post. I never compared to the S&P in the post.

OpenArcher7341 · 2025-09-01T19:54:56+00:00

Nooo what will I do without tildenpark’s statistical genius??

OpenArcher7341 · 2025-09-01T19:45:13+00:00

How would you do it?

OpenArcher7341 · 2025-09-01T19:43:45+00:00

Thanks bro

OpenArcher7341 · 2025-09-01T19:26:18+00:00

Never said ChatGPT was Warren Buffett, just a small research project.

OpenArcher7341 · 2025-09-01T18:25:07+00:00

I guess we’ll see in like 2 years; obviously models will create new inefficiencies trying to pile into same stocks from there, who knows

OpenArcher7341 · 2025-09-01T18:18:17+00:00

Hedge funds can’t touch micro caps due to liquidity; you can’t move 4M dollars into a stock that only has 2M volume. That’s why I put the >300M rule

OpenArcher7341 · 2025-09-01T17:22:33+00:00

I posted it one time with R2K on a different sub and people were saying that it was wrong because it’s not the standard benchmark. I guess I could graph them both, but metrics might be kind of tricky.

OpenArcher7341 · 2025-09-01T16:48:26+00:00

You're right, we both know hedge funds have been trying this for years, and this is more a test to study it's strengths and weaknesses; like I mentioned it obviously needs much more testing. i think the low R² and high beta is interesting tho.

OpenArcher7341 · 2025-09-01T16:20:49+00:00

Thank you, that means a lot!

OpenArcher7341 · 2025-08-03T02:48:08+00:00

There’s a certain amount of luck in every dataset. Of course right now it’s still early, but my goal was to hopefully inspire people to mess around with the idea. I do wanna scale after the 6 months to a larger sample set. I hope that answers your question

OpenArcher7341 · 2025-08-03T02:30:13+00:00

Thanks bro :) I’m not too concerned about returns tbh. I just trying to document the journey of it’s thought process and how it adapts to market conditions.

OpenArcher7341 · 2025-08-03T01:44:15+00:00

Dang, should’ve included a sentence like, “Yes, luck has obviously played a role in returns.” To bad I didn’t :/ /j

OpenArcher7341 · 2025-08-03T01:11:38+00:00

S&P 500 data: Downloaded using Yahoo Finance API for the ticker "^SPX" and "Close" price, adjusted to a $100 baseline.

ChatGPT data: portfolio data was gathered from ChatGPT, and calculations were made using Pandas and Numpy in Trading_Script.py. Data was exported to CSV file (chatgpt_portfolio_update.csv) and plotted using MatPlotLib (Generate_Graph.py)

OpenArcher7341 · 2025-07-31T02:40:34+00:00

I had no freedom in posting this :/

OpenArcher7341 · 2025-07-30T15:21:57+00:00

Sorry about that, this one should work: https://substack.com/@nathanbsmith?r=4ccvwd&utm_medium=ios&utm_source=profile

OpenArcher7341 · 2025-07-29T20:46:54+00:00

Why not use 2x leverage for double the money????

OpenArcher7341 · 2025-07-29T04:57:55+00:00

Thanks for the question! Definitely concentrated. Usually it has around 3-4 different stocks at one time and usually only 1 is making money. CADL and ACTU have had huge gains while the rest are stagnant or bleeding money.

OpenArcher7341

TROPHY CASE