Detecting SPY bottom phases with AI
Important note upfront:
This is not a buy/sell signal, not financial advice, and definitely not a “the AI predicts the market perfectly” tool. It is more of a regime score that is calculated daily after market close and checks whether the current market environment resembles historical bottom phases.
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Hi everyone,
Over the past few months, I built an AI-based dashboard that is meant to help me time my stock and ETF purchases a bit better.
The model was trained on data from January 1, 2000 to January 1, 2020. Everything from 2020 onward was never seen by the model and is used as the test period to understand how the model reacts to unseen data.
It is far from perfect, but if there is interest, I can make it available for free.
This is the AI’s performance so far. Every day after market close, the AI calculates a score/probability, and based on that, it indicates whether the current environment may be a potentially good entry point.
I would like to know whether there is interest in this, and secondly, what you would like to see.
Would you prefer a simple version like the current one, or would you want specific features or metrics?
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How does the SPY regime model work?
The model does not predict the future.
It looks at the current SPY market environment and compares it with historical periods that later turned into strong recovery phases. Based on that comparison, it calculates a daily regime score after market close.
A high score does not mean “buy now.”
It means: the current setup looks similar to previous market-bottom or recovery environments.
The model was trained only on data from 2000 to 2020. Everything from 2020 onward was not used for training, so the post-2020 results are used as an out-of-sample test.
I also show the bad signals, not only the good ones. Some signals were early or wrong, and that is important to see. The goal is not to create a perfect trading system, but a transparent tool that can help with timing long-term ETF or stock purchases.
In simple terms:
- It runs once per day after market close
- It analyzes the current SPY market regime
- It compares today’s setup with past bottom/recovery phases
- It outputs a score
The main idea is:
Instead of trying to predict tomorrow’s price, the model tries to identify when market conditions look historically similar to previous attractive entry zones.
