Digging through 38 days of live AI forecast data to find the unexpected

Digging through 38 days of live AI forecast data to find the unexpected

I created a dataset which contains forecast data which therefore can't be created retrospectively.

For ~38 days, a cronjob generated daily forecasts:

- 10-day horizons

- ~30 predictions/day (different stocks across multiple sectors)

- Fixed prompt and parameters

Each run logs:

- Predicted price

- Natural-language rationale

- Sentiment

- Self-reported confidence

I used stock predictions as the forecast subject, but this is not a trading system or financial advice, it's an EXPERIMENT!

Even though currently I didn't find something mind-blowing, visualizing the data reveals patterns I find interesting.

Currently, I just plotted trend, model bias, and ECE - more will come soon.

Maybe you also find it interesting.

The dataset isn't quite big, so I'm actually building a second one which is bigger with the Gemini Flash and Gemini Flash-Lite model.

PS: If you are interested in the dataset or the MVP with a dashboard to crawl data quickly, just mention it in the comments.

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