Forecasting where there is almost no structure
Most financial time series are noise.
No trend. No seasonality. Weak repeatability.
The best baseline is a random walk.
Any discovered pattern disappears as soon as it becomes part of the market.
What still works
Structure is scarce — but signal can be layered.
Statistics captures basic forms.
ML captures weak dependencies.
AI captures hidden links in text and context.
Crowd forecasting captures human information.
Each layer is weak on its own.
Together — they reach the maximum feasible.
The main idea
statistics → ML → AI → crowd forecasts
This is not a way to “beat the market.”
It is a way to extract everything the market allows.
The signal will be small.
Unstable.
Short‑lived.
But even a small improvement,
applied consistently, outperforms randomness.
— S. Praevis