Models are now a Composite of drift, volatility and (optional) shape
components, so an experiment can swap one part against a fixed control.
btcmodel/experiments.py holds seven experiments built from the ideas in the
old branches (catalogued in docs/2024-ideas.md), each with its hypothesis
and source, and a verdict rule fixed before anything ran. `just ab` runs
them on development data. Results:
- Shrinking the cycle drift, and a power-law trend (plain or reverting),
beat their controls. The power law beats the random walk by 53-63% at
3-4 years with unbiased outcomes, so it is promoted to MODELS.
- Every alternative volatility estimate (EWMA blends, other windows,
reversion to a level or trend) is worse than the trailing 365-day window.
Cycle-dependent volatility, heavy tails and stretched cycle phase show no
reliable effect.
sam
b0243adf61
