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.
Replace the 2024 model (model.py, ~2000 lines) with the btcmodel package, the
baseline for future work:
- Forecasts are quantiles of log price at each horizon, scored with CRPS in a
walk-forward backtest (origins every 30 days from 2014, horizons 1 month to
4 years). Skill is relative to a zero-drift random walk, with circular
block-bootstrap intervals and a count of independent windows.
- Development data stops at 2024-11-26, the last day the 2024 model saw.
Later outcomes are a holdout, scored only by `backtest --holdout`.
- Models: random_walk, drift_rw, and cycle (the 2024 model's cycle-position
drift, now kernel-smoothed and recency-weighted). On development data
nothing beats the random walk with confidence; cycle loses at every horizon.
- Prices: the Investing.com archive moves to data/ (cut at 2024-11-26; its
last row was intraday) and is extended with Coinbase daily closes by
`update`.
Also: Nix flake dev shell (Python 3.13, pandas 3), ruff in place of black,
pytest suite, and a rewritten README. NOTES.md is removed as inaccurate, and
poetry is dropped.
sam