2 Commits

Include renames

Author	SHA1	Message	Date
mathiasandClaude Sonnet 4.6	caccd1aa7b	feat(features): add hl_range + ret_intrabar OHLCV features (4-channel input) ... - prepare_hourly.py: keep O/H/L columns from M1 zips; compute per-hour hl_range=log(H/L) and ret_intrabar=log(close/open); backward-compat (falls back to 4-col output only when O/H/L present in input) - train.py build(): auto-detect extra features from parquet columns (FEAT_COLS = [ret, realized_vol] + [hl_range, ret_intrabar] if present) - 5 new tests (9 total in test_prepare_hourly); 24/24 pass Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-06-26 13:11:59 +02:00
mathiasandClaude Sonnet 4.6	e31905dc43	feat(data): EUR/USD hourly pipeline + 2008-2023 M1 dataset (#2) ... - scripts/prepare_hourly.py: M1→hourly aggregation (realized_vol = sqrt(Σr²), MIN_BARS=30 threshold, no weekend rows, year-based split preserved) - tests/test_prepare_hourly.py: 5 TDD tests, all green - train.py: USE_HOURLY=True, WINDOW=240 (10-day), PATCH_LEN=24 (1-day patches); build() prefers eurusd_hourly.parquet, falls back to daily; EXPORT BLOCK updated - Taskfile.yml: data:fetch:historical, data:prepare:hourly, data:prepare:all, data:test - 98,591 hourly rows (2008-2023) covering GFC, Euro crisis, Brexit, COVID, Fed cycle Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-06-25 13:12:48 +02:00