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research: factor census on the current panel; key the factor-rank cache to the panel

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factor_census measures all 86 lab factors one way on the post-Tiingo PIT
S&P 500 panel (IC, quintile spread, top-20 alpha vs EW). One class A
(low_svr21, 2018+), two class B (accruals, rev_5), 69 N, no |t| >= 3.
Momentum and overnight_mom have no quintile spread; the house edge sits
in the top 10. --part construction compares the live construction.

rotation.factor_ranks reused ranks_us.pkl regardless of the panel. The
cache predated the Tiingo merge (643 of 787 columns), so callers silently
dropped the backfilled delisted names. The cache now carries a key file
(panel calendar, tickers, membership, factors.py hash) and is rebuilt
when it does not match.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
Gahow Wang
2026-10-12 07:14:42 -07:00
parent ed0ed3f4b2
commit 81f4e3b32c
3 changed files with 396 additions and 4 deletions
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@@ -108,6 +108,7 @@ PYTHONPATH=. uv run python -m research.lab.daytime_reversal # buy the S&
PYTHONPATH=. uv run python -m research.lab.overnight_midsmall # the overnight-only momentum book on S&P 400/600 (preregistered; STOP 2026-10-09: 0.93 net at 3 bp/side, corr 0.83 with the S&P 500 book)
PYTHONPATH=. uv run --with numba python -m research.lab.dip_buying # buy-the-dip: SPY/QQQ RSI(2), trend-filtered stock RSI(2), drawdown tables (preregistered; STOP 2026-10-12: SPY 46 bp/trade t 3.4 but 14% of days, 3x Sharpe 0.57 = SPY; stocks breakeven 10 bp/side)
PYTHONPATH=. uv run python -m research.lab.dip_leverage_overlay # +1x SPY only inside SPY RSI(2) dip windows, on the overnight_book books (preregistered; STOP 2026-10-12: Sharpe 0.98->0.99 / 1.38->1.33, placebo rank 77-88%; the books already earn the bounce at ~2x SPY beta)
PYTHONPATH=. uv run --with numba python -m research.lab.factor_census [--part construction] # every lab factor (price, EDGAR, insider, Lazy Prices, EAR, SVR, FTD) measured one way on the current PIT panel: IC, quintile spread, top-20 alpha vs EW (2026-10-12: 1 A low_svr21, 2 B accruals/rev_5, 69 N; no |t|>=3)
uv run python -m research.lab.fetch_us_fundamentals --universe mid # EDGAR PIT facts for S&P 400 ever-members (name-checked CIKs)
uv run python -m research.lab.fetch_us_fundamentals --universe small # the same for S&P 600 (IJR)
PYTHONPATH=. uv run python -m research.lab.midcap_sleeve [--only h1..h4] [--universe small] # S&P 400 sleeves vs IJH; S&P 600 replication vs IJR (all REJECT 2026-10-08)