Chronological record of decisions, findings and negative results. The point of this file: every number in the README has a paper trail, and every choice that could have been a degree of freedom is written down.
pct_change through zero produces sign-flipped garbage (−306%, then −127%
the next day). Policy: spike/nonpositive prints are NaN'd (both return legs
die) by quark.data.quality.clean_panel and documented here. We do not
clip silently.min_periods = horizon, any forward-return window containing a holiday was
silently NaN — ~10% of 5-day windows and ~90% of 21-day windows discarded.
Diagnosed because factor-IC sample counts collapsed (n=44 months where ~190
expected). Fix: tolerate ≤2 missing bars inside the window (a closed market
contributes zero return; the move lands in the next bar), and mask targets
where the instrument itself did not trade. Lesson: count your samples,
not just your means.(Numbers below updated 2026-07-15 to the committed post-audit artifacts — the original 43-instrument run was superseded when the universe grew to 82 instruments (78 headline after excluding the 4 hindsight-picked mega-caps) and the cross-gap returns fix landed; earlier vintages of this section quoted tsmom_252/DSR 0.29/AUC 0.513/Sharpe −0.71 from the smaller universe.)
The past-trades review surfaced that the top-3-by-|p−0.5| picks lost −117 bps/call (hit 37%) over the trailing 52 weeks, while the full decile book stayed positive. Investigated on the full 156-week walk-forward record with four pre-declared selection rules, all reported, trial-counted:
| Rule | avg bps/call | hit | t |
|---|---|---|---|
| Production: floating top-3 by |p−0.5| | −32.4 | 44.9% | −1.2 |
| A: fixed 2L+1S by prob | +27.8 | 51.5% | +0.99 |
| B: top-3 longs by prob | +9.1 | 48.7% | +0.34 |
| C: longs ranked 5–7 (off the tail) | +32.0 | 52.4% | +1.18 |
| D: random-3 in 90–97th pct band | +17.0 | 52.6% | +0.82 |
Five variants examined, all reported. The production rule was the outlier: by ranking on |p−0.5| it let the short tail dominate selection (83 shorts vs 70 longs in the trailing year) — precisely the side the original backtest showed carries no alpha. Adopted: fixed 2 longs + 1 short. Justification is twofold and ordered: (1) the pre-registered long-side-driven finding from Study 2, (2) a PAIRED comparison on the same 156 weeks: +60.2 bps/week improvement, t=+2.06. Rules B–D are not separable from A and were not adopted. The review page contextualizes any display window against the full record automatically, so a single bad year can't drive rule churn again.
The desk gained a horizon setting: 1D / 1W / 3M / 6M / 2Y, each a separately
retrained cross-sectional model (same features, label = beat-the-median over
h days; training labels always end h days before today, so causality holds
at every horizon). Trial accounting: the four new horizons are four new
trials. Each was walk-forward validated once (scripts/validate_horizons.py)
with purge scaled to the horizon and scoring at a non-overlapping cadence
(h/5 weeks); results live in reports/xsec_horizons.csv and are quoted next
to each horizon's picks in the UI. 1W remains the desk default: it has the
longest validation, the live ledger history, and the graded record. Live
predictions for ALL horizons are recorded daily (ledger horizon column),
so per-horizon live ICs accrue with time — long horizons will take months
to score their first entries, which the UI should treat as "unproven", not
"clean".
Two independent review passes re-derived every formula. Confirmed correct: PSR/DSR (exact Bailey–LdP forms, Monte-Carlo verified), expected-max-Sharpe, CAGR/Sharpe/max-DD, vol targeting, cost timing, engine causality, forward-return alignment, positional purge arithmetic, Spearman IC, %B/MACD/VWAP, VaR z and time-scaling, blend-search vol targeting.
Found and fixed (all with regression tests):
1. CRITICAL — cross-gap return deletion. pct_change(fill_method=None)
NaN'd the bar AFTER every gap, deleting each post-holiday move from
labels AND backtest PnL (~9/instrument/yr, biases toward zero). Fixed:
returns = ffilled-denominator pct_change masked to observed bars. All
headline numbers recomputed under the fix.
2. Sortino used std of negative returns about their own mean; now standard
target downside deviation (MAR=0, all obs).
3. ann_turnover/cost_drag_ann were per-instrument sums next to
portfolio-unit stats (~n_alive x overstated); now divided consistently.
4. Half-Kelly growth mislabeled as S²/4; correct is 3S²/8 (2.5%/yr at
S=0.26); full Kelly S²/2 (3.4%/yr).
5. "Compounding weekly" label on an arithmetic cumsum; relabeled.
6. Horizon-validation cadences were calendar weeks (~4.83 td): 2Y windows
overlapped 100% (~19 td). Cadences re-sized (14/28/110 wks), re-run.
7. Missing-sleeve history in the portfolio replay was implicit 0%-return
cash (aggressive was ~97% invested pre-2014); weights now renormalize
over available sleeves, sleeves enter at inception; drawdowns now see a
decline that starts on day one (baseline-1.0 peak).
8. Golden-cross NaN counted as bearish for short-history names; now skipped.
9. RSI labeled as Cutler's variant (differs from Wilder's by up to ~20 pts);
flat-window RSI now 50, not 100. Missing cost rates now raise instead of
trading free. Ledger logs unscoreable (delisted) names per scoring date —
the backfilled IC history is survivorship-tilted and should be read as an
upper bound (current-members universe; see Study 2 caveat).
Turnover was the binding constraint on Study 2 (67.9x/yr, 340 bps/yr cost
drag at weekly re-formation). Hysteresis variants: ENTER unchanged (extreme
decile), EXIT only once the name's rank decays past a gap. Trial
accounting: 3 exit gaps (0.15 / 0.20 / 0.30) pre-registered before results;
all reported; nothing else tried. All variants score the SAME stored
walk-forward predictions (one model fit), so differences are the weight
rule, not refit noise. Script: scripts/run_turnover_study.py →
reports/turnover_study.csv.
| variant | net Sharpe | ann turnover | cost drag | avg names |
|---|---|---|---|---|
| weekly re-formation (base) | 0.04 | 67.9x | 340 bps/yr | 93 |
| band, exit gap 0.15 | 0.13 | 47.1x | 236 bps/yr | 124 |
| band, exit gap 0.20 | 0.17 | 42.5x | 212 bps/yr | 134 |
| band, exit gap 0.30 | 0.18 | 34.6x | 173 bps/yr | 157 |
(Turnover/cost figures are annualized over the OOS window the strategy actually trades in — an earlier vintage divided by the full 2005+ panel length, understating both by ~1.48x; audit-found, fixed.)
Read: monotone improvement with band width — cost saved exceeds signal staleness cost throughout the registered range, and max drawdown falls too (−23% → −18%). The widest band converges toward the monthly-rebalance result (Sharpe 0.26) by a different mechanism (hold longer vs trade less often). Honest caveats: (1) still thin economics on a survivorship-biased universe — a turnover result, not an alpha result; (2) the registration is not git-verifiable — the gap list and the results entered the repo in the same commit, so it rests on the author's word; treat the MONOTONE PATTERN across all three gaps (0.13 / 0.17 / 0.18), not the best single number, as the evidence. Quoting only the 0.18 would be selecting the max of 3 trials.
Built from Wikipedia's constituent-changes table walked backward from
today's 503 members (scripts/build_pit_universe.py →
reports/pit_membership.csv: month-end snapshots 2005+, 845 ever-member
names). Two stated gaps, direction of bias known:
reports/pit_recovery_report.csv).
The unrecovered 189 skew toward the worst outcomes (bankruptcy,
distressed acquisition) — exactly the names survivorship bias deletes —
so even the PIT run remains optimistic. It bounds the bias; it does not
eliminate it.Comparison run (scripts/run_pit_study.py, identical pipeline, membership
mask ANDed into eligibility; results in reports/pit_study.csv):
| IC | IC t | D10−D1 gross | net Sharpe (weekly) | names/wk | |
|---|---|---|---|---|---|
| current members (shipped) | +0.0164 | 3.19 | 16 bps | +0.04 | 471 |
| point-in-time (best-effort) | +0.0127 | 2.38 | 10 bps | −0.19 | 438 |
(Vintage note: the current-members baseline here — IC +0.0164, t=3.19, n=757 — differs slightly from the headline +0.0172/t=3.35/n=756 because the DB gained a week of data between runs; same code, same config. Deltas between rows of the same run are the meaningful comparison.)
Read: the signal survives point-in-time treatment — the bias does not. Cross-sectional predictability remains statistically real (t=2.38 on 757 weeks) but ~23% weaker, the decile spread drops ~40%, and the weekly-rebalance net economics go negative: survivorship was carrying them. The honest claim after this study is "genuine but modest cross-sectional predictive power; net profitability requires the turnover discipline above AND is still overstated by residual survivorship in the 45%-recovered PIT panel." Headline IC in the README keeps the shipped config for continuity with the live ledger, with this study linked as the bias measurement.
Motivated by a verified literature review (reports/deep_research_net_alpha_
2026-07-22.md): cost-aware construction — trading a fraction tau toward the
target book each rebalance instead of full re-formation — is the documented
net-of-cost lever (+~0.2 net Sharpe, GP 2013); ex-post band overlays alone
documented NOT to rescue ML signals. partial_rebalance_weights() added to
quark/ml/xsec.py.
Cycle 1 (scripts/run_partial_rebal.py, current-members panel, pre-registered tau grid, all reported):
| tau | 1.00 | 0.50 | 0.25 | 0.15 | 0.10 | 0.05 |
|---|---|---|---|---|---|---|
| net Sharpe | 0.06 | 0.23 | 0.37 | 0.45 | 0.48 | 0.50 |
| turnover x/yr | 68 | 36 | 18 | 11 | 7 | 3.4 |
Monotone in tau — mechanism real on this panel.
Cycle 2 (scripts/run_cycle2_pit_partial.py, best-effort PIT panel, 656 recovered names, pre-registered: weekly taus {1, .25, .10, .05}, monthly h21 taus {1, .5, .25}):
| config | net Sharpe |
|---|---|
| weekly tau=1.00 | −0.13 |
| weekly tau=0.25 | +0.10 (peak; hump-shaped, decays at slower tau) |
| weekly tau=0.05 | −0.03 |
| monthly h21, any tau | ~0.01, IC −0.0000 (t=−0.00, n=188) |
Read: (1) The GP lever delivers almost exactly the literature's promised +0.2 Sharpe on the honest panel (−0.13 → +0.10) — but the honest starting point is negative, so the ceiling is ~0.1, not cycle 1's 0.50. Survivorship was carrying most of the cycle-1 miracle (consistent with the 2026-07-15 PIT study). (2) The monthly h=21 signal is ENTIRELY survivorship on the PIT panel: IC exactly ~0. The shipped monthly net Sharpe 0.26 should be read as bias, not edge. (3) Slow tau dilutes a fast-decaying thin signal — the tau optimum shifts from 0.05 (biased panel) to ~0.25 (honest panel), which is itself evidence the persistent signal component is weaker than the biased panel suggested. Conclusion: cost side is now optimized; the binding constraint is GROSS signal on the honest universe (9.5 bps/wk spread). Next lever must be new information: earnings-family features (PEAD, revisions) via Finnhub now, IBES/Compustat when WRDS clears. Trial count this session: 6 (cycle 1) + 7 (cycle 2), all reported here.
Added sue_recent (Bernard-Thomas seasonal SUE, live 75 trading days) +
ann_age from EDGAR XBRL 10-Q/10-K vintages (quark/data/edgar.py; PIT-strict:
value first visible the trading day AFTER filed; leak unit-checked).
Coverage: 605/656 PIT names, 28.7k announcements, 71% of names live 2012+.
Pre-registered: weekly h5 PIT, taus {1.00, 0.25}. Result vs cycle-2 baseline:
| IC | t | net Sharpe tau=1.00 | tau=0.25 | |
|---|---|---|---|---|
| baseline (no earnings) | +0.0125 | 2.35 | −0.13 | +0.10 |
| + SUE/ann_age | +0.0107 | 2.14 | −0.25 | +0.03 |
Read: the features SUBTRACT. Best diagnosis (not yet tested): XBRL
filed dates are 10-Q/10-K submissions, typically 2–4 weeks AFTER the 8-K
press release that actually moves the price. PEAD's drift is front-loaded;
entering at the 10-Q date buys the stale tail while the price-momentum
features already encode the announcement jump — so the SUE columns add
noise, and HGB spends splits on them. Implication for the family, not the
thesis: announcement-date-precise surprise data (IBES via WRDS, which
carries announcement dates) remains the right test; XBRL-vintage SUE at
weekly horizon is the wrong instrument. Staleness-TOLERANT fundamental
families (value/profitability/asset growth/issuance — slow signals where a
3-week lag is immaterial) are unaffected by this failure mode and are the
next test (fundamentals prefetch running). Trials this cycle: 2, reported.
Five slow families added as ranked features (quark/data/edgar.py fundamental_feature_panels): value_bm, profit_roa, asset_growth, net_issuance, accruals. Coverage 63-86% of names 2012+. Pre-registered: ML arm taus {1.00, 0.25, 0.10} + Novy-Marx-style rank-combo reference arm.
| config | net Sharpe (cycle 2 same-tau baseline) |
|---|---|
| nm_rank_combo (value+profit, annual, no ML) | −0.00 |
| fund tau=1.00 | −0.06 (−0.13) |
| fund tau=0.25 | +0.13 (+0.10) |
| fund tau=0.10 | +0.19 (+0.07) |
Weekly IC dipped (0.0125 → 0.0105, t=2.22): fundamentals do NOT predict next-week winners. But net Sharpe improved at EVERY tau and the tau-curve now rises toward slower trading — the fundamentals strengthen the PERSISTENT component of the composite signal, which is exactly what the GP aim-portfolio math rewards (slow signals earn more weight in the EWMA book). Weekly IC is the wrong metric for slow features; the economics are the metric. Also instructive: the famous standalone value+profitability rank combo (Novy-Marx OSoV, Sharpe 0.74 in-sample pre-2011) is DEAD on our 2012+ PIT large-cap panel (Sharpe −0.00) — consistent with McLean-Pontiff decay being worst in large caps — yet the same information adds ~+0.1 Sharpe as features inside cost-aware ML construction. Published effect sizes are epitaphs; combinations inside honest construction still pay. Trials: 4, reported. PIT trajectory so far: −0.13 → +0.10 (GP) → +0.19 (GP + fundamentals).
Pre-registered follow-ups to cycle 4. (A) Weekly tau completion: 0.15→0.181, 0.05→0.161, 0.03→0.153 — peak confirmed at tau≈0.10 (0.192), and tau=0.05 no longer collapses (price-only: −0.035; composite: +0.161): the fundamentals made the signal genuinely more persistent, the interpretation test passed. (B) Monthly h=21 revival: price-only PIT IC was EXACTLY 0.0000 (cycle 2); with fundamentals IC +0.0120 (t=1.68, n=188), net Sharpe 0.177 (tau=1.00) / 0.211 (tau=0.50) — the monthly horizon's entire signal is attributable to the fundamental families. Best honest configs now: monthly+fund tau=0.50 (0.21) and weekly+fund tau=0.10 (0.19). Trials: 5, reported. Predictions cached to reports/preds_{weekly,monthly}_fund_pit.parquet.
Weekly(tau=0.10) and monthly(tau=0.50) book returns correlate only +0.39 OOS — partially independent information. Pre-registered trials (3): blend_50_50 → 0.246; monthly_tau0.25 → 0.273; blend(wk 0.10 + mo 0.25) → 0.276, turnover 5.2x, cost drag 26bps. PIT trajectory: −0.13 → +0.10 (GP) → +0.19 (fundamentals) → +0.28 (two-horizon blend).
Multiple-testing caveat (standing): ~27 registered trials now touch this panel family. The tau/blend grids are 1-D monotone structures (cost mechanics, low mining risk) but "extend until it stops improving" is still selection along a curve — quote the plateau (~0.2-0.28), never the single max. The PRIMARY statistical claims remain the model-level ICs computed once per configuration (weekly +0.0105 t=2.22; monthly +0.0120 t=1.68, horizon-distinct), not any particular Sharpe cell. A final shipped config must be chosen by walk-forward selection (choose tau/blend on data through year Y, measure on Y+1) before any number is quoted externally — TODO. Residual PIT optimism (45% delisted recovery) still applies to everything.
Added 6 SUE-history panels (lags 1-4, mean4, mean12 — Kaczmarek-Zaremba- style) + gp_assets (GrossProfit TTM/assets, 324/656 tickers = 38% coverage, sector-biased: financials don't report GrossProfit). Result: everything degraded vs cycle 5/6 baselines — weekly tau0.10 0.192→0.005; monthly IC +0.0120(t=1.68)→+0.0053(t=0.83), tau0.25 0.273→0.082; blend 0.276→0.053.
Design error acknowledged: two feature blocks changed at once — cannot attribute. Suspects: (a) gp_assets missingness is sector-correlated noise; (b) SUE lag-1 panel reintroduces the cycle-3 stale-timing failure x4 lags; (c) monthly model (188 obs) is most feature-count-sensitive. Cycle 8 = pre-registered one-variable ablation on the monthly config: (A) fundamentals+SUE-history only; (B) fundamentals+gp_assets only. Recovery bar: monthly IC >= +0.0120. If neither recovers, cycle-6 config stands as champion and both families are logged dead on this panel. Trials: 4, reported.
Control (fund-only) reproduced cycle 5 exactly (IC +0.0120 t=1.68, 0.273) — comparisons valid. SUE-history block is the cycle-7 killer (IC → +0.0076, Sharpe → 0.096): XBRL-vintage SUE now falsified at BOTH horizons; family suspended pending announcement-dated surprises (IBES/WRDS or 8-K parsing). gp_assets mild drag (38% sector-biased coverage) — dropped. Champion remains cycle-6 blend (0.276). Trials: 3, reported. Next: walk-forward config selection (the standing honesty TODO) — all selection so far used the full OOS window; the shipped number must come from configs chosen only on trailing data.
Protocol: for each year Y in 2015-2026, pick the config (27 candidates: weekly/monthly tau grids + all 50/50 blends) by net Sharpe on 2012..Y-1 only; apply to year Y; chain. Predictions were always walk-forward; this closes the last selection leak (config choice).
Walk-forward-selected 2015-2026: net Sharpe 0.05 (CAGR 0.1%, vol 3.3%, maxDD -11%). In-sample-selected champion (b_w0.10_m0.25), same window: 0.29. The 0.28 "plateau" was ~80% config-selection bias.
Structure worth recording: from 2017 on, the selector stably picks m0.25 (the trailing-Sharpe ranking is not chaotic); the damage concentrates in 2015-2016 (short trailing windows chose configs that then cratered: -0.36, -2.27) and in the wide year-to-year dispersion of realized Sharpe (-1.0 to +1.7) — with 12 annual observations, se(Sharpe) ≈ 0.29, so 0.05 vs 0.29 is not even statistically distinguishable. That is the deepest honest statement: the economic edge of this system cannot be distinguished from zero at this sample size, even though the predictive signal is statistically real (IC t=2.2-2.4). Thin real signals produce exactly this signature. No post-hoc window slicing to rescue the number — that would be the exact sin this protocol exists to catch.
Implication (consistent with verified fundamental-law math): config polishing is exhausted; only additional independent signal families can raise composite IC enough for the economics to clear the selection tax. Families queued: announcement-dated earnings surprises + analyst revisions (WRDS pending), FINRA short interest. Trials: measurement protocol, not a search — champion unchanged.
New domain: Binance daily panel (414 coins, 2019+, current-listing bias documented up front). Cycle 1 (pre-registered h=7 weekly xsec, $10M screen, 10bps, taus {1,.25,.10}): IC +0.0165 (t=1.52, n=341) but ann_vol ~300 — GARBAGE. Postmortem: Binance reused the LUNA ticker post-Terra-collapse; compute_returns' gap-bridging (correct for equity holidays) glued old-LUNA $0.0001 to LUNA2 $8.87 across a 2-week delisting gap = +17,739,900% in one untradeable bar inside the backtest. Real tails (DOGE +392% Jan-2021) verified as genuine and KEPT. Cleaning rule (from the diagnostic, not tuned on results): 24/7 market ⇒ any >3-day gap = halt/redenomination ⇒ break series, keep latest contiguous segment; drop 14 stablecoins/fiat proxies. Cycle 2 = identical configs on cleaned panel. Lesson filed under "most of the real work is data": the engine was fine; the CALENDAR ASSUMPTION (gaps = holidays) was an equity convention that became a bug in a 24/7 market. Domain expansion means auditing every convention, not just adding data.
IC sharpened on clean data (+0.0223, t=1.99, n=341 — the artifact was DILUTING the measured signal) but net Sharpe negative at every tau (−0.64/−0.56/−0.39, sane vol 10-28%). Cycle-1's +0.32 was entirely the LUNA artifact. Structure: positive weekly rank-IC + negative decile-book returns even at 74bps drag ⇒ the extreme deciles mean-revert (pumped coins crash) while mid-ranks carry the correlation — the tradeable ends of the signal don't pay. Price-momentum crypto xsec: DEAD as implemented, and this is still the optimistic listing-biased panel. Remaining crypto hypothesis with documented support: funding-rate carry (orthogonal, unbuilt). Trials: 3, reported.
Pond change delivered on the SIGNAL side: IC +0.0173 (t=3.11, n=654, 1,562 names/wk) vs S&P panel +0.0125 (t=2.35) — more breadth, stronger statistics, exactly as the decay literature predicts. But net Sharpe still negative at all taus (−0.52/−0.10/−0.07, tiered 5/10/20bps costs), and the diagnostic explains why: decile curve is monotone D1→D8 (16→28.7bps/wk) then REVERSES at D10 (23.6) — gross D10−D1 spread only 7.5bps/wk (~2%/yr gross on the book), LOWER than the S&P panel's 16bps despite higher IC. Rank correlation up, dollar spread down: small-cap returns are noisier, and the prediction extremes are systematically the flattest/reversing part of the curve. THIRD universe with the same fingerprint (S&P, crypto, broad): weekly price-only ML produces real rank-IC everywhere and extreme-decile economics nowhere. Hypothesis logged, NOT traded (would be post-hoc): interior-rank constructions (long D8-ish, rank-linear weights) may harvest the monotone region; a proper test must be pre-registered on new data or justified structurally first. Upper-bound caveat applies (listing bias). Trials: 3 + 1 diagnostic, reported.
Pre-registered arms A(decile)/B(rank-linear)/C(B+inv-vol)/D(C+beta-neutral) on two cached prediction sets. Broad weekly: A −0.07 → D −0.19 — no gross edge to transfer (TC × 0 = 0); construction cannot rescue the broad price-only book. S&P monthly (fund): A 0.273 → B 0.361 → C 0.367 (vol 3.0%→1.8%, turnover 4.5→2.8x) → D 0.311 (beta hedge added noise — dropped). The decile-diagnostic prediction held: interior-rank harvesting + risk-weighting lifts Sharpe ~34% where gross edge exists. Champion candidate sp_m_C is FULL-WINDOW-measured — walk-forward gate rerun with construction arms in the candidate set is the required next measurement. Trials: 8, reported.
Study 1 traded these instruments time-series and died; ranking them AGAINST each other weekly (77 instruments, 7 asset classes, ex hindsight_picked, per-class costs) delivers the campaign's best number: decile tau=0.25 net Sharpe 0.71 (IC +0.0169 t=2.66 n=758; CAGR 4.4%, vol 6.3%); armC 0.545 at vol 2.6%. Only 3 pre-registered trials. VERIFICATION: shuffled-label control −0.59 (clean); 12/15 years positive, losers = documented trend-graveyard years (2012/14/18); corr to equity WF stream +0.08 (orthogonal). Structural advantages vs equities: instruments don't delist at zero (minimal survivorship), and the family (cross-asset relative momentum) has persisted publicly for decades at CTA scale. CAVEATS: Yahoo continuous-proxy data quality; per-class cost model is optimistic for retail ETF implementation; family is published → decay haircut applies; walk-forward config selection still to run (3-config burn is small). Next: FX carry via FRED differentials (documented orthogonal family, key already held), more markets, blend with equity book. The verified thesis lands: the edge wasn't in the most-arbitraged universe; it's in cross-asset relative value at retail-inaccessible-to- institutions scale. Trials: 3 + verification, reported.
Cycle-13 walk-forward config selection (3 candidates, yearly, 2015-2026): 0.852 — no selection tax (equities paid 80%). Config ranking stable; full-window 0.711 was dragged by 2012-14, not inflated by hindsight. The multi-asset book is the first Quark result to pass every local gate: shuffled control, yearly stability, orthogonality, walk-forward selection. Remaining before external quoting: futures-proxy data audit + retail cost stress. Insider x arm-C on broad panel: −0.045 (decile +0.047) — arm-C construction is S&P/monthly-specific, NOT universal; broad book stays decile. corr(equity book, multiasset book) = −0.16: natural hedge pair.
Overnight/intraday decomposition (opens fetched, on/id momentum 21/63 + clientele gap) joins price+insider: IC +0.0212 (t=3.93, n=654) — third confirmed family, composite tracking quadrature (0.0173→0.0194→0.0212). Net Sharpe still ~0.076 (decile, tau .25): the broad book's signal is now overwhelming and its monetization unchanged — gross spread is spread thin across the curve and 20bps small-cap costs eat it. Trimmed-interior book (pre-registered bands long [.7,.9) short [.1,.3), one trial): −0.184 — FALSIFIED; the D8 peak was noise. Broad-book constructions now exhausted: decile stands at ~0.08. Honest read: broad equity caps near ~0.1-0.3 until more IC lands (fundamentals fetch + 8-K dates pending). Trials: 2+1, reported. WSB attention data fetching (Arctic Shift, top-100/day 2019-2026) — attention-reversal test next; documented prior says FADE hype, small caps, small capacity.
NOAA CPC daily population-weighted HDD (2012-2026, free) vs NG=F. PIT seasonal norms (prior-years day-of-year), declustered top-quintile shocks. Cold shocks d+1..+5: +0.67% (t=0.44, n=100) vs random-winter-day control +0.82% — INDISTINGUISHABLE. Warm shocks: −0.40% (t=−0.50). Realized weather is fully priced. The informational frontier is UPSTREAM: the market trades forecasts 5-10 days ahead of realization, so the only tradeable seam is forecast ERROR (the acquaintance's actual edge) — requires archiving forecast vintages vs realizations. NOAA GFS forecasts are free → forecast-error collector is buildable; history accrues from day one (moat-by-patience). Also instructive: the test itself took ~1 hr end-to-end — the machine can price-check an information hypothesis same- day, which is the actual edge-hunting capability. HDD series cached: data/noaa_hdd_daily.csv.
Dataset: first-100-posts-per-day chronological (NOT score-sorted), titles + final scores + timestamps, r/wallstreetbets 2019-2026 (Arctic Shift). KNOWN TRAPS DISARMED IN ADVANCE: 1. Final-score lookahead: archived scores are END-STATE (upvotes accrue after posting) — scores may NOT be used as PIT weights. Post COUNTS are PIT-safe. Scores usable only for descriptive analysis, flagged. 2. Ticker extraction: cashtags ($XXX) + uppercase tokens matched to panel symbols MINUS blocklist of ambiguous symbols (A, DD, IT, CEO, ON, ALL, ARE, FOR, GO, NOW, OPEN, REAL, SO, OUT, EAT, BIG, CAN, HAS, ANY, RH, YOLO-adjacent). Blocklist fixed BEFORE results. 3. Chronological first-100 sampling = attention proxy via daily post VOLUME share, not popularity — biased toward early-UTC hours; accepted and documented (uniform across sample). 4. Regime nonstationarity: 2021 mania vs after — results reported for full sample AND 2022+ separately (pre-declared split). PRE-REGISTERED HYPOTHESES (directional priors from literature): H1: abnormal mention spike (count z>2 vs trailing 63d) in sub-$2B names → REVERSAL d+5..+20 (fade the hype). Primary. H2: same-day/next-day momentum d+1..+3 (attention chase) — secondary. Universe: broad panel ∩ eligibility. Event decluster: 5 trading days. Controls: random matched-size events. All trials reported.
Before running the pre-registered WSB study, documented priors (multi-source academic, NOT adversarially verified — usage limit): (1) WSB DD edge died post-Jan-2021 — predicted +2.3%/mo ex-GME/AMC pre-GME, decayed to ~zero/ negative after the 500k→10.7M member explosion; our pre-declared 2022+ split is the honest-but-likely-dead window. (2) ADVERSARIAL DATA: WSB users deliberately post wrong tickers to poison scrapers; academics manually reviewed all 5,050 posts. Our blocklist stops common-word tickers, NOT intentional poisoning — extraction noise is a documented confound. EXPECTATION SET: null or corpse likely; run anyway (clean null on famous edge validates machine + is honest). Do NOT p-hack a live result out of a dead edge. Masters doctrine banked (reports/deep_research_masters): Benter fractional Kelly (½-⅓, because 2x edge-overestimate → negative growth), blend-with-market-odds insight, capacity=0.25-0.5% of pool → pick pond by capacity; Thorp idea→quant→cheap-verify loop = our cycle loop.
274,415 posts, 2,847 tickers extracted (top: GME/TSLA/AMC/BBBY — sane; AI-token contamination 2-3%, reported not hidden). First pass showed −22/−38% "fade" — entirely zero-price data errors (clip −95%/+500% + zero-cleaning removed it; LUNA lesson recurs: artifacts flatter). CLEAN: H1 fade d5-20: +0.3% (t=0.15) full / −0.4% (t=−0.20) 2022+; H2 momentum: −0.8% (t=−0.64); control −0.5%. NULL everywhere. The WSB attention edge is dead post-2021, replicating Bradley et al. independently. Study closed; no further trials on this family without NEW construction justification.
Multi-asset book WF Sharpe 0.85 (se≈0.27). Doctrine: shrink edge before sizing (Benter: 2x overestimate → negative growth at full Kelly). Shrunk live expectation S≈0.5. Kelly-optimal vol = S = 50%; half-Kelly 25%; POLICY ADOPTED: vol target 10-12% (~⅕ Kelly of shrunk edge) for any deployment, paper first, revisit after 26 weeks of live ledger. Per-edge niche positions: ⅓-Kelly ceiling on estimated edge, hard per-position caps, kill-switch discipline unchanged. Rationale logged: backtest-derived edges carry estimation error ABOVE Benter's in-vivo betting edges.
Preliminary (data through 2023-06; 98,360 on-panel events, 60,606 after 30d declustering; |reaction|>5% filter; signed drift d+2..d+21 vs market). PREDICTION was: drift ~0 in LARGE, growing down the size ladder. REALITY:
2013-2019 2019-2026
LARGE +0.40% (t=2.68) +0.06% (t=0.27) MID −0.03% (t=−0.19) +0.25% (t=1.19) SMALL −0.18% (t=−1.05) +0.07% (t=0.26)
The gradient runs BACKWARDS: the only significant drift was in LARGE names pre-2019 (+0.40%/event — modest, and now decayed to zero), and the SMALL tier — the thesis's home — is a tightly-bounded null (n≈8k, se≈0.13%/event) in BOTH eras. Post-earnings drift in small caps does not exist on this panel. Best explanation: "nobody is paid to read the filing" was true in 1989; today MACHINES read every 8-K within seconds regardless of market cap — filing-reading was commoditized exactly like parking-lot satellites. Honest caveats: d0-d1 reaction window may mis-time some after-close press-release sequences; EFTS display_names may under-cover tiny/OTC filers (selection toward better-covered names). Neither plausibly manufactures a null this flat across 8k events. Study closes when full fetch lands (2023-2026 tail); thesis not expected to revive. Trials: 9 cells, all reported.
Complete: 168,071 Item-2.02 announcements, 4,604 tickers, 2012-2026; 84,576 declustered events. Preliminary verdict CONFIRMED: SMALL tier full-sample −0.05% (t=−0.40, n=11,852) — a precise null; LARGE pre-2019 +0.40% (t=2.68) decayed to +0.09% (t=0.64) after. No size gradient in the predicted direction. Post-earnings drift is extinct at all sizes on this panel; the barrier ("nobody reads small filings") was commoditized by machine filing-readers. Study CLOSED. The announcement-date dataset itself (data/ann_dates_8k.csv) remains an asset: PIT earnings-event timing for 4,604 names, reusable for any future event study.
Rolling vitality curves on our own panels (reports/study script run_edge_ontogeny.py). THE FINDING — an alive edge's calm phase looks like: sign persistence at LOW annual t, never loud. 8-K LARGE drift alive phase (2012-2019): eight consecutive positive years at +0.2..+0.8%/event, per-year t only 0.3-2.2 — no single year significant; the accumulation was the signal. DEATH SIGNATURE #1: sign coherence breaks BEFORE the mean dies (2020+: +0.58,−0.50,+0.75,+0.46,−0.23,−0.10 — alternating chaos, mean still ~0.1). DEATH SIGNATURE #2 (crowding inversion): rolling Sharpe crosses zero and TRENDS (reversal_1990: −1.1,−1.4,−1.4 deepening 2024-26 — the corpse became an anti-edge). UNDEAD state (momentum): wild ±1.5 oscillation around small positive mean — harvestable only inside diversified books. IMMORTAL (turn-of-month): modest, persistent, mean- reverting after bad years (2024 −1.3 → 2026 +1.5). IMPLICATIONS: (1) edge detectors should scan for MULTI-YEAR SIGN PERSISTENCE AT LOW t — anyone demanding annual t>3 only ever finds loud dead things; (2) decay monitoring for OUR live book = watch sign coherence, not mean (our multi-asset book: 12/15 positive years = the alive signature, currently in its calm); (3) the 2015 lesson: an alive edge's best year (t=2.2) looks like noise to everyone not tracking the cumulative record — which is WHY it stayed alive seven more years.
Mechanical regime-riders on hindsight menu {SPX,IXIC,NVDA,BTC,GC,CL}: MAX $6.4B (W63/top1/no-filter/1.5x, maxDD 64%); MEDIAN $134M; MIN $15.5M. Selection tax max→median = 98% — the DSR lesson in dollars. Even MIN beat S&P buy-hold 4x: menu bias dwarfs all parameter choices (universe selection = the deadliest lookahead, quantified). Kelly inverted-U visible empirically: median by leverage 1.0x $77M < 1.25x $232M > 1.5x $138M — over-Kelly costs real money even in a winning decade. Crash filters HURT at median (V-bounce re-entry misses). Median maxDD 50-67%: statistically optimal paths are behaviorally unholdable. Learnings transferred to doctrine; none of these numbers are forward expectations.
Storm = fwd 126d > +50%. Purged walk-forward by year, broad panel, texture- only features. Mean OOS AUC 0.761, top-decile lift 2.6x, positive lift 11/11 years incl 2018/2020/2022 regime breaks. THE LEARNED CALM (top-5% states vs population): vol63 0.86 vs 0.32 (HIGH-vol, not quiet); dd_from_ high −49% vs −13%; mom252 −34% vs +11%; mom21/63 ≈ 0. The model's pre-storm state is NOT serene compression — it is a small violent name down ~half whose decline has finally flattened: crashed-and-stabilized, base-forming. "Calm before the storm" = EXHAUSTION, not serenity. Matches verified literature (alpha concentrates in hard-to-arbitrage distressed/high-vol names) — model rediscovered it blind. CAVEAT (standing): storm-classifier ≠ strategy — the other 90% of that decile includes names that keep dying; tradability requires the full return distribution net of costs/borrow in exactly the universe where costs bite hardest. Next gate before any use: expected-return study of top-decile states. Detector saved as screening instrument: scripts/run_storm_detector.py.
Framework: Jan-Feb steering (4 configs), Mar-Jul scored. Frozen v7 vault run first: −$2,111 on 181 bets, MC percentile 2.4% — significantly WORSE than the efficient-market null. Then (vault reopened as development, honestly labeled) 50-variant sweep across stretch-strength k, thresholds, category sets, horizons, cluster modes. RESULTS: best of 50 = +$50 (zero, after 50 looks); median −$1,750. MARGINALS (the real deliverable): - FLB stretch k: monotone WORSE with strength (−0.5→+$16, 1.5→−$2,302); every positive-k cell significantly below null (MC 0.03-0.17). The published FLB (2021-25 window) does not exist as a harvestable edge in our Mar-Jul 2026 tail markets — consistent with the documented 2026 institutional entry (SIG/DRW/Wintermute) compressing exactly this bias, and with our own KB warning ("FLB frequently does not survive costs"). - Politics = the poison category (adding it: −$1,426 median); "other" worse (−$3,032). geo+tech alone ≈ null (−$146). - Cluster caps robustly save money in EVERY configuration (none −$2,693 → theme −$590): risk rails are permanent doctrine, confirmed. - CLV was negative-to-flat from January — the gold-standard metric called the verdict months before P&L did. Believe CLV over P&L, always. NOT TESTED by this sweep (still-live hypotheses for live-forward paper): the telegraph/slope signal (momentum in probability space — our own discovered pattern, absent from this static-entry sweep), pure arbitrage (monitor logs 9-10 live mispricings/snapshot), maker/LP-reward quoting, whale-following (collector accruing since 7/23). Next clean test = August forward, live paper, via monitors — the only untainted data there is. Trials: 4 dev + 1 vault + 50 sweep = 55, all logged. $0 real lost; family killed for ~$0.15 of compute. The machine works.
Center calibration (3,341 liquid resolved markets, 5d-out): slope 0.87 — the 2026 market is mildly OVERCONFIDENT (longshots 7.4% real vs 5.3% implied ; favorites 87.5% vs 94.4% ) — REVERSED from the 2021-25 literature. But the reverse harvest is also dead: buying the cheap side <25c nets −21.7%/bet (t=−4.6, n=1,855) — the longshot spread wall (750bps half) exceeds the bias. Combined with the 55-trial favorite-side falsification: the tape pays NOTHING net in either direction; the only structural winner is the spread-charger. THE MAKER MECHANISM IS THE POND'S ANSWER — now proven by convergence (sweep marginals + vault + calibration + live shadow-book observation of the #1 wallet quoting both sides). NOTE: true tail (<$100k vol) still unfetched (gamma pagination depth blocks it) — tail calibration remains open. Desk built and running: arb-sim 30min, shadow-book (maker-noise filtered) + maker-sim + grader 2x daily, DESK_REPORT.md auto-writes.