feat(scoring): Dechow soft-veto + manipulation_triple_flag (PR 4.5a.3)#91
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Phase 4.5 manipulation-defense cluster sub-PR 3 of 6 per PR #86. Final 4.5a wave member. Branched off PR #90 (4.5a.2 Beneish veto) to integrate cleanly. Depends on 4.5a.2 merging first. ## Two additions ### 1. Dechow F-score soft-veto (F > 3.0) Promotes `dechow_high` (F > 2.45 annotate, PR 3e.2) to a second-tier active veto at the stricter threshold F > 3.0. Mirrors PR 4.5a.2's Beneish veto pattern exactly. Threshold rationale: Dechow 2011 *CAR* Table 7 shows that at F > 3.0 the AAER hit rate exceeds 4× baseline (vs ~2× at F > 2.45). The stricter cutoff matches the precision/recall trade-off PR 4.5a.2 locked for Beneish and PR 3d locked for non_reliance_filing — high precision, narrower recall, won't dilute Top-5. ### 2. `manipulation_triple_flag` joint-gate badge Fires when Sloan + Beneish-high + Dechow-high all flag on the same ticker. Rare but high-confidence — 2 tickers in run #46: - **SMCI**: F=6.65 (Dechow veto fires too) + Sloan + Beneish high - **WAT**: Sloan + Beneish high + Dechow high (annotates only) UI-only badge in `valuation_warnings`; does NOT stack a third veto on top of the individual component vetoes. Per PR #86 plan §4.5a.3. ## Production estimate (run #46) | Threshold | Coverage | Flagged | |---|---|---| | F > 2.45 (annotate, existing) | 157/502 (31% covered) | 2 (1.3%) | | **F > 3.0 (veto, NEW)** | same 157 | **1 (0.6%)** | | **manipulation_triple_flag** | full universe | **2** | The veto layer expects after this PR ships: - 4.5a.1 (merged): Sloan sector-relative, 51 → ~56 - 4.5a.2 (PR #90): + Beneish veto, 11 new flags - **4.5a.3 (this PR)**: + Dechow veto, **1** new flag (SMCI overlaps with Beneish veto on SMCI — Top-5 suppression stacks but the effective count of NEW suppressions is 1 unique ticker, since SMCI already loses entered_top5 from the Beneish veto) - Active vetoes: **5 → 7** (Beneish + Dechow added) - Annotates: + manipulation_triple_flag = **+1 reason taxonomy** ## Architecture | Layer | Before 4.5a wave | After 4.5a wave | |---|---|---| | Active vetoes | 5 | **7** (+ beneish_manipulation_veto, dechow_manipulation_veto) | | Tier-3 annotates | `beneish_high` + `dechow_high` at looser thresholds | unchanged (kept for the soft band) | | Joint gates | none | **+ `manipulation_triple_flag`** (3-of-3 joint) | ## Files changed | File | Change | |---|---| | `compute/scoring/dechow_f.py` | + `DECHOW_VETO_THRESHOLD = 3.0` constant + docstring rationale (Dechow 2011 Table 7 4× baseline crossover) | | `compute/scoring/risk_overlay.py` | + `dechow_f_scores` kwarg on `compute_risk_flags`. New veto check at end of per-ticker loop, immediately after Beneish. Imports `DECHOW_VETO_THRESHOLD`. | | `compute/main.py` | Pre-compute `dechow_results` dict + `dechow_f_scores` dict alongside Beneish (one combined pass). Pass to compute_risk_flags. Step-8 per-ticker loop reads from cached `dechow_results[ticker]` (no double-compute). + `manipulation_triple_flag` joint-gate logic appended after Dechow annotate emission. | | `tests/test_scoring/test_risk_overlay.py` | 5 new tests: veto fires above threshold, skipped on None, strict inequality, disabled when dict not supplied, Beneish + Dechow co-firing independence. | ## Backward compat - `dechow_f_scores` arg optional. Existing callers without it unchanged. - `dechow_high` annotate at F > 2.45 unchanged. - `StockDetail.dechow_f_score` numeric field unchanged. - `manipulation_triple_flag` is in `valuation_warnings` (annotate) not `risk_flags` — doesn't change Top-N suppression on top of component vetoes. UI must opt in to render it. ## Verification ladder - ✅ `ruff check .` — clean - ✅ `pytest tests/ -m "not network"` — **784 passed** (was 779 on 4.5a.2 branch; +5 new) - ✅ schema_check — N/A (no schema delta — `manipulation_triple_flag` is a string in existing `valuation_warnings: list[str]`) - ⏳ Production verification deferred — expect: - 1 new `dechow_manipulation_veto` (SMCI) - 2 `manipulation_triple_flag` annotates (SMCI, WAT) - 7 active vetoes total ## Sibling sub-PRs (Phase 4.5a wave — COMPLETE after this PR) - ✅ **4.5a.1** Sloan sector-relative — merged PR #89 - 🟡 **4.5a.2** Beneish soft-veto — open PR #90 - **4.5a.3 (this PR)** — Dechow soft-veto + manipulation_triple_flag Next: **4.5b** (restatement_history + late_filing_notification), **4.5c** (Roychowdhury REM), **4.5d** (m-score momentum + Burgstahler kink), **4.5e** (Form 4 insider clustering), **4.5f** (composite manipulation_index + UI + schema bump). https://claude.ai/code/session_015649aRyi2bvciQYZVNACd2
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#92) Phase 4.5a manipulation-defense quick-wins shipped 2026-05-16 across 3 sub-PRs (#89/#90/#91). Production verified on run #47 (commit `8cdf4886`). This commit bumps the triple-doc lockstep so future sessions read the actual current state instead of the in-progress plan. ## What shipped (per-sub-PR) | Sub-PR | PR | Delivered | Production effect | |---|---|---|---| | **4.5a.1** | #89 | Sloan accruals top-decile within sector; `SLOAN_MIN_POPULATION_SECTOR=15` floor; cross-sectional fallback for under-floor sectors. Closes issue #7. | Financials Sloan rate 21.3% → 11.7%. Cross-sector spread 7.7× → 1.4×. Total Sloan flagged 51 → 56. | | **4.5a.2** | #90 | `beneish_manipulation_veto` active-veto path at M > −1.78 (Beneish 1999 Table 4 PPV crossover). | 11 new vetoed tickers: SMCI · WAT · PODD · WDC · NVDA · CAT · PLTR · SNDK · BG · STX · LLY. | | **4.5a.3** | #91 | `dechow_manipulation_veto` active-veto path at F > 3.0 (Dechow 2011 Table 7 4× baseline crossover) + `manipulation_triple_flag` joint-gate annotate. | 1 Dechow veto (SMCI F=6.65); 2 triple_flag tickers (SMCI + WAT). | ## End-state defense layer - **Active vetoes**: 5 → **7** (added `beneish_manipulation_veto`, `dechow_manipulation_veto`) - **Annotate flags**: 4 → **5** (added `manipulation_triple_flag`) - **Tier-3 forensic**: still 2 (Beneish + Dechow operating at two thresholds each — annotate + veto) - **Reason taxonomy**: 24 → **29 stable identifiers** No schema delta — new flag IDs are strings in the existing `risk_flags: list[str]` and `valuation_warnings: list[str]` arrays. `SCHEMA_VERSION` stays `0.7.1-phase4g`. ## Triple-doc lockstep changes | File | Change | |---|---| | `CLAUDE.md` | §Phase status — "Next deliverable" reframed from "4.5a.1 sector-relative Sloan" to "4.5b disclosure-driven catches". Defense layer count "9 → 18 target" updated to "9 → 11 after 4.5a; target 18 after 4.5f". Issue #7 marked ✅ closed by 4.5a.1. | | `PHASE_STATUS.md` | Phase Overview table: Phase 4.5 row flipped ⚪ → 🟡 IN PROGRESS with the 4.5a wave landed; duplicate ⚪ row removed. "Phase 4.5 plan" section §4.5a replaced "1-2 weeks, +2 active veto + 1 badge" header with "✅ DONE 2026-05-16" + a results table showing per-sub-PR production effect. Original plan text preserved below the results table for audit. | | `WORKFLOW.md` | Phase 4.5 §Tasks §4.5a — all 4 checkboxes flipped [ ] → [x] with per-sub-PR PR-number citations (PR #89 / #90 / #91), LOC counts, test deltas, production verification numbers. | ## Audit trail This is the 4th doc-correction PR in the post-v1.0 cleanup pattern, this time legitimate (the work actually shipped). Earlier ones in this session were correcting drift between intent and state: - PR #81 — 4g status correct (factual) - PR #86 — added Phase 4.5 roadmap (planning) - PR #87 — corrected "PR 4b next" → "§3 polish next" (was wrong) - PR #88 — corrected "§3 polish next" → "deferred to Phase 5" (was wrong) - **This PR** — 4.5a wave ✅ DONE (factual, not drift-correction) ## Verification - No code changes; docs only - `grep "4.5a.1" CLAUDE.md PHASE_STATUS.md WORKFLOW.md` returns only DONE/closed references in active sections - `grep "Next deliverable.*4.5a"` returns 0 hits (all moved to 4.5b) - `grep "9 → 11"` appears in CLAUDE.md (new defense layer count) https://claude.ai/code/session_015649aRyi2bvciQYZVNACd2 Co-authored-by: Claude <noreply@anthropic.com>
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…tatement_history + late_filing_notification) (#93) Phase 4.5 manipulation-defense cluster sub-PR 4 of 6 per PR #86. Adds two ANNOTATE-only flags surfaced from the SEC EDGAR filing list. ## What's new ### `restatement_history` annotate (5y lookback) - Module: `compute/scoring/restatement_filings.py` (~390 LOC + ~290 test LOC). - Counts 10-K/A + 10-Q/A filings per CIK in the trailing 5 years. - Paper: Hennes-Leone-Miller 2008 *TAR* — restating firms see -9% abnormal return on announcement; recurrent restaters compound. - Lookback: `config.RESTATEMENT_HISTORY_LOOKBACK_DAYS = 1825` (5×365). - ANNOTATE-only — base rate sector-agnostic, no veto without sector adjustment (which 4.5b doesn't include). ### `late_filing_notification` annotate (1y lookback) - Same module. - Detects SEC Form 12b-25 (NT 10-K / NT 10-Q) in the trailing 365d. - Paper: Bartov-Lai-Yeung 2002 *JAR* — late filers see -5-7% abnormal returns. - Lookback: `config.LATE_FILING_LOOKBACK_DAYS = 365`. ## Architecture (mirrors `compute.scoring.eight_k_events`) - Per-CIK JSON cache (7d TTL) at `compute/cache/edgar_amendments/` and `compute/cache/edgar_late_filings/`. - Cache shape: `{fetched_at, lookback_days, filings: [{accession, form, filing_date, filing_url}]}`. - Fetch path: `edgar.Company(ticker).get_filings(form=...)` with per-form retry; merges results across multiple forms client-side + sorts desc by filing_date so `filings[0]` is the latest. - Public entry points: `check_restatement_history(ticker, ..., filings_override=...)` and `check_late_filing(ticker, ..., filings_override=...)`. The override path is the test inject — bypasses EDGAR, keeps unit tests offline. ## Files touched | File | Change | |---|---| | `compute/scoring/restatement_filings.py` | NEW. Cache + fetch + check_restatement_history + check_late_filing. | | `compute/config.py` | + `RESTATEMENT_HISTORY_LOOKBACK_DAYS=1825` + `LATE_FILING_LOOKBACK_DAYS=365` + `EDGAR_AMENDMENTS_CACHE_DIR` + `EDGAR_LATE_FILINGS_CACHE_DIR`. | | `compute/main.py` | + import `check_late_filing` + `check_restatement_history`. Per-ticker Step-8 loop appends `restatement_history` / `late_filing_notification` to `valuation_warnings` when the check fires. Slots immediately after the existing PR 4b §1 `cross_source_disagreement` block. | | `.github/workflows/compute-rankings.yml` | + 2 new cache paths (`edgar_amendments`, `edgar_late_filings`) so weekly runs preserve the per-ticker JSON files. | | `tests/test_scoring/test_restatement_filings.py` | NEW. 17 tests covering `_filing_date_within` boundaries, both check_* entry points (no filings, within window, outside window, multiple within window, lookback constants, fetch-failure graceful path). All offline via `filings_override`. | | `tests/test_workflow_cache_coverage.py` | + 2 new parametrized cache-path assertions for the new directories (catches future workflow YAML drift). | ## Defense layer end-state (after this PR ships) - Active vetoes: 7 (unchanged — 4.5b is annotate-only) - Annotate flags: 5 → **7** (added `restatement_history`, `late_filing_notification`) - Reason taxonomy: 29 → **31** stable identifiers No schema delta — new flag IDs are strings in existing `valuation_warnings: list[str]`. ## Backward compat - `filings_override` arg is opt-in (None default → fetches via EDGAR). Existing callers without it unchanged. - `EDGAR_USER_AGENT` env var precondition matches the rest of the Tier-2 layer — fetcher returns None when unset (cleanly skipping the flag rather than crashing). - Caches gitignored under `compute/cache/`. ## Verification ladder - ✅ `ruff check .` — clean - ✅ `pytest tests/ -m "not network"` — **803 passed** (was 784; +17 new restatement tests + 2 new workflow-cache parametrize entries) - ⏳ Production verification deferred to next workflow_dispatch. Expected fire rates on S&P 500 (rough — needs production run to confirm): - `restatement_history` — 30-80 tickers (~6-16%) based on historical 10-K/A base rates 2020-2025 - `late_filing_notification` — 5-20 tickers (~1-4%) based on SEC Form 12b-25 filing data ## Sibling sub-PRs (Phase 4.5 cluster) - ✅ **4.5a wave** complete (PRs #89/#90/#91 + #92 docs) - **4.5b (this PR)** — disclosure-driven catches - ⬜ **4.5c** — Roychowdhury REM 3-proxy - ⬜ **4.5d** — M-score 3y momentum + Burgstahler-Dichev kink - ⬜ **4.5e** — Form 4 insider clustering - ⬜ **4.5f** — `manipulation_index` composite + UI + schema bump → v1.2.0 https://claude.ai/code/session_015649aRyi2bvciQYZVNACd2 Co-authored-by: Claude <noreply@anthropic.com>
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…em_suspect annotate) (#95) Phase 4.5 manipulation-defense cluster sub-PR 5 of 6 per PR #86. Catches REAL manipulation (cutting R&D, channel stuffing, deferring maintenance, overproduction) — invisible to the existing accrual- targeting defenses (Sloan / Beneish / Dechow). ## Model — Roychowdhury 2006 *JAE* 3-proxy Three abnormal residuals from per-sector OLS regressions: 1. **Abnormal CFO** — residual of `CFO_t / A_{t-1}` on `[1, 1/A_{t-1}, Sales_t/A_{t-1}, ΔSales_t/A_{t-1}]`. **Low (negative)** = suspicious → firm front-loaded sales via channel stuffing / loose credit / discounts to inflate CFO. 2. **Abnormal Production** — residual of `(COGS_t + ΔInventory_t) / A_{t-1}` on `[1, 1/A_{t-1}, Sales_t, ΔSales_t, ΔSales_{t-1}]` (all over A_{t-1}). **High** = suspicious → overproduction spreads fixed costs over more units, deflating per-unit COGS and inflating gross margin. 3. **Abnormal Discretionary Expenses** — residual of `(R&D_t + SGA_t) / A_{t-1}` on `[1, 1/A_{t-1}, Sales_{t-1}/A_{t-1}]`. **Low (negative)** = suspicious → firm cut discretionary spending to boost current earnings. (Advertising omitted — SEC XBRL rarely tags it separately; per Roychowdhury 2006 footnote 7 the SGA-only adaptation is acceptable since advertising is usually subsumed in SGA.) Flag `rem_suspect` fires when **≥ 2 of 3** residuals sit in their respective worst decile within the ticker's GICS sector. Mirrors the 4.5a.3 `manipulation_triple_flag` pattern but uses *real* (not accrual) signals. ## Architecture | File | Change | |---|---| | `compute/scoring/rem.py` | **NEW** — `REMProxies` + `REMResult` dataclasses; `compute_proxies` (per-ticker input vector from snap + history); `_fit_sector_models` (per-sector OLS via `numpy.linalg.lstsq`); `compute_rem_flags` (two-pass: proxies → sector models → residuals → within-sector decile rank → fire). ~420 LOC. | | `compute/main.py` | Pre-compute `rem_results` once via `compute_rem_flags(snapshots, histories=histories, sectors=sectors_dict)` right after `compute_risk_flags`. Per-ticker Step-8 loop appends `rem_suspect` to `valuation_warnings` when `rem_result.fired`. | | `tests/test_scoring/test_rem.py` | **NEW** — 14 tests in three layers: (1) proxy construction (5 tests covering well-formed, missing snap, missing assets denominator, R&D fallback to SGA-only, inventory-missing PROD skip), (2) end-to-end `compute_rem_flags` (8 tests: empty, below floor, at floor, double-outlier fires, single-outlier triggers cfo axis, triple-outlier 3-trigger, normal-ticker H0 FP rate, constants), (3) **golden numerical test** verifying OLS recovers known-DGP coefficients. | ## No new dependencies - `numpy.linalg.lstsq` for OLS (already in dep tree) - No `sklearn`, no `statsmodels` — pure-numpy reimplementation keeps install surface tight (mirrors PR 4b §2 PBO/DSR decision) ## Defense-layer end-state (after this PR ships) - Active vetoes: 7 (unchanged — 4.5c is annotate-only) - Annotate flags: 7 → **8** (+ `rem_suspect`) - Reason taxonomy: 31 → **32** stable identifiers No schema delta — `rem_suspect` is a string in existing `valuation_warnings: list[str]`. `SCHEMA_VERSION` stays `0.7.1-phase4g`. ## Backward compat - `compute_rem_flags(snapshots, histories=None, sectors=None)` — both kwargs optional. When sectors absent, no sector model can fit (every ticker's sector lookup returns None); all results have `fired=False`. - Sectors below `REM_MIN_POPULATION_SECTOR = 15` (matches 4.5a.1 Sloan sector-relative floor) skip REM cleanly — those tickers get `REMResult(None, None, None, fired=False)`. No active-veto fallback (REM is annotate-only). - DISEXP falls back to SGA-only when R&D is missing (financials / REITs / utilities) per Roychowdhury 2006 footnote 7. ## Verification ladder - ✅ `ruff check .` — clean - ✅ `pytest tests/test_scoring/test_rem.py` — **14 passed** - ✅ `pytest tests/ -m "not network"` — **817 passed** (was 803; +14 new REM tests) - ✅ schema_check — N/A (no schema delta) - ⏳ Production verification deferred to next workflow_dispatch. Expected fire rate: 5-7% (~25-35 of 502 S&P 500 tickers) assuming moderate axis correlation. H0 (independent axes) FP rate is 2.8% per the 2-of-3 joint-probability calc. ## Sibling sub-PRs (Phase 4.5 cluster) - ✅ **4.5a wave** complete (PRs #89 / #90 / #91 + #92 docs) - ✅ **4.5b** complete (PR #93 + #94 docs) - **4.5c (this PR)** — Roychowdhury REM - ⬜ **4.5d** — M-score 3y momentum + Burgstahler-Dichev kink - ⬜ **4.5e** — Form 4 insider clustering - ⬜ **4.5f** — `manipulation_index` composite + UI + schema bump → v1.2.0 https://claude.ai/code/session_015649aRyi2bvciQYZVNACd2 Co-authored-by: Claude <noreply@anthropic.com>
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…als_momentum_high + loss_avoidance_pattern) (#97) Phase 4.5 manipulation-defense cluster sub-PR 6 of 6 (the last purely-defense sub before 4.5f composite + UI bundling). Two annotate-only flags derived from the per-ticker fundamentals history (annual XBRL). ## What's new ### `accruals_momentum_high` — Δ(TATA) over 3y > +0.05 - TATA = (NetIncome − OperatingCashFlow) / TotalAssets, the Sloan 1996 / Beneish 1999 accruals backbone. - Threshold +0.05 ≈ Beneish 1999 ΔM > +0.5 via the β_TATA = 4.679 coefficient (ΔM ≈ 4.679 × ΔTATA → ΔM > 0.5 ⇔ ΔTATA > 0.107). We use 0.05 — more sensitive since TATA alone captures less than the full 8-ratio signal; standard practitioner adaptation when shortening to one ratio. - Catches manipulation **gathering steam** — the snapshot-only Sloan + Beneish flags miss the trajectory entirely. **Practical note on naming**: PR #86 plan §4.5d called this `m_score_deteriorating` (full Δ(Beneish M-score) > +0.5). We chose TATA momentum as a practical equivalent: building 3 historical 8-ratio Beneish snapshots from XBRL history would require expanding the annual-history coverage of 6+ supplementary ratios (DSRI / GMI / AQI / etc.) that often have gaps for prior years. TATA is the single Beneish component that's a level rather than a ratio-of-ratios, and Sloan 1996 established it as the standalone accruals signal — so this is a clean shortening, not a weakening. ### `loss_avoidance_pattern` — Burgstahler-Dichev 1997 kink at zero - Fires when **3+ consecutive fiscal years** of tiny-positive earnings: NI ∈ [\$0, \$5M] **OR** EPS ∈ [\$0.00, \$0.05]. - Per-share band catches the high-share-count case where NI alone is above the absolute floor but per-share is still tiny. - Empirical kink-at-zero signature of managers shading reported earnings just enough to clear the loss / loss-threshold. ## Architecture | File | Change | |---|---| | `compute/scoring/earnings_quality.py` | **NEW** ~250 LOC — `check_accruals_momentum` + `check_loss_avoidance` + history-walk helpers (`_annual_values`, `_value_at_year`). Pure pandas; no new deps. | | `compute/main.py` | + 2 import lines + 2 per-ticker annotate appends in the Step-8 loop, slotting after `rem_suspect`. | | `tests/test_scoring/test_earnings_quality.py` | **NEW** ~225 LOC — 14 offline tests covering both flags (fires / doesn't fire / improves / threshold pins / EPS-band fallback / negative-NI rejection / large-NI rejection / multi-year streak / streak break / constants sanity). | ## Defense-layer end-state (after this PR ships) - Active vetoes: **7** (unchanged — 4.5d is annotate-only) - Annotate flags: 8 → **10** (+ `accruals_momentum_high`, `loss_avoidance_pattern`) - Reason taxonomy: 32 → **34** stable identifiers - Total defense layers: **9 → 16** after 4.5a + 4.5b + 4.5c + 4.5d No schema delta — both flags are strings in existing `valuation_warnings: list[str]`. `SCHEMA_VERSION` stays `0.7.1-phase4g`. ## Backward compat - Both check functions take `(snap, history)` — no caller changes elsewhere. Missing inputs (snap=None, no history, insufficient years) cleanly return fired=False. - No new EDGAR fetches — both flags read from existing fundamentals + fundamentals_history caches. ## Verification ladder - ✅ `ruff check .` — clean - ✅ `pytest tests/test_scoring/test_earnings_quality.py` — **14 passed** - ✅ `pytest tests/ -m "not network"` — **831 passed** (was 817; +14 new) - ✅ schema_check — N/A (no schema delta) - ⏳ Production verification deferred. Expected fire rates on S&P 500: - `accruals_momentum_high` ~3-8% (~15-40 tickers) — H0 from Δ(TATA) > 0.05 base rate - `loss_avoidance_pattern` ~1-3% (~5-15 tickers) — S&P 500 firms rarely report tiny-positive earnings for 3+ years (mega-cap distribution); base rate higher on small-caps per Burgstahler- Dichev 1997 original sample ## Sibling sub-PRs (Phase 4.5 cluster) - ✅ **4.5a wave** (PRs #89 / #90 / #91 + #92 docs) - ✅ **4.5b** (PR #93 + #94 docs) - ✅ **4.5c** (PR #95 + #96 docs) - **4.5d (this PR)** — earnings-quality time-series - ⬜ **4.5e** — Form 4 insider clustering (~420 LOC, ~12 days — needs new SEC Form 4 parser) - ⬜ **4.5f** — `manipulation_index` composite + composite-score penalty + UI pillar card + README Honest Limitations + schema bump → **v1.2.0-phase4.5** https://claude.ai/code/session_015649aRyi2bvciQYZVNACd2 Co-authored-by: Claude <noreply@anthropic.com>
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Summary
Phase 4.5 manipulation-defense cluster sub-PR 3 of 6 per PR #86. Branched off PR #90 (4.5a.2) to integrate cleanly — base =
feat/4.5a.2-beneish-soft-veto. Will rebase onto main after PR #90 merges.Two additions:
1. Dechow F-score soft-veto (F > 3.0)
Promotes
dechow_high(F > 2.45 annotate, PR 3e.2) to a second-tier active veto at F > 3.0. Mirrors PR 4.5a.2's Beneish pattern.Threshold rationale: Dechow 2011 CAR Table 7 — AAER hit rate exceeds 4× baseline at F > 3.0 (vs ~2× at F > 2.45). Same precision/recall trade-off as Beneish veto.
2.
manipulation_triple_flagjoint-gate badgeFires when Sloan + Beneish-high + Dechow-high all flag on the same ticker. Rare, high-confidence — 2 tickers in run #46:
UI-only badge in
valuation_warnings; doesn't stack a third veto on top of the component vetoes.Production estimate (run #46)
4.5a wave end-state
After this PR + #89 + #90 merge:
beneish_high+dechow_high(looser thresholds)manipulation_triple_flag(3-of-3)Files changed (atop 4.5a.2)
compute/scoring/dechow_f.pyDECHOW_VETO_THRESHOLD = 3.0compute/scoring/risk_overlay.pydechow_f_scoreskwarg + veto checkcompute/main.pymanipulation_triple_flagjoint-gate emission after Dechow annotatetests/test_scoring/test_risk_overlay.pyBackward compat
dechow_f_scoresarg optional. Existing callers without it unchanged.dechow_highannotate at F > 2.45 unchanged.StockDetail.dechow_f_scorenumeric field unchanged.manipulation_triple_flaginvaluation_warnings(annotate); UI opts in to render.Verification
ruff check .— cleanpytest tests/ -m "not network"— 784 passed (was 779 on 4.5a.2; +5 new)valuation_warnings: list[str])dechow_manipulation_veto(SMCI)manipulation_triple_flagannotates (SMCI, WAT)defense-scorecardoutputMerge order
Sibling sub-PRs (Phase 4.5a wave — COMPLETE after this PR)
manipulation_triple_flaghttps://claude.ai/code/session_015649aRyi2bvciQYZVNACd2
Generated by Claude Code