feat(forecasting): §9.5 macro coefficient (#951e, advisory) #1010

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Site Finder v2 / EPIC 7 — #951 sub-PR 4 (§9.5 макрокоэффициент). Детерминированный, эвристический (не fitted), без LLM. ADVISORY (не врезан). Часть #944.

macro_coefficient.py — композитный множитель спроса (центр 1.0, clamp [0.6,1.3]), направленный по сегментам:

4 backed sub-factor: rate (.18) / mortgage_rate (.12) / issuance (.10) / overdue (.05); 4 degraded (gov/income/cpi/confidence → None, reserved weights).
Renormalize над available (degraded выпадают из числителя И знаменателя → коэф не сжимается искусственно к 1.0; single survivor == all-4 по масштабу).
Segment-steepness: expensive×1.4 / large×1.3 / investment×1.5 / favored×1.25 на rate-каналы.
Graceful empty → 1.0/low.

50 тестов (forecasting/ всего 191), ruff clean. code-reviewer opus OK (renorm-математика верна против реальных весов, segment-направление верно). Follow-up в PR6: lone-survivor leverage gate, асимметрия favored. Refs #951

**Site Finder v2 / EPIC 7 — #951 sub-PR 4 (§9.5 макрокоэффициент).** Детерминированный, эвристический (не fitted), без LLM. **ADVISORY** (не врезан). Часть #944. `macro_coefficient.py` — композитный множитель спроса (центр 1.0, clamp [0.6,1.3]), направленный по сегментам: - 4 backed sub-factor: rate (.18) / mortgage_rate (.12) / issuance (.10) / overdue (.05); 4 degraded (gov/income/cpi/confidence → None, reserved weights). - **Renormalize над available** (degraded выпадают из числителя И знаменателя → коэф не сжимается искусственно к 1.0; single survivor == all-4 по масштабу). - Segment-steepness: expensive×1.4 / large×1.3 / investment×1.5 / favored×1.25 на rate-каналы. - Graceful empty → 1.0/low. **50 тестов** (forecasting/ всего 191), ruff clean. code-reviewer opus OK (renorm-математика верна против реальных весов, segment-направление верно). Follow-up в PR6: lone-survivor leverage gate, асимметрия favored. Refs #951

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feat(forecasting): §9.5 macro coefficient (#951e, advisory) a5e887ae32

Deterministic composite demand multiplier (centered 1.0, clamped [0.6,1.3]),
corrects a forecast for the macro regime, directional by market segment.
Heuristic named-constant weights over 4 backed sub-factors (rate / mortgage
rate / issuance / overdue) with weight renormalization over available inputs
(degraded gov/income/cpi/confidence drop out of num AND denom, not silently 0).
Segment-steepness modifier on rate-driven channels (expensive/large/investment
steeper-negative on rate↑; family/compact/liquid steeper-positive on rate↓).
Graceful empty -> 1.0/low. Pure, no LLM, no new SQL (reuses PR2 get_monthly_macro).
ADVISORY: not wired into any endpoint. 50 unit tests (forecasting/ total 191).

PR6/wiring follow-ups: gate lone-survivor renorm leverage under low confidence;
reconsider asymmetric favored-segment steepness (resilient on rate↑).