Light1YT
f87c5cb0b8
Add rate_sensitivity.py: regress Δln(sales) on lagged Δ(key_rate) per segment, gate (n≥8, r2≥0.1, slope<0), shrink toward EKB-wide prior (w=n/(n+10); EKB prior bootstrapped from all-None spec, gate-fail→0.0 neutral), emit §9.6 explainability phrase (X=100·(exp(β)−1), Y=lag, Z=most-sensitive Source-B bucket area floor). Pure numpy helpers (ols_slope_r2, best_lag, shrink) DB-free + unit-tested on synthetic series (real slope/lag recovery); compute_rate_sensitivity tested with mocked PR1/PR2. Wrong-sign guarded 3 layers; degrades to insufficient-data / EKB-wide form on thin/wrong-sign. ADVISORY until PR6 backtest — not wired into any endpoint. 28 tests (forecasting/ total 141), ruff clean. Follow-ups for PR6 backtest: validate lag selection out-of-sample (spurious-lag on short windows), confirm _SHRINK_K + confidence thresholds before prod wiring.
63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
"""Forecasting services — детерминированный форсайт-слой Site Finder v2.
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#951 (Site Finder v2 / «GG-форсайт», EPIC 7 «Чувствительность к ключевой ставке»).
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Этот пакет — фундамент data-independent логики прогноза: monthly макро-ряды,
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классификатор режима ставки, лаговые помощники. Всё ДЕТЕРМИНИРОВАННО, БЕЗ LLM.
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Слои (по PR):
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• macro_series (#951b) — monthly макро-ряд + классификатор режима ставки (X-ось §9.6).
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• sales_series (#951c) — monthly ряд продаж по сегменту (Y-ось §9.6).
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• rate_sensitivity (#951d) — §9.6 чувствительность продаж к key_rate (CORE, ADVISORY).
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• macro_coefficient (later PR) — §9.5 макро-коэффициент.
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Источники данных:
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• макро — таблица macro_indicator через reader site_finder/macro.py (reuse).
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• продажи — objective_corpus_room_month / objective_lots (см. sales_series).
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"""
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from __future__ import annotations
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from app.services.forecasting.macro_series import (
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MonthlyMacro,
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classify_regime,
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get_monthly_macro,
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is_confounded_window,
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macro_at_lag,
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)
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from app.services.forecasting.rate_sensitivity import (
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RateSensitivity,
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best_lag,
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compute_rate_sensitivity,
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ols_slope_r2,
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shrink,
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)
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from app.services.forecasting.sales_series import (
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SalesSeries,
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SegmentSpec,
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build_sales_series,
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fill_month_grid,
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log_diff,
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price_bucket_of,
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room_area_bucket_of,
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)
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__all__ = [
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"MonthlyMacro",
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"RateSensitivity",
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"SalesSeries",
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"SegmentSpec",
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"best_lag",
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"build_sales_series",
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"classify_regime",
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"compute_rate_sensitivity",
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"fill_month_grid",
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"get_monthly_macro",
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"is_confounded_window",
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"log_diff",
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"macro_at_lag",
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"ols_slope_r2",
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"price_bucket_of",
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"room_area_bucket_of",
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"shrink",
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]
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