dennisthiessen
ebff19940b
A new /regime tab scoring how far the AI/Tech bull regime has deteriorated toward a re-rating as a single 0-100 index with per-signal breakdown and a 7/30-day trend. Intentionally decoupled: nothing reads its output to gate or score trades — the daily-pipeline membership is scheduling only. - regime_monitor_service: price sub-scores (P1-P6 via Alpaca, like market_regime), VIX + HY credit spreads via a small FRED helper, weighted aggregation over available signals (missing source -> n/a, dropped from the denominator), one snapshot row/day, and a ~90-day history backfill by replaying the already-fetched series as-of each past day. - F1/F3 fundamentals proposed by the configured grounded LLM (reuses sentiment_provider_service config resolution), with a manual override + lock. - regime_snapshots table (migration 011); endpoints on the existing market router; admin-editable weights/threshold; standalone /regime page. Data needs: prices via Alpaca, VIX/credit via FRED (optional key — signals show n/a without it). No LLM needed for history. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
27 lines
1.1 KiB
Python
27 lines
1.1 KiB
Python
from datetime import date as date_type
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from datetime import datetime
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from sqlalchemy import Date, DateTime, Float, String, Text
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from sqlalchemy.orm import Mapped, mapped_column
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from app.database import Base
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class RegimeSnapshot(Base):
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"""Daily snapshot of the AI/Tech regime-change index.
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One row per calendar date (unique). ``breakdown_json`` holds the full
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per-signal breakdown plus the raw inputs, so reads need no recomputation and
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the 7/30-day trend is just a query over ``total_score``. Decoupled from the
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rest of the platform: nothing reads this to gate or score trades.
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"""
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__tablename__ = "regime_snapshots"
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id: Mapped[int] = mapped_column(primary_key=True)
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date: Mapped[date_type] = mapped_column(Date, nullable=False, unique=True, index=True)
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total_score: Mapped[float] = mapped_column(Float, nullable=False)
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band: Mapped[str] = mapped_column(String(20), nullable=False)
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breakdown_json: Mapped[str] = mapped_column(Text, nullable=False)
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created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
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