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signal-platform/app/models/ticker.py
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dennisthiessenandClaude Opus 5 ad3e47dc50
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feat(universe): separate scanner membership from retained history
bootstrap_universe(prune_missing=True) ran DELETE FROM tickers, cascading OHLCV,
setups, scores and S/R levels away for any symbol that had merely dropped out of
the index. Migration 032's own comment predicted this. The survivorship audit
measured what it costs: 2.09 Sharpe against 1.57 on universe composition alone.

Migration 035 adds untracked_on, the sibling of delisted_on — delisted means the
security stopped trading, untracked means a prune took it out of the scanner.
Nothing is deleted either way.

Migration 036 separates three more things that were still conflated:

  universe_memberships       what the index actually contained, when
  tickers.untracked_on       excluded from scanning by a prune
  tickers.scan_disabled_on   the operator's own "stop scanning this"
  tickers.tracking_source    who owns the row: a bootstrap, or an operator

The operator flag is its own column because with one column serving both
writers, a prune -> re-entry cycle would clear an explicit "off" — re-entry
cannot tell who set it. Re-entry clears untracked_on and never touches
scan_disabled_on.

untracked_on is NOT current index membership. The scheduled sync runs
prune_missing=False, so a symbol can have left the index and still be scanned;
the two legitimately differ and nothing asserts they agree.

Tracking ownership is sticky towards manual: prune touches index-owned rows
only, and a bootstrap never converts manual to index — a hand-added symbol that
joins the index would otherwise lose its protection the moment it left again,
which is exactly when it is needed. An explicit add of an index-owned symbol
claims it as manual without touching either off-switch.

Membership is observed, never asserted. first_seen_on is the first live
sighting; absent_since is the first observation that found the symbol GONE, so
the interval is [first_seen_on, absent_since) — named for what it stores rather
than "last_seen_on", which would have claimed the opposite. Intervals are
append-only, so a symbol that leaves and returns has two and a point-in-time
query for the gap correctly answers "not a member". members_on() implements the
boundary rule once. A date before the first live sync returns empty: that means
"we were not looking", not "the index was empty".

A failed fetch drives nothing. The cache and seed fallbacks mean the live fetch
failed, and the seed lists are ~44 symbols against a ~500-symbol universe — a
regression test caught a seed fallback untracking 2 of 3 tickers. Recording,
pruning and clearing prune flags all require a live source; only adding still
runs, so a cold start can still bootstrap from seeds.

Migration decisions: existing rows become manual (fail-safe — a wrong guess
costs an un-pruned symbol, not one swept out of the scanner), and existing
untracked_on values are copied into scan_disabled_on, since the original writer
is ambiguous and re-entry clears the prune column.

Backtest eligibility is unchanged. _load_backtest_symbols deliberately does not
use active_only, so today's scanner state cannot erase yesterday's candidates,
and untracking a symbol still cannot silence a coverage gap in the report.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HAH7vVtn7qbcn1EVheecHQ
2026-09-07 19:30:05 +02:00

73 lines
4.7 KiB
Python

from datetime import date, datetime
from sqlalchemy import Date, String, DateTime
from sqlalchemy.orm import Mapped, mapped_column, relationship
from app.database import Base
class Ticker(Base):
__tablename__ = "tickers"
id: Mapped[int] = mapped_column(primary_key=True)
symbol: Mapped[str] = mapped_column(String(10), unique=True, nullable=False)
# Company name (e.g. "Biogen Inc."); backfilled from Alpaca, nullable for
# symbols Alpaca doesn't know.
name: Mapped[str | None] = mapped_column(String(120), nullable=True)
# SEC issuer identity, refreshed by the SEC fundamentals import from
# company_tickers.json / submissions. The only ticker<->issuer join point;
# multi-class tickers (GOOG/GOOGL) share these values. Nullable: not every
# symbol resolves to a CIK (e.g. ADRs, foreign issuers not in SEC data).
cik: Mapped[str | None] = mapped_column(String(10), nullable=True)
sic: Mapped[str | None] = mapped_column(String(4), nullable=True)
sic_description: Mapped[str | None] = mapped_column(String(160), nullable=True)
# Delisting is recorded, never deleted: the rows carry the price history that
# makes a backtest less survivorship-biased, and a delete cascades it away.
# NULL == actively traded. The live signal path filters on this (see
# ticker_service.active_only); list/admin views keep the row and show it.
delisted_on: Mapped[date | None] = mapped_column(Date, nullable=True, index=True)
# How we learned: "form_25" (SEC confirmed), "manual" (operator).
delisted_reason: Mapped[str | None] = mapped_column(String(32), nullable=True)
# The sibling of delisted_on, and the distinction matters: delisted means the
# security stopped trading; untracked means it still trades and a prune took
# it out of the scanner. Both retain every row — the delete this replaced
# cascaded away exactly the history a survivorship-honest backtest needs.
#
# This records *exclusion by pruning*, NOT current index membership. The
# scheduled sync runs prune_missing=False, so a symbol can have left the
# index and still be scanned; the two states legitimately differ. Membership
# itself lives in universe_memberships.
#
# active_only filters on it; the backtest's universe query deliberately does
# not, so today's scanner state cannot erase yesterday's candidates.
untracked_on: Mapped[date | None] = mapped_column(Date, nullable=True, index=True)
# The operator's own "stop scanning this", kept apart from the prune flag on
# purpose. If one column served both, a prune -> re-entry cycle would clear
# an explicit operator "off", because re-entry cannot tell which writer set
# it. Only set_tracked writes this; no bootstrap ever clears it.
scan_disabled_on: Mapped[date | None] = mapped_column(Date, nullable=True, index=True)
# Who owns this row's tracking: "index" (created by a universe bootstrap) or
# "manual" (an operator added it). Pruning only ever touches index-owned
# rows. Ownership is sticky towards manual — a bootstrap must never convert
# manual to index, or a hand-added symbol that happens to join the index
# would lose its protection when it later leaves.
tracking_source: Mapped[str] = mapped_column(
String(16), nullable=False, server_default="manual", default="manual"
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), default=datetime.utcnow, nullable=False
)
# Relationships (cascade deletes)
ohlcv_records = relationship("OHLCVRecord", back_populates="ticker", cascade="all, delete-orphan")
sentiment_scores = relationship("SentimentScore", back_populates="ticker", cascade="all, delete-orphan")
fundamental_data = relationship("FundamentalData", back_populates="ticker", cascade="all, delete-orphan")
sr_levels = relationship("SRLevel", back_populates="ticker", cascade="all, delete-orphan")
dimension_scores = relationship("DimensionScore", back_populates="ticker", cascade="all, delete-orphan")
composite_scores = relationship("CompositeScore", back_populates="ticker", cascade="all, delete-orphan")
trade_setups = relationship("TradeSetup", back_populates="ticker", cascade="all, delete-orphan")
watchlist_entries = relationship("WatchlistEntry", back_populates="ticker", cascade="all, delete-orphan")
ingestion_progress = relationship("IngestionProgress", back_populates="ticker", cascade="all, delete-orphan", uselist=False)
earnings_events = relationship("EarningsEvent", back_populates="ticker", cascade="all, delete-orphan")
universe_memberships = relationship("UniverseMembership", back_populates="ticker", cascade="all, delete-orphan")