dennisthiessen
605f95098c
Part 1 — long-only. The momentum edge is long top-momentum; the gate was
qualifying shorts on high-momentum names (fighting the trend), which showed as
the -0.13R Short(qual.) drag. While the gate is active, shorts no longer qualify
(backend qualification, backtest _momentum_qualifies, and the frontend mirror).
Part 2 — production wiring. Live setups now carry a real momentum rank, so the
dashboard, the Track Record's qualified stats, and outcome evaluation all gate on
the same value instead of deferring to floors:
- new momentum_service.compute_momentum_percentiles: 12-1 momentum per ticker,
ranked across the universe into a {symbol: percentile} map.
- the daily R:R scan ranks the universe up front and stores each setup's
percentile (new trade_setups.momentum_percentile column, migration 010).
- enhance_trade_setup mutates the same row, so the percentile is preserved;
_trade_setup_to_dict + TradeSetupResponse expose it to the API.
Until a fresh scan runs, pre-existing setups have a null percentile and the gate
falls back to floors for them (longs) / excludes them (shorts) — they fill in on
the next scan. 341 backend tests pass; frontend build clean.
Needs the alembic upgrade (migration 010) on deploy.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
72 lines
2.1 KiB
Python
72 lines
2.1 KiB
Python
"""Unit tests for the cross-sectional 12-1 momentum ranking."""
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from __future__ import annotations
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from datetime import date, timedelta
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import pytest
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from app.models.ohlcv import OHLCVRecord
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from app.models.ticker import Ticker
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from app.services import momentum_service as ms
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@pytest.fixture
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async def session():
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from tests.conftest import _test_session_factory
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async with _test_session_factory() as s:
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yield s
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async def _seed(session, symbol: str, rate: float, n: int = 280) -> None:
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t = Ticker(symbol=symbol)
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session.add(t)
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await session.flush()
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base = date(2024, 1, 1)
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for i in range(n):
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close = 100.0 * (rate ** i)
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session.add(OHLCVRecord(
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ticker_id=t.id,
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date=base + timedelta(days=i),
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open=close, high=close, low=close, close=close,
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volume=1_000_000,
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))
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await session.commit()
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def test_compute_momentum_insufficient_history():
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assert ms.compute_12_1_momentum([100.0] * 100) is None
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def test_compute_momentum_value():
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closes = [100.0 * (1.01 ** i) for i in range(300)]
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m = ms.compute_12_1_momentum(closes)
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# 12-1 momentum skips the last month: close[-22] / close[-253] - 1
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assert m == closes[-22] / closes[-253] - 1.0
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assert m > 0
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async def test_ranks_universe_into_percentiles(session):
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await _seed(session, "HIGH", rate=1.010) # strong uptrend → top momentum
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await _seed(session, "MID", rate=1.002)
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await _seed(session, "LOW", rate=0.999) # declining → bottom momentum
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pct = await ms.compute_momentum_percentiles(session)
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assert pct["HIGH"] == 100.0
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assert pct["MID"] == 50.0
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assert pct["LOW"] == 0.0
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async def test_short_history_ticker_is_unranked(session):
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await _seed(session, "LONG", rate=1.005)
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await _seed(session, "SHORTHX", rate=1.005, n=100) # < 1y → no momentum
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pct = await ms.compute_momentum_percentiles(session)
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assert "LONG" in pct
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assert "SHORTHX" not in pct
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async def test_empty_universe_returns_empty(session):
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assert await ms.compute_momentum_percentiles(session) == {}
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