dennisthiessen
30effa89b7
Three usability fixes: 1. Global ticker search in the sidebar (TickerSearch) — typeahead over the tracked universe that opens a ticker's detail page without adding it to the watchlist. Also wired into the mobile nav. 2. Watchlist table shows the ticker's 12-1 momentum percentile (the top-pick selector) instead of the noisy full S/R-level list. Enriched from the setup already loaded in watchlist_service._enrich_entry — no extra query. 3. Alpha vs the S&P 500 on paper trades (open + closed). New benchmark_prices table + benchmark_service store SPY daily closes (a standalone series, not a Ticker, so it never enters the scanner / momentum ranking / rankings) via a new daily-pipeline step. paper_trade_service computes per-trade benchmark_return / alpha_pct / alpha_usd over each holding period; the open- trades table, dashboard, and closed-trades panel surface per-trade and total alpha. The list read path never makes a provider call. Deploy: alembic upgrade head, then run the benchmark/daily job once to populate SPY closes (alpha shows "—" until then). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
30 lines
1.0 KiB
Python
30 lines
1.0 KiB
Python
"""Tests for benchmark return / alpha helper (pure, no DB)."""
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from __future__ import annotations
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from datetime import date
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import pytest
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from app.services.benchmark_service import benchmark_return_pct
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def test_benchmark_return_basic():
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closes = {date(2026, 1, 2): 100.0, date(2026, 1, 5): 110.0}
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assert benchmark_return_pct(closes, date(2026, 1, 2), date(2026, 1, 5)) == pytest.approx(10.0)
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def test_benchmark_return_uses_nearest_prior_trading_day():
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# No bar on the 4th (weekend) → falls back to the 2nd; as-of the 12th → the 9th.
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closes = {date(2026, 1, 2): 100.0, date(2026, 1, 9): 120.0}
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assert benchmark_return_pct(closes, date(2026, 1, 4), date(2026, 1, 12)) == pytest.approx(20.0)
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def test_benchmark_return_none_when_empty():
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assert benchmark_return_pct({}, date(2026, 1, 2), date(2026, 1, 5)) is None
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def test_benchmark_return_none_when_open_before_history():
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closes = {date(2026, 1, 10): 100.0}
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assert benchmark_return_pct(closes, date(2026, 1, 2), date(2026, 1, 12)) is None
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