Layout regrouped by relationship, not size: the setup-in-focus card and the radar sit side by side (they are one decision surface), the four account ribbons move directly above the open positions they describe, and a new performance chart closes the page. - Radar rows are selectable: clicking one swaps the focus card to that setup - including below-gate rows, whose card shows a muted "rank N / below gate" badge and the disqualify reason in the footer, with a "back to top pick" reset. The row currently in focus is highlighted; ticker links still deep-link without selecting. - Performance chart (the mockup's missing piece): new GET /paper-trades/equity-curve computes, per benchmark trading day since the first paper trade, the book's cumulative P&L (realized + mark-to-market from stored OHLCV) vs the same cost basis riding SPY over each trade's window (benchmark_prices). Pure curve math in paper_trade_service with unit tests; hidden until there are 2+ points of data. Frontend renders both lines with crosshair readout, zero baseline, and direct end labels. Backend unit suite: 501 passed. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
77 lines
2.4 KiB
Python
77 lines
2.4 KiB
Python
"""Unit tests for the paper-book equity curve math (pure function)."""
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from datetime import date, datetime
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from types import SimpleNamespace
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from app.services.paper_trade_service import build_equity_curve
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def _trade(**kw):
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defaults = dict(
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ticker_id=1,
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direction="long",
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entry_price=100.0,
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shares=10.0,
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status="open",
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opened_at=datetime(2026, 1, 5, 15, 0),
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closed_at=None,
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close_price=None,
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)
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defaults.update(kw)
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return SimpleNamespace(**defaults)
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BENCH = {
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date(2026, 1, 5): 500.0,
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date(2026, 1, 6): 505.0,
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date(2026, 1, 7): 510.0,
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}
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def test_open_long_marks_to_market_vs_benchmark():
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trades = [_trade()]
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ticker_closes = {1: {date(2026, 1, 5): 100.0, date(2026, 1, 6): 104.0, date(2026, 1, 7): 106.0}}
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curve = build_equity_curve(trades, ticker_closes, BENCH)
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assert [p["date"] for p in curve] == ["2026-01-05", "2026-01-06", "2026-01-07"]
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# Day 3: book +6 * 10 shares; benchmark: 1000 basis * (510-500)/500 = +20
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assert curve[-1]["book_pnl"] == 60.0
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assert curve[-1]["benchmark_pnl"] == 20.0
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def test_closed_trade_freezes_both_legs_at_close_date():
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trades = [
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_trade(
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status="closed",
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closed_at=datetime(2026, 1, 6, 21, 0),
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close_price=104.0,
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)
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]
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# Ticker keeps rising after the close — must NOT affect the curve.
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ticker_closes = {1: {date(2026, 1, 5): 100.0, date(2026, 1, 6): 104.0, date(2026, 1, 7): 999.0}}
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curve = build_equity_curve(trades, ticker_closes, BENCH)
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# Realized +4 * 10 from close date onward.
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assert curve[-1]["book_pnl"] == 40.0
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# Benchmark leg also freezes at the close date: (505-500)/500 * 1000 = +10.
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assert curve[-1]["benchmark_pnl"] == 10.0
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def test_short_direction_and_missing_ticker_prices():
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trades = [
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_trade(direction="short"),
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_trade(ticker_id=2), # no price history — contributes nothing
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]
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ticker_closes = {1: {date(2026, 1, 5): 100.0, date(2026, 1, 6): 96.0, date(2026, 1, 7): 90.0}}
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curve = build_equity_curve(trades, ticker_closes, BENCH)
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# Short: entry 100 → 90 = +10/share * 10 shares.
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assert curve[-1]["book_pnl"] == 100.0
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# Benchmark counterfactual is long-SPY for the priced trade only.
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assert curve[-1]["benchmark_pnl"] == 20.0
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def test_empty_without_trades_or_benchmark():
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assert build_equity_curve([], {}, BENCH) == []
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assert build_equity_curve([_trade()], {}, {}) == []
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